tag:blogger.com,1999:blog-71426774910735956532024-03-14T13:16:38.639+07:00Big Data VietnamKnowledge Blog and Learning Community HubTrieuhttp://www.blogger.com/profile/07314868735883662234noreply@blogger.comBlogger206125tag:blogger.com,1999:blog-7142677491073595653.post-17573524706244942692023-12-14T14:10:00.002+07:002023-12-14T14:11:14.558+07:00Customer Data Platform (CDP) for smarter business<p> </p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiFKm5NcUQRIX7z7WzF7Cx5FJt8OUX2NzsZAk0dCqTZuzt0UxtmCKba5rMhbOpfNjMTR6aXDh7Br1hm1wPnUhbCldGyh3_MUlqrwVTed6Vakr97AAIsZVdIp09CAyFVjRXIJdzgmuN4eoQ4XTq37-Rwy4irjYcI5JM0x7Tbkr4N4EOE3RQxKB0G40kh3aM/s1655/USPA%20framework%20and%20LEO%20CDP-Leo%20CDP%20USPA%20flow.drawio%20(1).png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1141" data-original-width="1655" height="442" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiFKm5NcUQRIX7z7WzF7Cx5FJt8OUX2NzsZAk0dCqTZuzt0UxtmCKba5rMhbOpfNjMTR6aXDh7Br1hm1wPnUhbCldGyh3_MUlqrwVTed6Vakr97AAIsZVdIp09CAyFVjRXIJdzgmuN4eoQ4XTq37-Rwy4irjYcI5JM0x7Tbkr4N4EOE3RQxKB0G40kh3aM/s1655/USPA%20framework%20and%20LEO%20CDP-Leo%20CDP%20USPA%20flow.drawio%20(1).png" width="640" /></a></div><div><br /></div><div>Customer Data Platform (CDP) is a software that helps businesses collect, manage, and analyze customer data. It provides a single view of the customer across all channels and devices, and it can be used to track customer behavior, identify trends, and improve marketing and sales efforts.</div><div><br /></div><div>There are many different CDP vendors on the market, and each one has its own unique features and benefits. Some of the most popular CDP vendors include Salesforce, Adobe, Oracle and LEO CDP</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhoFnxem86iDaWZaaZkPPqy-K3J4CeAeu8UuBYTCaz9siTHCGj62SfeNJO0wB82EdrvSCA4StgQC5GW9W_G-jRFzXTkbUJIhAfkWyl_pHWUNeayYFj5l-6J1CbyNnTqGlkQkBIuCIuzsOlSSo0eDcVZCMmiB-I-2ZpOdzN05vENgkUfJCl8IGo6LStoz0E/s950/leocdp-matrix-features.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="653" data-original-width="950" height="440" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhoFnxem86iDaWZaaZkPPqy-K3J4CeAeu8UuBYTCaz9siTHCGj62SfeNJO0wB82EdrvSCA4StgQC5GW9W_G-jRFzXTkbUJIhAfkWyl_pHWUNeayYFj5l-6J1CbyNnTqGlkQkBIuCIuzsOlSSo0eDcVZCMmiB-I-2ZpOdzN05vENgkUfJCl8IGo6LStoz0E/s950/leocdp-matrix-features.png" width="640" /></a></div><div><br /></div><div>When choosing a CDP, it is important to consider the specific needs of your business. Some of the factors to consider include the size of your business, the amount of customer data you have, and your budget.</div><div><br /></div><div>Once you have chosen a CDP, you will need to implement it. This process can be complex and time-consuming, but it is essential to ensure that the CDP is properly configured and integrated with your other systems.</div><div><br /></div><div>Once the CDP is implemented, you can begin to use it to collect and analyze customer data. This data can be used to improve your marketing and sales efforts, and it can also be used to create personalized customer experiences.</div><div><br /></div><div>CDPs are a powerful tool that can help businesses improve their customer relationships and drive growth. If you are considering implementing a CDP, be sure to do your research and choose the right vendor for your business.</div><div><br /></div><div><b><i>Here are some of the benefits of using a CDP:</i></b></div><div><ol style="text-align: left;"><li>Improved customer experience: A CDP can help businesses create personalized customer experiences by tracking customer behavior and identifying their needs and preferences. This can lead to increased customer satisfaction and loyalty.</li><li>Increased sales: A CDP can help businesses increase sales by providing them with insights into their customers' buying habits. This information can be used to create targeted marketing campaigns and improve the customer experience.</li><li>Reduced costs: A CDP can help businesses reduce costs by automating marketing and sales tasks. This can free up employees to focus on other tasks that are more important to the business.</li></ol></div><div>If you are looking for a way to improve your customer relationships and drive growth, a CDP is a valuable tool to consider.</div><p></p>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-74976339267519970632023-05-17T17:06:00.001+07:002023-05-17T17:06:13.670+07:00Dataism - Sự khác biệt giữa Social graph và User Interest graph<p>Bản chất con người là sinh vật xã hội. Mặc dù một số người hòa đồng hơn những người khác, nhưng ngay cả những người kém năng động hơn cũng tìm kiếm các phương tiện để kết nối và kết nối. Trong thời đại này, internet là nguồn mạng xã hội phổ biến nhất, với vô số ứng dụng và nền tảng mạng xã hội. Như vậy, mọi người không còn cần phải gặp mặt trực tiếp hoặc đưa ra những cái bắt tay để giao tiếp. Chẳng hạn, Facebook, trang mạng xã hội lớn nhất toàn cầu đã vượt mốc 1 tỷ người dùng. Biểu đồ xã hội và biểu đồ sở thích là hai khía cạnh hình thành nên trải nghiệm của mạng xã hội. Mặc dù đôi khi được sử dụng như từ đồng nghĩa, cả hai đều có sự khác biệt.</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjB52ZV9DgHlGyPs9c1w_ko63latxJH6-xWYDdP0tdweXKqEKBjJUrQNski6L9J1gIaR4K6VyaLfJzTDSjisMxz1DqCXxjS26EPHk9_a3erTX947etn4KXUjf-0CtY7W4Blr09UFilc7BZ5nnwgMmQoU6C-igGheh7beNjiZ3dhCOZY4qYHiKm4FzNl/s1382/Difference-Between-Social-Graph-and-Interest-Graph-768x1382.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1382" data-original-width="768" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjB52ZV9DgHlGyPs9c1w_ko63latxJH6-xWYDdP0tdweXKqEKBjJUrQNski6L9J1gIaR4K6VyaLfJzTDSjisMxz1DqCXxjS26EPHk9_a3erTX947etn4KXUjf-0CtY7W4Blr09UFilc7BZ5nnwgMmQoU6C-igGheh7beNjiZ3dhCOZY4qYHiKm4FzNl/w356-h640/Difference-Between-Social-Graph-and-Interest-Graph-768x1382.png" width="356" /></a></div><div class="separator" style="clear: both; text-align: center;"><br /></div><h3 style="text-align: left;">Social Graph (đồ thị mạng xã hội) là gì?</h3><div>Đây là cách thể hiện cho thấy những điều cụ thể mà một cá nhân thu hút sự quan tâm dựa trên khía cạnh mà sở thích của mọi người tạo thành một phần chính trong con người họ.</div><div><br /></div><div>Vì Social Graph tạo thành một phần danh tính của một cá nhân, nên chúng có thể được sử dụng làm chỉ báo về sở thích, chẳng hạn như những gì một cá nhân có thể muốn mua, nơi họ muốn sống, người mà họ muốn bỏ phiếu, tương tác với gặp gỡ, v.v.</div><div><br /></div><div>Phổ biến với các trang mạng xã hội như LinkedIn và Facebook, nó giúp duy trì và vạch ra các mối quan hệ xã hội. Nó cũng dựa trên lý thuyết rằng người tiêu dùng có thể thích những thứ mà bạn bè thích.</div><div><br /></div><div>Social Graph hình thành các mô hình kinh doanh và doanh thu, như thường thấy trên Facebook. Do đó, các nhà quảng cáo có thể cho chúng tôi thông tin được cá nhân hóa để phân phối các quảng cáo hấp dẫn và có ý nghĩa.</div><div><br /></div><div><h3 style="text-align: left;">User Interest Graph (đồ thị sở thích người dùng) là gì?</h3><div>Đây là một đại diện trực tuyến về những thứ riêng biệt mà một người quan tâm. Chúng được sử dụng để tạo mạng lưới sở thích của một người trên các trang truyền thông xã hội như Facebook bằng cách tổ chức xung quanh sở thích của một người. Amazon cũng đã khai thác biểu đồ sở thích thông qua công cụ đề xuất, theo đó công ty cho người tiêu dùng biết những khách hàng khác có lịch sử mua hàng tương tự đã mua gì.</div><div><br /></div><div>Dựa trên giao điểm giữa nội dung trang web và biểu đồ sở thích, điều này cung cấp phương tiện cá nhân hóa trang web. Tuy nhiên, một biểu đồ sở thích chính xác phải tính đến các sở thích đã khai báo chẳng hạn như sở thích, ảnh và nhận xét được gắn thẻ cũng như lượt thích.</div><div><br /></div><div><b><i>Tầm quan trọng của User Interest Graph</i></b></div><div><ul style="text-align: left;"><li>Kết nối những người có cùng sở thích trong xã hội hoặc mạng xã hội</li><li>Nó rất quan trọng trong marketing vì nó cung cấp khả năng phân tích tập khách hàng (audience analytics) </li><li>Nó hỗ trợ lập hồ sơ hành vi trong marketing bằng cách nhắm mục tiêu người tiêu dùng dựa trên sở thích</li><li>Giúp phát triển sản phẩm thông qua việc sử dụng lợi ích của khách hàng</li></ul></div><div><br /></div><div><b>Điểm tương đồng giữa Biểu đồ xã hội và Biểu đồ sở thích</b></div><div><ul style="text-align: left;"><li>Cả hai định hình lại trải nghiệm của mạng xã hội và thị trường hàng hoá tiêu dùng</li></ul></div><div><b><i>Sự khác biệt giữa Biểu đồ xã hội và Biểu đồ sở thích</i></b></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh1s62snJNAyX1AOYKKCi4CR7ZPnYB1WdnYFhTsVMY_y9Ugq5d8YQBJlWwDCvziN-bGoswXJbd163kc1tEpeB-5ED-84SDM3x2OomKDn1uB3PgfsyrwtncAoID4mScRr5caFbdKZEpX2qQS_MpUVUdrXQS8o1SVSEhLbrGs2Vr8V3whFq-o_iG4rM1v/s1024/Difference-Between-Social-Graph-and-Interest-Graph-.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="683" data-original-width="1024" height="426" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh1s62snJNAyX1AOYKKCi4CR7ZPnYB1WdnYFhTsVMY_y9Ugq5d8YQBJlWwDCvziN-bGoswXJbd163kc1tEpeB-5ED-84SDM3x2OomKDn1uB3PgfsyrwtncAoID4mScRr5caFbdKZEpX2qQS_MpUVUdrXQS8o1SVSEhLbrGs2Vr8V3whFq-o_iG4rM1v/w640-h426/Difference-Between-Social-Graph-and-Interest-Graph-.jpeg" width="640" /></a></div><div><br /></div><div><br /></div><div>Social Graph đề cập đến một biểu diễn cho thấy những điều cụ thể mà một cá nhân thu hút sự quan tâm dựa trên khía cạnh mà sở thích của mọi người tạo thành một phần chính trong con người họ. Mặt khác, biểu đồ sở thích đề cập đến một biểu diễn trực tuyến về những thứ riêng biệt mà một người quan tâm.</div><div><br /></div><div>Trong khi Social Graph dựa trên danh tính thực của một người, User Interest Graph dựa trên những điều mà một người quan tâm.</div><div><br /></div><div><b><i>Bảng so sánh</i></b></div></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSb1YcKuj8jhmBYyIYLyYwsYMLfr8vxJWNfh0SyVOp56HRyL8PhcMreGSpXd2ozyMKLKu3Qu1MIJv55LF56thygiiOdkDhn08PU7_KmwS-F6UuDMjfTs2j-eT8P13zAY0dbQvFYv9k0XNYKPK1OjIdKfGKva3fNApMT1Z-5TsFbOx_kUQazQz5cUMG/s1086/USG-vs-UIG.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1024" data-original-width="1086" height="603" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSb1YcKuj8jhmBYyIYLyYwsYMLfr8vxJWNfh0SyVOp56HRyL8PhcMreGSpXd2ozyMKLKu3Qu1MIJv55LF56thygiiOdkDhn08PU7_KmwS-F6UuDMjfTs2j-eT8P13zAY0dbQvFYv9k0XNYKPK1OjIdKfGKva3fNApMT1Z-5TsFbOx_kUQazQz5cUMG/w640-h603/USG-vs-UIG.png" width="640" /></a></div><br /><div><br /></div><div><h3 style="text-align: left;"><b>Tóm tắt về Social graph và Interest graph</b></h3><div>Biểu đồ xã hội đề cập đến một biểu diễn cho thấy những điều cụ thể mà một cá nhân thu hút sự quan tâm dựa trên khía cạnh mà sở thích của mọi người tạo thành một phần chính trong con người họ. Mặt khác, biểu đồ sở thích đề cập đến một đại diện trực tuyến về những thứ riêng biệt mà một người quan tâm. Bất chấp sự khác biệt, cả hai đều định hình lại trải nghiệm của các mạng xã hội.</div></div><p><br /></p>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-74167045408257785152023-05-09T16:21:00.002+07:002023-05-09T16:21:15.600+07:00Free ebook: Customer Data Platforms - The Ultimate Handbook 2023<p> </p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhTsp9-cgwlpEno2me07w3BVrh8MFZAtkPyt3-p2BY-TQKfYR57iYlRRgP8E_i51V9gK81_-ZNFDxuv4Y2UTGeSZYOXW9_rI9DF8veUoK_ElBkdLXQnoVhrWzfuIz76CuV6fvJPbLPfwbP6xYvg42nO-MWxQvtzlshqYM-TKAkRDun_b78cIqJuCiDj/s672/345469666_801242254848505_1149504252855023564_n.jpeg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="672" data-original-width="512" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhTsp9-cgwlpEno2me07w3BVrh8MFZAtkPyt3-p2BY-TQKfYR57iYlRRgP8E_i51V9gK81_-ZNFDxuv4Y2UTGeSZYOXW9_rI9DF8veUoK_ElBkdLXQnoVhrWzfuIz76CuV6fvJPbLPfwbP6xYvg42nO-MWxQvtzlshqYM-TKAkRDun_b78cIqJuCiDj/s672/345469666_801242254848505_1149504252855023564_n.jpeg" width="305" /></a></div><p><i><b>Link to download ebook:</b></i></p><p></p><p><a href="https://datahub4uspa.leocdp.net/ct/2HtlqyYdyBjmEPJ4pkZwHZ"><span style="color: #2b00fe;"><b><i>https://datahub4uspa.leocdp.net/ct/2HtlqyYdyBjmEPJ4pkZwHZ</i></b></span></a></p><p></p><p><b><i>This ebook is written by Chat GPT, You.com and Bing Chat</i></b></p><p></p><p><b><i>Content is edited by Trieu Nguyen, the author of LEOCDP.com</i></b></p><p><b><i>Table of Contents</i></b></p><p><i>Chapter 1: The Rise of Customer Data Platforms</i></p><p><i>Chapter 2: Understanding Customer Data Platforms<span style="white-space: pre;"> </span></i></p><p><i>Chapter 3: Building a Unified Customer View<span style="white-space: pre;"> </span></i></p><p><i>Chapter 4: Segmentation, Personalization and Real-Time Behavioral Profiling<span style="white-space: pre;"> </span></i></p><div style="border: none; margin: 0px 0px 0px 40px; padding: 0px; text-align: left;"><p><i>What is data segmentation in CDP ?<span style="white-space: pre;"> </span></i></p><p><i>What is data personalization in CDP ?<span style="white-space: pre;"> </span></i></p><p><i>What is real-time behavioral profiling in CDP ?<span style="white-space: pre;"> </span></i></p></div><p><i>Chapter 5: Implementing CDPs: Challenges and Best Practices<span style="white-space: pre;"> </span></i></p><p><i>Chapter 6: Evaluating CDP Vendors and Solutions<span style="white-space: pre;"> </span></i></p><p><i>Chapter 7: Real-World CDP Use Cases and Success Stories</i></p><p><i>Chapter 8: The Future of Customer Data Platforms<span style="white-space: pre;"> </span></i></p><p><i>Chapter 9. Emerging trends and opportunities in customer data management<span style="white-space: pre;"> </span></i></p><p><i>Chapter 10. Conclusion: Thriving in the Age of Customer-Centricity</i></p><p><br /></p>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-46679493703593624242022-02-15T12:13:00.019+07:002023-05-09T16:23:10.572+07:00Data Engineering Roadmap 2022 for beginner<h3 style="text-align: left;">1. Programming Languages</h3><p></p><ul style="text-align: left;"><li>Python Tutorial - Python for Beginners <a href="https://www.youtube.com/watch?v=_uQrJ0TkZlc">https://www.youtube.com/watch?v=_uQrJ0TkZlc</a></li><li>Java Tutorial for Beginners <a href="https://www.youtube.com/watch?v=eIrMbAQSU34">https://www.youtube.com/watch?v=eIrMbAQSU34</a></li><li>Scala Tutorial for Beginners <a href="https://www.youtube.com/watch?v=OfngvXKNkpM">https://www.youtube.com/watch?v=OfngvXKNkpM</a></li><li>Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib) <a href="https://www.youtube.com/watch?v=LHBE6Q9XlzI">https://www.youtube.com/watch?v=LHBE6Q9XlzI</a></li></ul><p></p><h3 style="text-align: left;">2. Learn Linux</h3><br /><p>Linux Essentials - Beginner Crash Course (Ubuntu) <a href="https://www.youtube.com/watch?v=n_2jPbQornY">https://www.youtube.com/watch?v=n_2jPbQornY</a></p><div><br /></div><h3 style="text-align: left;">3. Learn about Data Structures and Algorithms</h3><div class="separator" style="clear: both; text-align: center;"><a href="https://favtutor.com/resources/images/uploads/mceu_86555629211619777343713.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="414" data-original-width="579" height="414" src="https://favtutor.com/resources/images/uploads/mceu_86555629211619777343713.jpg" width="579" /></a></div><p>DATA STRUCTURES you MUST know <a href="https://www.youtube.com/watch?v=sVxBVvlnJsM">https://www.youtube.com/watch?v=sVxBVvlnJsM</a></p><p><br /></p><h3 style="text-align: left;">4. Learn about Core DBMS (Database Management Systems)</h3><p>Learn RDBMS in 6 minutes <a href="https://www.youtube.com/watch?v=t48TGntrX4s">https://www.youtube.com/watch?v=t48TGntrX4s</a></p><h3 style="text-align: left;">5. Learn SQL</h3><p>SQL Tutorial - Full Database Course for Beginners <a href="https://www.youtube.com/watch?v=HXV3zeQKqGY">https://www.youtube.com/watch?v=HXV3zeQKqGY</a></p><p><br /></p><h3 style="text-align: left;">6. Data Exploration Libraries (Pandas — NumPy — Spark)</h3><ul style="text-align: left;"><li>PySpark Tutorial <a href="https://www.youtube.com/watch?v=_C8kWso4ne4">https://www.youtube.com/watch?v=_C8kWso4ne4</a></li><li>Data Analysis with Python - Full Course for Beginners <a href="https://www.youtube.com/watch?v=r-uOLxNrNk8">https://www.youtube.com/watch?v=r-uOLxNrNk8</a></li><li><span style="background-color: white; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; letter-spacing: -0.003em;">PySpark:</span><span style="background-color: white; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; letter-spacing: -0.003em;"> </span><a class="au tv" href="https://www.udacity.com/course/learn-spark-at-udacity--ud2002" rel="noopener ugc nofollow" style="-webkit-tap-highlight-color: transparent; background-color: white; box-sizing: inherit; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; letter-spacing: -0.003em;" target="_blank">https://www.udacity.com/course/learn-spark-at-udacity--ud2002</a></li><li><span style="background-color: white; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; letter-spacing: -0.003em;">Pandas / NumPy:</span><span style="background-color: white; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; letter-spacing: -0.003em;"> </span><a class="au tv" href="https://www.udemy.com/course/writing-production-ready-etl-pipelines-in-python-pandas/" rel="noopener ugc nofollow" style="-webkit-tap-highlight-color: transparent; background-color: white; box-sizing: inherit; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; letter-spacing: -0.003em;" target="_blank">https://www.udemy.com/course/writing-production-ready-etl-pipelines-in-python-pandas</a></li></ul><br /><h3 style="text-align: left;">7. Data Warehousing and Data Lake Concepts</h3><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://tino.org/wp-content/uploads/2021/08/word-image-21.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="484" data-original-width="800" height="387" src="https://tino.org/wp-content/uploads/2021/08/word-image-21.png" width="640" /></a></div><br /><p></p><ul style="text-align: left;"><li>What Is a Data Warehouse? <a href="https://www.youtube.com/watch?v=AHR_7jFCMeY">https://www.youtube.com/watch?v=AHR_7jFCMeY</a></li><li>What is a Data Lake? <a href="https://www.youtube.com/watch?v=v3yv88h68GY">https://www.youtube.com/watch?v=v3yv88h68GY</a></li><li>What is ETL | What is Data Warehouse | OLTP vs OLAP <a href="https://www.youtube.com/watch?v=oF_2uDb7DvQ">https://www.youtube.com/watch?v=oF_2uDb7DvQ</a></li></ul><br /><p></p><h3 style="text-align: left;">8. Learn about Distributed Computing and Cloud Computing </h3><div class="separator" style="clear: both; text-align: center;"><a href="https://upload.wikimedia.org/wikipedia/commons/thumb/b/b5/Cloud_computing.svg/1200px-Cloud_computing.svg.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="725" data-original-width="800" height="580" src="https://upload.wikimedia.org/wikipedia/commons/thumb/b/b5/Cloud_computing.svg/1200px-Cloud_computing.svg.png" width="640" /></a></div><div class="separator" style="clear: both; text-align: left;">Cloud Computing Tutorial for Beginners <a href="https://www.youtube.com/watch?v=RWgW-CgdIk0">https://www.youtube.com/watch?v=RWgW-CgdIk0</a></div><div class="separator" style="clear: both; text-align: left;">Distributed Systems | Distributed Computing Explained <a href="https://www.youtube.com/watch?v=ajjOEltiZm4">https://www.youtube.com/watch?v=ajjOEltiZm4</a></div><div class="separator" style="clear: both; text-align: left;"><br /></div><h3 style="text-align: left;">9. Workflow schedulers</h3><div class="separator" style="clear: both; text-align: center;"><br /></div>Apache Airflow for beginners <a href="https://www.youtube.com/watch?v=YWtfU0MQZ_4">https://www.youtube.com/watch?v=YWtfU0MQZ_4</a><br /><p><br /></p><h3 style="text-align: left;">10. NoSQL Databases</h3><ul style="text-align: left;"><li>Introduction to NoSQL by Martin Fowler <a href="https://www.youtube.com/watch?v=qI_g07C_Q5I">https://www.youtube.com/watch?v=qI_g07C_Q5I</a></li><li>First day with ArangoDB <a href="https://www.arangodb.com/learn/first-day/">https://www.arangodb.com/learn/first-day/</a></li><li>Redis Crash Course <a href="https://www.youtube.com/watch?v=jgpVdJB2sKQ">https://www.youtube.com/watch?v=jgpVdJB2sKQ<br /></a></li></ul><br /><div><h3 style="text-align: left;">11. Streaming Systems</h3><p>Kafka Streams 101: Getting Started <a href="https://www.youtube.com/watch?v=y9a3fldlvnI">https://www.youtube.com/watch?v=y9a3fldlvnI</a></p><h3 style="text-align: left;">12. Dashboarding tools</h3><br /><p></p><ul style="text-align: left;"><li>Google Data Studio Tutorial 2021 – Building Google Analytics Dashboards Step-by-Step <a href="https://www.youtube.com/watch?v=KouK1INq7Gg">https://www.youtube.com/watch?v=KouK1INq7Gg</a></li><li>Turn An Excel Sheet Into An Interactive Dashboard Using Python (Streamlit) <a href="https://www.youtube.com/watch?v=Sb0A9i6d320">https://www.youtube.com/watch?v=Sb0A9i6d320</a></li></ul><p></p><p><br /></p><h3 style="text-align: left;">14. Data Engineering in the Cloud</h3><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEhH-kwl-qBCuGk40hArYEYUrRki9stqLqfMp-Lk1o6hIlEvacTllzEsJ3zu5jQlN89FIVk9nSGCTN0ESMgEaOLn7P19OpnIOTRO3tZWvBiNVJut2WhcgLxlEpb41_aZ5sJ13fbbQ6j-kqWVfmn2vcKsAIc8jYdYh-EBL2fj5Q7bOaudp5MiCrivYPmL=s1505" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1505" data-original-width="1088" height="776" src="https://blogger.googleusercontent.com/img/a/AVvXsEhH-kwl-qBCuGk40hArYEYUrRki9stqLqfMp-Lk1o6hIlEvacTllzEsJ3zu5jQlN89FIVk9nSGCTN0ESMgEaOLn7P19OpnIOTRO3tZWvBiNVJut2WhcgLxlEpb41_aZ5sJ13fbbQ6j-kqWVfmn2vcKsAIc8jYdYh-EBL2fj5Q7bOaudp5MiCrivYPmL=w562-h776" width="562" /></a></div><div class="separator" style="clear: both; text-align: left;"><div class="separator" style="clear: both;">AWS Data Engineering Course - Full Course <a href="https://www.youtube.com/watch?v=ckQ7d6ca2J0">https://www.youtube.com/watch?v=ckQ7d6ca2J0</a></div><div class="separator" style="clear: both;">Google Cloud Platform Full Course <a href="https://www.youtube.com/watch?v=IUU6OR8yHCc">https://www.youtube.com/watch?v=IUU6OR8yHCc</a></div><div class="separator" style="clear: both;">Google Cloud Professional Data Engineer <a href="https://www.youtube.com/playlist?list=PLrFrRPGXX0xV7jTfXKZfGrYI0UE-MaweY">https://www.youtube.com/playlist?list=PLrFrRPGXX0xV7jTfXKZfGrYI0UE-MaweY</a></div><div><br /></div></div><h3 style="text-align: left;">15. DevOps (Docker — Kubernetes)</h3><div><br /></div>Docker and Kubernetes Tutorial | Full Course [2021] <a href="https://www.youtube.com/watch?v=bhBSlnQcq2k">https://www.youtube.com/watch?v=bhBSlnQcq2k</a></div><div><br /><h3 style="text-align: left;">16. System Design</h3><div>System Design Course for Beginners <a href="https://www.youtube.com/watch?v=MbjObHmDbZo">https://www.youtube.com/watch?v=MbjObHmDbZo</a></div>System Design Interview – Step By Step Guide <a href="https://www.youtube.com/watch?v=bUHFg8CZFws">https://www.youtube.com/watch?v=bUHFg8CZFws</a><div>System Design Mock Interview: Design Instagram <a href="https://www.youtube.com/watch?v=VJpfO6KdyWE">https://www.youtube.com/watch?v=VJpfO6KdyWE</a><br /><p>This series touches key areas in system design, which are used to design real world systems and interview questions.</p><p></p><ol style="text-align: left;"><li>Load balancing</li><li>Message Passing</li><li>Microservice architecture</li><li>NoSQL databases</li><li>Distributed Systems</li></ol><p></p><p><a href="https://www.youtube.com/playlist?list=PLMCXHnjXnTnvo6alSjVkgxV-VH6EPyvoX">https://www.youtube.com/playlist?list=PLMCXHnjXnTnvo6alSjVkgxV-VH6EPyvoX</a></p></div></div>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-28731808766234341922022-02-02T16:50:00.004+07:002022-02-02T16:51:11.889+07:00[Video Lecture] Học máy thống kê và khoa học phân tích dữ liệu lớn<p> </p><div class="separator" style="clear: both; text-align: center;"><a href="http://i3.ytimg.com/vi/bvIqG6vnxZQ/hqdefault.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="360" data-original-width="480" height="360" src="http://i3.ytimg.com/vi/bvIqG6vnxZQ/hqdefault.jpg" width="480" /></a></div><br /><p></p><p style="text-align: center;">Bài giảng đại chúng “Học máy thống kê và khoa học phân tích dữ liệu lớn” Phần 1</p>
<div style="text-align: center;"><iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/bvIqG6vnxZQ" title="YouTube video player" width="560"></iframe></div><div style="text-align: center;"><br /></div><div><div style="text-align: center;">Bài giảng đại chúng “Học máy thống kê và khoa học phân tích dữ liệu lớn” phần 2</div>
<div style="text-align: center;"><iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/SIQ3fIcfNLQ" title="YouTube video player" width="560"></iframe></div></div>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-25542781840739842382022-01-06T17:31:00.004+07:002022-01-06T17:31:39.563+07:005 Machine Learning BEGINNER Projects (+ Datasets & Solutions)<div style="text-align: center;"><iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" frameborder="0" height="315" src="https://www.youtube.com/embed/bYSeGBOLzqw" title="YouTube video player" width="560"></iframe></div><div>
<p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 0px 0px 1.25em;">I this tutorial I share 5 Beginner Machine Learning projects with you, and I give you tips how to solve all of them. These projects are for complete beginners and should teach you some basic machine learning concepts. With each project the difficulty increases a little bit and you’ll learn a new algorithm.</p><div class="separator" style="clear: both; text-align: center;"><a href="https://i3.ytimg.com/vi/bYSeGBOLzqw/maxresdefault.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="450" data-original-width="800" height="225" src="https://i3.ytimg.com/vi/bYSeGBOLzqw/maxresdefault.jpg" width="400" /></a></div><p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 0px 0px 1.25em;"><br /></p><p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 1.25em 0px;">For each project we give you an algorithm that you can use. The links to the datasets can be found below.</p><p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 1.25em 0px;">Project 1:</p><ul style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; list-style: none; margin: 1.25em 0px; padding: 0px;"><li style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; margin-bottom: 0.5em; margin-top: 0px; padding-left: 1.75em; position: relative;"><a href="https://www.kaggle.com/rsadiq/salary" rel="noopener nofollow" style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #3b82f6; margin-top: 0px; text-decoration-line: none;" target="_blank">https://www.kaggle.com/rsadiq/salary</a></li><li style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; margin-bottom: 0.5em; margin-top: 0.5em; padding-left: 1.75em; position: relative;"><a href="https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html" rel="noopener nofollow" style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #3b82f6; margin-top: 0px; text-decoration-line: none;" target="_blank">https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html</a></li></ul><p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 1.25em 0px;">Project 2:</p><ul style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; list-style: none; margin: 1.25em 0px; padding: 0px;"><li style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; margin-bottom: 0.5em; margin-top: 0px; padding-left: 1.75em; position: relative;"><a href="https://archive.ics.uci.edu/ml/datasets/iris" rel="noopener nofollow" style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #3b82f6; margin-top: 0px; text-decoration-line: none;" target="_blank">https://archive.ics.uci.edu/ml/datasets/iris</a></li><li style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; margin-bottom: 0.5em; margin-top: 0.5em; padding-left: 1.75em; position: relative;"><a href="https://github.com/allisonhorst/palmerpenguins" rel="noopener nofollow" style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #3b82f6; margin-top: 0px; text-decoration-line: none;" target="_blank">https://github.com/allisonhorst/palmerpenguins</a></li></ul><p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 1.25em 0px;">Project 3:</p><ul style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; list-style: none; margin: 1.25em 0px; padding: 0px;"><li style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; margin-bottom: 0.5em; margin-top: 0px; padding-left: 1.75em; position: relative;"><a href="https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29" rel="noopener nofollow" style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #3b82f6; margin-top: 0px; text-decoration-line: none;" target="_blank">https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+(Diagnostic)</a></li></ul><p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 1.25em 0px;">Project 4:</p><ul style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; list-style: none; margin: 1.25em 0px; padding: 0px;"><li style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; margin-bottom: 0.5em; margin-top: 0px; padding-left: 1.75em; position: relative;"><a href="https://archive.ics.uci.edu/ml/datasets/spambase" rel="noopener nofollow" style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #3b82f6; margin-top: 0px; text-decoration-line: none;" target="_blank">https://archive.ics.uci.edu/ml/datasets/spambase</a></li></ul><p style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; margin: 1.25em 0px;">Project 5:</p><ul style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; background-color: white; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #374151; font-family: ui-sans-serif, system-ui, -apple-system, "system-ui", "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size: 16px; list-style: none; margin: 1.25em 0px; padding: 0px;"><li style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; margin-bottom: 0.5em; margin-top: 0px; padding-left: 1.75em; position: relative;"><a href="https://www.kaggle.com/c/titanic/data" rel="noopener nofollow" style="--tw-blur: var(--tw-empty, ); --tw-border-opacity: 1; --tw-brightness: var(--tw-empty, ); --tw-contrast: var(--tw-empty, ); --tw-drop-shadow: var(--tw-empty, ); --tw-filter: var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow); --tw-grayscale: var(--tw-empty, ); --tw-hue-rotate: var(--tw-empty, ); --tw-invert: var(--tw-empty, ); --tw-ring-color: rgba(59,130,246,0.5); --tw-ring-inset: var(--tw-empty, ); --tw-ring-offset-color: #fff; --tw-ring-offset-shadow: 0 0 #0000; --tw-ring-offset-width: 0px; --tw-ring-shadow: 0 0 #0000; --tw-rotate: 0; --tw-saturate: var(--tw-empty, ); --tw-scale-x: 1; --tw-scale-y: 1; --tw-sepia: var(--tw-empty, ); --tw-shadow: 0 0 #0000; --tw-skew-x: 0; --tw-skew-y: 0; --tw-transform: translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-translate-x: 0; --tw-translate-y: 0; border-color: rgba(229,231,235,var(--tw-border-opacity)); border-image: initial; border-style: solid; border-width: 0px; box-sizing: border-box; color: #3b82f6; margin-top: 0px; text-decoration-line: none;" target="_blank">https://www.kaggle.com/c/titanic/data</a></li></ul><p> </p></div>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-50482426724425775622022-01-05T10:55:00.006+07:002022-01-05T10:55:34.814+07:0012 Cheat Sheets for Machine Learning, Data Science & Big Data<p></p><a href="https://i1.wp.com/datasciencedojo.com/wp-content/uploads/Mlchart3.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em; text-align: center;"><img border="0" data-original-height="519" data-original-width="800" height="416" src="https://i1.wp.com/datasciencedojo.com/wp-content/uploads/Mlchart3.jpg" width="640" /></a><br /><ol style="text-align: left;"><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PySpark_Cheat_Sheet_Python.pdf" target="_blank">PySpark - RDD Basics</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PySpark_SQL_Cheat_Sheet_Python.pdf" target="_blank">PySpark - SQL Basics</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf" target="_blank">Python Basics</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_SciPy_Cheat_Sheet_Linear_Algebra.pdf" target="_blank">SciPy - Linear Algebra</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Numpy_Python_Cheat_Sheet.pdf" target="_blank">NumPy Basics</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Pandas_Cheat_Sheet_2.pdf" target="_blank">Pandas</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf" target="_blank">Scikit-Learn</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf" target="_blank">Keras</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Matplotlib_Cheat_Sheet.pdf" target="_blank">Matplotlib</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Seaborn_Cheat_Sheet.pdf" target="_blank">Seaborn</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Python_Bokeh_Cheat_Sheet.pdf" target="_blank">Bokeh</a></li><li><a href="https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Jupyter_Notebook_Cheat_Sheet.pdf" target="_blank">Jupyter Notebook Cheat Sheet</a></li></ol><p></p><div class="separator" style="clear: both; text-align: center;"><br /></div><br />Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-50349078977409412602021-10-15T16:04:00.020+07:002021-10-21T09:59:21.247+07:00Giáo Dục Khai Phóng Libero<p> <a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIa6ogaQS9CL5p0fb7-VvnJAP9KvguruE34hvNAPNjBIfpIJ5s3qB-44rS3HOBPpNZReuHmROgb6upEqfWb02YZXtQZX48VyPysUrYuWKTTauCbSAINy0c3cD2NddFdvNoeCc0zqq6uCA/s1093/FB_IMG_1634139917740.jpg" style="color: #2196f3; display: inline-block; font-family: arial; font-size: 15px; margin-left: 1em; margin-right: 1em; text-align: center; text-decoration-line: none;"><img border="0" data-original-height="1093" data-original-width="1080" height="640" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIa6ogaQS9CL5p0fb7-VvnJAP9KvguruE34hvNAPNjBIfpIJ5s3qB-44rS3HOBPpNZReuHmROgb6upEqfWb02YZXtQZX48VyPysUrYuWKTTauCbSAINy0c3cD2NddFdvNoeCc0zqq6uCA/w632-h640/FB_IMG_1634139917740.jpg" style="border-style: none; height: inherit; max-width: 100%;" width="632" /></a></p><p style="background-color: white; color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><p style="background-color: white; color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="font-family: arial;"><span style="font-size: 11pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Chương trình tham khảo : </span><a href="https://libero.school/" style="background-color: transparent; color: #2196f3; text-decoration-line: none;"><span style="color: #1155cc; font-size: 11pt; font-variant-east-asian: normal; font-variant-numeric: normal; text-decoration-line: underline; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;">https://libero.school</span></a><span style="font-size: 11pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"> và các video, ghi chú được thêm bởi mình</span></span></p><span id="docs-internal-guid-a8b4783f-7fff-165d-e7d2-5b513e300fcb" style="background-color: white;"><div style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><p>Giáo dục cho bạn một kỹ năng, còn giáo dục khai phóng cho bạn phẩm giá - <a href="https://en.wikipedia.org/wiki/Ellen_Key" style="background-color: transparent; color: #2196f3; text-decoration-line: none;" target="_blank">ELLEN KEY</a></p></span></div><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">CHUYỂN ĐỔI TƯ DUY</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><span style="font-weight: bolder;">Chuyển đổi tư duy để học hỏi</span></span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=-71zdXCMU6A" style="background-color: transparent; color: #2196f3; text-decoration-line: none;" target="_blank">https://www.youtube.com/watch?v=-71zdXCMU6A</a> (The Growth Mindset)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=PLgbicuCANk" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=PLgbicuCANk</a> (Chọn Nghề Phù Hợp Với Tính Cách)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=a53xIhthKJ0" style="background-color: transparent; color: #2196f3; text-decoration-line: none;" target="_blank">https://www.youtube.com/watch?v=a53xIhthKJ0</a> (Công Việc Nào Phù Hợp Nhất Với Bạn?)</span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><span style="font-weight: bolder;">Tư duy phát triển</span></span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><a href="https://www.youtube.com/watch?v=PZ7lDrwYdZc" style="background-color: transparent; color: #2196f3; font-family: arial; font-size: 13.3333px; text-decoration-line: none; white-space: pre-wrap;" target="_blank">https://www.youtube.com/watch?v=PZ7lDrwYdZc</a><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"> (Atomic Habits summary)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=btp-sbwb7zM" style="background-color: transparent; color: #2196f3; text-decoration-line: none;" target="_blank">https://www.youtube.com/watch?v=btp-sbwb7zM</a> (Atomic Habits Summary & Review)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=W9DV2K4Aebw" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=W9DV2K4Aebw</a> (Mindset Book Summary - Carol Dweck)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=kkE1lC4CpIE" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=kkE1lC4CpIE</a> (Mindset: How You Can Fulfil Your Potential by Carol Dweck)</span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><span style="font-weight: bolder;">Học cách học</span></span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=O96fE1E-rf8" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=O96fE1E-rf8</a> (Learning how to learn | Barbara Oakley)</span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><span style="font-weight: bolder;">Đọc sách thông minh</span></span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=UzGyN0T4YQg" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=UzGyN0T4YQg</a> (Đọc sách sao cho hiệu quả)</span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><span style="font-weight: bolder;">Trở thành người học tập suốt đời</span></span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="font-family: arial;"><span style="color: #413500; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=DekAMet0qA8" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=DekAMet0qA8</a> (</span><span style="color: #413500;"><span style="font-size: 13.3333px; white-space: pre-wrap;">Why You NEED to be a Lifelong Learner</span></span><span style="color: #413500; font-size: 13.3333px; white-space: pre-wrap;">)</span></span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">SỰ HÌNH THÀNH CON NGƯỜI</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Điều gì làm nên con người?</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Cách mạng nhận thức</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Cách mạng nông nghiệp</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Sự thống nhất của loài người</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Cách mạng khoa học và cách mạng công nghiệp</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Con người trong thế giới hậu công nghiệp</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><span style="font-weight: bolder;"><i>Sapiens - Lược sử loài người (Yuval Noah Harari) <a href="https://youtube.com/watch?v=MQmKdviDYTg" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://youtube.com/watch?v=MQmKdviDYTg</a></i></span></span></span></li><li><span><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><b>Ý nghĩa cuộc sống | Tác giả: Albert Einstein </b></span></span></span><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><b><a href="https://www.youtube.com/watch?v=Y8X1uy40zzU">https://www.youtube.com/watch?v=Y8X1uy40zzU</a></b></span></span></li><li><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><b><i>IKIGAI LÀ GÌ?</i></b> <a href="https://www.youtube.com/watch?v=Num2rTAJX-M">https://www.youtube.com/watch?v=Num2rTAJX-M</a></span></span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">NGÔN NGỮ VÀ TƯ DUY</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Sự ra đời của ngôn ngữ</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Ngôn ngữ và tư duy</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Ngữ âm, ngữ pháp, ngữ nghĩa</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Chữ quốc ngữ</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Nâng cao năng lực biểu đạt tiếng Việt</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><a href="https://www.youtube.com/watch?v=yWMYqhOtusE" style="background-color: transparent; color: #2196f3; font-family: arial; font-size: 13.3333px; text-decoration-line: none; white-space: pre-wrap;">https://www.youtube.com/watch?v=yWMYqhOtusE</a><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"> (Chúng ta nên tiếp cận ngôn ngữ như thế nào)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://youtube.com/watch?v=bbmHwGydC2k" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://youtube.com/watch?v=bbmHwGydC2k</a> (Kỷ niệm 100 năm chữ Quốc ngữ thay cho chữ Hán ở VN)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=4YtlIJlQ570" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=4YtlIJlQ570</a> (</span><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;">Phim tài liệu - Chữ quốc ngữ theo dòng thời gian)</span></span></li><li><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=duLf6KUCHiw" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=duLf6KUCHiw</a> (Alexandre de Rhodes – Người “Hợp Thức Hóa” Chữ Quốc Ngữ Và Cuộc Đời Gây Tranh Cãi)</span></span></li><li><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=pQ33gAyhg2c" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=pQ33gAyhg2c</a> (PHILOSOPHY - Ludwig Wittgenstein)</span></span></li><li><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://chiecnon.wordpress.com/2018/05/01/ludwig-wittgenstein-nhung-cau-van-trich-tuyen/" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://chiecnon.wordpress.com/2018/05/01/ludwig-wittgenstein-nhung-cau-van-trich-tuyen/</a></span></span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">SỰ HÌNH THÀNH DÂN TỘC VIỆT NAM</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Sự hình thành tính cách dân tộc và nhà nước</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Biến động và thống nhất</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Văn hóa Việt Nam</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Người Việt – phẩm chất và thói xấu</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"></span></p><ul><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=MjeFdeEBZBo" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=MjeFdeEBZBo</a> (Tóm tắt nhanh Lịch sử Việt Nam qua 4000 năm)</span></span></li><li><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=DX_1ejhXO9k" target="_blank">https://www.youtube.com/watch?v=DX_1ejhXO9k</a> (Dân tộc "An Nam" dưới cái nhìn của thực dân)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=YZZkGk0QNrs" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=YZZkGk0QNrs</a> (Vietnam Economy- The Next China?)</span></span></li></ul><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">TRIẾT HỌC VÀ VIỆC RÈN TRÍ NGHĨ</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Triết học là gì?</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Triết học và công việc rèn trí nghĩ</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Đạo đức</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tri thức</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Luật pháp</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Hoài nghi</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tâm trí, não bộ, máy tính</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Khoa học</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tự do</span></p><ul><li><a href="https://www.youtube.com/watch?v=CH4vZ-oicw0" target="_blank">LOGIC HỌC & TƯ DUY PHẢN BIỆN</a></li><li><a href="https://www.youtube.com/watch?v=Wbz1wJMeaWs" target="_blank">GS.TS Nguyễn Hữu Liêm giới thiệu về tác phẩm - Tại Sao Đạo Phật Là Đúng</a></li><li><a href="https://www.youtube.com/watch?v=4SctCTsKj1Y" target="_blank">GS.TS Nguyễn Hữu Liêm - Chỗ đứng đạo Phật trong triết học ở Hoa Kỳ hiện nay</a></li><li><a href="https://duyendangvietnam.net.vn/nguyen-huu-liem-va-tac-pham-phac-thao-ve-mot-triet-hoc-cho-lich-su-the-gioi.html" target="_blank">Nguyễn Hữu Liêm và tác phẩm 'Phác thảo về một triết học cho lịch sử thế giới'</a></li><li><a href="https://www.youtube.com/watch?v=o-HvdDiOFms" target="_blank">Lộ trình tiến hóa của ý thức: Tư tưởng của Ken Wilber</a></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://youtube.com/watch?v=incilHT9XXM" target="_blank">Review sách: Sự An Ủi Của Triết Học (The Consolations of Philosophy)- Alain de Botton</a></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=FsDrnP973MQ" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=FsDrnP973MQ</a> (Hành Trình Bên Trong Bộ Não)</span></span></li><li><span><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=DFQfoy5Vb70">https://www.youtube.com/watch?v=DFQfoy5Vb70</a> (Nghịch lý hại não của Du Hành Thời Gian)</span></span></span></li><li><span><span style="color: #413500; font-family: arial;"><span><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=U2I1eQ9A9bk">https://www.youtube.com/watch?v=U2I1eQ9A9bk</a> (Định luật Murphy – tại sao chúng ta luôn gặp xui xẻo vào những lúc tồi tệ nhất)</span></span></span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=uEDT08tgKDM" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=uEDT08tgKDM</a> (Tâm lý học của máy tính - Khoa Học Máy Tính)</span></span></li><li><span><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=ZBmwBkr9s5c">https://www.youtube.com/watch?v=ZBmwBkr9s5c</a> (TẤT TẦN TẬT VỀ SQUID GAME)</span></span></span></li><li><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=12ntFR-APAU">https://www.youtube.com/watch?v=12ntFR-APAU</a> (MIDNIGHT MASS: Khi con người NGỘ ĐỘC niềm tin)</span></span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">GIÁO DỤC KHAI PHÓNG</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Sự trưởng thành và khai sáng</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Chức năng của giáo dục</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Về tăng trưởng</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Kinh nghiệm và tư duy</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Mục tiêu, nội dung và phương pháp</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Hứng thú và kỉ luật</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Chương trình giáo dục khai phóng: trường hợp phổ thông và người trưởng thành</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><a href="https://www.youtube.com/watch?v=WiO3_ZipLWk" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=WiO3_ZipLWk</a> (Tư duy lại về các mô hình giáo dục )</li><li><a href="https://www.youtube.com/watch?v=VBvQzlqc9cA" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=VBvQzlqc9cA</a> (Albert Einstein - Kẻ Lữ Hành Đơn Độc, Một Mình Thay Đổi Thế Giới Và Thâu Tóm Vũ Trụ)</li><li>Phim Die Ketzerbraut (Cô dâu dị giáo): <a href="https://www.youtube.com/watch?v=-pHHRgYhlRg" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=-pHHRgYhlRg</a></li><li><a href="https://www.youtube.com/watch?v=VH9jSv-NfO8" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=VH9jSv-NfO8</a> (Giáo dục khai phóng - Học để tự do | G.S Phan Văn Trường)</li><li><a href="https://www.youtube.com/watch?v=Ix5v_mbw_dg" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=Ix5v_mbw_dg</a> (5 mẹo đơn giản để có tư duy logic)</li><li><a href="https://www.youtube.com/watch?v=I1EBmzM78rk" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=I1EBmzM78rk</a> (TƯ DUY PHẢN BIỆN nâng cao sức khoẻ tinh thần)</li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">TÂM LÝ HỌC VÀ ỨNG DỤNG</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Giới thiệu tâm lý học và các lĩnh vực nghiên cứu</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Ngôn ngữ</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Nhận thức</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Cái tôi và xã hội</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Sự đa dạng và hạnh phúc</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tâm lý học lâm sàng, sức khỏe tâm thần</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=lqI23aF7T28" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=lqI23aF7T28</a> (Điều khiển não bộ của người khác)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=i3-w0S_Qei0" style="background-color: transparent; color: #2196f3; text-decoration-line: none;" target="_blank">https://www.youtube.com/watch?v=i3-w0S_Qei0</a> (NGŨ UẨN và Tâm lý học nhận thức)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=bpL0DJweAVY" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=bpL0DJweAVY</a> (Vì sao cần tìm hiểu về ngụy biện)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=_vIr3kdBxNk" target="_blank">https://www.youtube.com/watch?v=_vIr3kdBxNk</a> (Tâm Lý Học Hành vi theo dòng chảy lịch sử)</span></li><li><span style="color: #413500; font-family: arial; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=BXFGEGO8UY0" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=BXFGEGO8UY0</a> (Finding Peace of Mind)<br /></span></span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">CÁI ĐẸP VÀ CÁI HỮU DỤNG</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Cái đẹp và cái hữu dụng</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Nghệ thuật</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Thiết kế</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=2TKS1ifrhqI" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=2TKS1ifrhqI</a> (Nhập môn thiết kế UX/UI)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=RmK_ZVnCXys" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=RmK_ZVnCXys</a> (Tiêu Chuẩn Cái Đẹp Hiện Đại: "Thị Nở" Thời Xưa Lại Là Mỹ Nhân Thời Nay)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=pDKiiiGO_NA" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=pDKiiiGO_NA</a> (MỸ HỌC ĐẠI CƯƠNG - Bài mở đầu)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=4SYyxmImGB0" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=4SYyxmImGB0</a> (Thiên Tài Toàn Năng Vĩ Đại Nhất Lịch Sử Loài Người – Leonardo da Vinci)</span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">KỸ NĂNG SỐ (DIGITAL SKILL)</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Phân tích và xử lý dữ liệu với Excel</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Kỹ năng số, Khoa học dữ liệu</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">An toàn thông tin</span></p><p dir="ltr" style="line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="text-align: left;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=VH2JgqlN2so">https://www.youtube.com/watch?v=VH2JgqlN2so</a> (Làm Báo cáo & Phân tích Doanh số Bán hàng của Doanh nghiệp với Python, Pandas, và Matplotlib)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=0-B_8VJPitU" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=0-B_8VJPitU</a> (Mạng internet hoạt động như thế nào?)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=Y9FOyoS3Fag" style="background-color: transparent; color: #2196f3; text-decoration-line: none;" target="_blank">https://www.youtube.com/watch?v=Y9FOyoS3Fag</a> (The Digital Skills Gap and the Future of Jobs)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=KapHj_AQ5uE" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=KapHj_AQ5uE</a> (Why you need Digital Skills for lifelong employability)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=IGWjAI-SvQs" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=IGWjAI-SvQs</a> (Giải thích về An Ninh Mạng - Khoa Học Máy Tính)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=QnAyqnC3r0E" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=QnAyqnC3r0E</a> (TẬN DỤNG BIG DATA - BIẾN DỮ LIỆU THÀNH LỢI NHUẬN)</span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=aW7P4Y8DY9o">https://www.youtube.com/watch?v=aW7P4Y8DY9o</a> (Database, Data Lake, Data Warehouse là gì)</span></li></ul><p></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">CÁCH NỀN KINH TẾ VẬN HÀNH</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Giới thiệu kinh tế học</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Kinh tế học cổ điển</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Lý thuyết Keynes</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Giả thuyết kỳ vọng hợp lý</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Các ngân hàng trung ương</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Lạm phát</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Thị trường chứng khoán</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Suy thoái và khủng hoảng</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Chính sách tiền tệ</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Kinh tế học hành vi</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Marketing </span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><a href="https://www.youtube.com/watch?v=Ex6R370Bc40" style="background-color: transparent; color: #2196f3; font-family: arial; font-size: 13.3333px; text-decoration-line: none; white-space: pre-wrap;">https://www.youtube.com/watch?v=Ex6R370Bc40</a><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"> (Tóm tắt sách: Tâm Lý Học Về Tiền)</span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=a8UTbbIuKyY" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=a8UTbbIuKyY</a> (Adam Smith – Cha Đẻ Của Lý Thuyết “Bàn Tay Vô Hình” Và “Kinh Tế Thị Trường”)</span></span></li><li><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=2ovVtFnjaIk">https://www.youtube.com/watch?v=2ovVtFnjaIk</a> (Diện tích nhà ở xã hội: Thế nào là hợp lý?)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=VcU-Ym05EfE" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=VcU-Ym05EfE</a> (John Maynard Keynes - Nhà Kinh Tế Học Có Ảnh Hưởng Nhất Thế Kỷ 20)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=AHacTaIIOnQ" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=AHacTaIIOnQ</a> (Tư Duy: Lát Cắt Và Chuỗi)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=TIZJ25s7vzs" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=TIZJ25s7vzs</a> (NỀN KINH TẾ hoạt động như thế nào)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=-Y6uSVyO9U4" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=-Y6uSVyO9U4</a> (Kinh Tế Học: Tư Bản và Cộng Sản)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=izeZVhrRAPM" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=izeZVhrRAPM</a> (Kinh Tế Học : NIỀM TIN và NỢ CÔNG )</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=DSD1z0YkMOs" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=DSD1z0YkMOs</a> (Kinh Tế Học Hành Vi, Chủ Nghĩa Gia Trưởng Tự Do, Cú Hích)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=8ST4nIogu2A" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=8ST4nIogu2A</a> (Lịch Sử Và Cách Vận Hành Của Thị Trường Chứng Khoán)</span></span></li><li><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=StyU4bL3pyw">https://www.youtube.com/watch?v=StyU4bL3pyw</a> (BAYERN MUNICH và cách kiếm tiền của ĐỘI BÓNG MẠNH NHẤT NƯỚC ĐỨC)</span></span></li><li><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=qbBDF8DIFGk">https://www.youtube.com/watch?v=qbBDF8DIFGk</a> (Marketing là gì, có khó không?)</span></span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">CHÍNH TRỊ</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Công bằng</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Công lý</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tự do</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Luật pháp</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Hệ thống chính trị Việt Nam</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ul style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://youtube.com/watch?v=-QzhAZ-xVXc" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://youtube.com/watch?v=-QzhAZ-xVXc</a>: Plato – Vị Triết Gia Đặt Nền Móng Cho Tư Tưởng Cộng Hòa</span></li></ul><p style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"></p><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">QUẢN TRỊ VÀ LÃNH ĐẠO</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Sự hình thành quản trị</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Vai trò quản trị</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Đội nhóm và tổ chức</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Các hoạt động quản trị</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Các phong cách lãnh đạo</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Các kỹ năng lãnh đạo</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Văn hóa doanh nghiệp</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Đạo đức và trách nhiệm xã hội</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Thay đổi và chuyển hóa tổ chức</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Công nghệ và đổi mới</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"></span></p><ul><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=Gk-9Fd2mEnI" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=Gk-9Fd2mEnI</a> (The video lecture of Steve Jobs at MIT )</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=xFFs9UgOAlE" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=xFFs9UgOAlE</a> (Lecture by Mark Zuckerberg - 7 December 2005)</span></span></li><li><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=qp0HIF3SfI4">https://www.youtube.com/watch?v=qp0HIF3SfI4</a> (How great leaders inspire action)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=_MICMDfxI5k">https://www.youtube.com/watch?v=_MICMDfxI5k</a> (Cty TNHH là gì? Cty 1 thành viên là gì? Theo luật Việt Nam)</span></span></li><li><span><span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://www.youtube.com/watch?v=m689ExeJlkw" target="_blank">Thông Điệp Cho Lãnh Đạo: Nòng Cốt và Nguồn Gốc Của Quyền Lực - giáo sư Phan Văn Trường</a></span></span></li></ul><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">TINH THẦN ĐỔI MỚI</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tư duy đổi mới, khởi sự và tinh thần doanh nhân</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Sáng tạo, đổi mới, và phát minh</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Cơ hội và nhu cầu</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Giải quyết vấn đề</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Các yếu tố của mô hình kinh doanh</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tư duy thiết kế</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Khởi nghiệp tinh gọn</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Tài chính</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Con người</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"></span></p><ul><li style="color: #757575; font-family: Roboto, sans-serif;"><span><a href="https://www.youtube.com/watch?v=mtn31hh6kU4" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=mtn31hh6kU4</a> (4 simple ways to have a great idea)</span></li><li><span><a href="https://www.youtube.com/watch?v=bNpx7gpSqbY" style="background-color: transparent; color: #2196f3; font-family: Roboto, sans-serif; text-decoration-line: none;">https://www.youtube.com/watch?v=bNpx7gpSqbY</a><span face="Roboto, sans-serif" style="color: #757575;"> (The single biggest reason why startups succeed)</span></span></li><li style="color: #757575; font-family: Roboto, sans-serif;"><span><a href="https://www.youtube.com/watch?v=4nTh3AP6knM" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=4nTh3AP6knM</a> (Design Thinking Full Course)</span></li><li style="color: #757575; font-family: Roboto, sans-serif;"><span style="color: #413500; font-family: arial;"><span style="white-space: pre-wrap;"><span><a href="https://www.youtube.com/watch?v=2Vt7Ik8Ublw" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=2Vt7Ik8Ublw</a> (Scrum in under 5 minutes)</span></span></span></li><li style="color: #757575; font-family: Roboto, sans-serif;"><span style="color: #413500; font-family: arial;"><span style="white-space: pre-wrap;"><span><a href="https://www.youtube.com/watch?v=gHGN6hs2gZY" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://www.youtube.com/watch?v=gHGN6hs2gZY</a> (What Is Design Thinking? An Overview)</span></span></span></li></ul><h2 dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 18pt;"><span style="font-family: arial; font-size: 18pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">CAPSTONE PROJECT</span></h2><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;">Một dự án đổi mới, tạo ra sản phẩm/dịch vụ mới hoặc giải quyết vấn đề xã hội.
</span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"><span style="color: #413500; font-family: arial; font-size: 10pt; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><span style="font-weight: bolder;">Ví dụ đây là dự án của mình đang làm, từ những gì mình học:</span></span></p><p dir="ltr" style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px; line-height: 1.38; margin-bottom: 5pt; margin-top: 0pt;"></p><ol style="color: #757575; font-family: Roboto, sans-serif; font-size: 15px;"><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://leocdp.com/" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://leocdp.com</a></span></li><li><span style="color: #413500; font-family: arial; font-size: 13.3333px; font-variant-east-asian: normal; font-variant-numeric: normal; vertical-align: baseline; white-space: pre-wrap;"><a href="https://github.com/trieu/leo-cdp-free-edition" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://github.com/trieu/leo-cdp-free-edition</a></span></li><li><span id="docs-internal-guid-a8b4783f-7fff-165d-e7d2-5b513e300fcb"><span style="color: #413500; font-family: arial;"><span style="font-size: 13.3333px; white-space: pre-wrap;">Why LEO CDP is important for digital business:</span></span> <span style="color: #413500; font-family: arial; font-size: 13.3333px; white-space: pre-wrap;"><a href="https://youtube.com/watch?v=zWEIUxCTEiY" style="background-color: transparent; color: #2196f3; text-decoration-line: none;">https://youtube.com/watch?v=zWEIUxCTEiY</a></span></span></li></ol></span><div style="text-align: center;"><iframe allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" frameborder="0" height="400" src="https://www.youtube-nocookie.com/embed/zWEIUxCTEiY" style="width: 100%;" title="YouTube video player" width="100%"></iframe></div>
Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-5524989984085547662021-09-30T20:27:00.006+07:002021-09-30T20:29:02.890+07:00FREE DATA COURSES<div class="separator" style="clear: both; text-align: center;"><a href="https://i.ytimg.com/vi/Hnil5cRXNXs/maxresdefault.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="450" data-original-width="800" height="360" src="https://i.ytimg.com/vi/Hnil5cRXNXs/maxresdefault.jpg" width="640" /></a></div><p>Data Privacy Fundamentals <a href="https://www.coursera.org/learn/northeastern-data-privacy">https://www.coursera.org/learn/northeastern-data-privacy</a></p><p>Web of Data <a href="https://www.coursera.org/learn/web-data">https://www.coursera.org/learn/web-data</a></p><p>AI for Everyone: Master the Basics <a href="https://www.edx.org/course/artificial-intelligence-for-everyone">https://www.edx.org/course/artificial-intelligence-for-everyone</a></p><p>Using Databases with Python <a href="https://www.coursera.org/learn/python-databases">https://www.coursera.org/learn/python-databases</a></p><p>Machine Learning <a href="https://www.coursera.org/learn/machine-learning">https://www.coursera.org/learn/machine-learning</a></p><p>Data Science and Agile Systems for Product Management <a href="https://www.edx.org/course/data-science-and-agile-systems-for-product-management">https://www.edx.org/course/data-science-and-agile-systems-for-product-management</a></p><p>Learning from Data <a href="https://home.work.caltech.edu/telecourse.html">https://home.work.caltech.edu/telecourse.html</a></p><p>SQL for Data Analysis <a href="https://www.udacity.com/course/sql-for-data-analysis--ud198">https://www.udacity.com/course/sql-for-data-analysis--ud198</a></p><p>Data Science in the Games Industry <a href="https://www.futurelearn.com/courses/gaming-big-data">https://www.futurelearn.com/courses/gaming-big-data</a></p><p>Data for Better Lives: A New Social Contract <a href="https://www.edx.org/course/data-for-better-lives-a-new-social-contract">https://www.edx.org/course/data-for-better-lives-a-new-social-contract</a></p><div><br /></div>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-26911719537683955352021-05-05T13:57:00.009+07:002021-05-05T14:09:48.857+07:0075 FREE Data Science Courses on Udemy You Need to Know in 2021<p> </p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFP7kN-VYU7ZTKchVBYtc_1VL19dxkyb5XeiLE4j3AQj56eo3y15oDSOn6gGVJzzJnrfxtpqX18hdd4DorQIHX9FdLPmAAODu46VBMLBqlkbawfmLSfnm0Av5NMxAApS0dgVM0e4OY9IQ/s2048/75-FREE-Udemy-Courses-Data-Science-Courses-2048x1152.jpeg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1152" data-original-width="2048" height="360" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFP7kN-VYU7ZTKchVBYtc_1VL19dxkyb5XeiLE4j3AQj56eo3y15oDSOn6gGVJzzJnrfxtpqX18hdd4DorQIHX9FdLPmAAODu46VBMLBqlkbawfmLSfnm0Av5NMxAApS0dgVM0e4OY9IQ/w640-h360/75-FREE-Udemy-Courses-Data-Science-Courses-2048x1152.jpeg" width="640" /></a></div><br /><p></p><h2 style="background-color: white; border: 0px; box-sizing: inherit; clear: both; color: #262626; font-family: Poppins, sans-serif; font-size: 1.57895rem; font-weight: normal; line-height: 1.3; margin: 0px 0px 20px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-size: 30px; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">FREE Data Science Courses on Udemy</span></h2><p style="background-color: white; border: 0px; box-sizing: inherit; color: #262626; font-family: Poppins, sans-serif; font-size: 19px; margin: 0px 0px 1.6em; outline: 0px; padding: 0px; vertical-align: baseline;">For your convenience, I have created a table from where you can filter out the course according to <span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">Rating, Time to Complete, and Prerequisites.</span></p><figure class="wp-block-table is-style-regular" style="background-color: white; box-sizing: inherit; color: #262626; font-family: Poppins, sans-serif; margin: 0px; overflow-x: auto;"><figure class="wp-block-table is-style-regular" style="box-sizing: inherit; margin: 0px; overflow-x: auto;"><table style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-spacing: 0px; border-style: solid; border-width: 1px 0px 0px 1px; box-sizing: inherit; font-size: 19px; font-style: inherit; font-weight: inherit; margin: 0px 0px 1.5em; outline: 0px; padding: 0px; vertical-align: baseline; width: 100%;"><tbody style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">S/N</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">Course Name</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">Rating</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">Time to Complete</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">Prerequisites</span></span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">1.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintroduction-to-data-science-using-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Introduction to Data Science using Python </span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">2hr 32min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">2.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fwhat-is-data-science%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">What is Data Science?</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.3/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">40min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">3.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fpython-numpy-fundamentals%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn NumPy Fundamentals (Python Library for Data Science)</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 49min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">4.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fessentials-of-data-science-in-90-minutes%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Essentials of Data Science</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.3/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 41min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic statistics and math</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">5.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdata-science-machine-learning-data-analysis-python-r%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Science, Machine Learning, Data Analysis, Python & R</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.1/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">8hr 7min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">6.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fpython-for-every1%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Python For Data Science</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3hr 55min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">7.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fpython-tutorial-complete%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Python for Data Science – Great Learning</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.3/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 55min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">8.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fpython-crash-course-for-data-science-and-machine-learning%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Python Crash Course for Data Science and Machine Learning</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 39min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">9.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintro2dseng%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Introduction to Data Science for Complete Beginners</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 56min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">10.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintro-to-data-for-data-science%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Intro to Data for Data Science</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 1min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">11.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintroduction-to-python-for-data-science-g%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Introduction to Python For Data Science 2021</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">57min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">12.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdata-science-with-analogies-algorithms-and-solved-problems%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Science with Analogies, Algorithms and Solved Problems</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.0/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 19min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic mathematics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">13.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdatascience_with_r%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn Data Science With R Part 1 of 10</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3.9/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">8hr 42min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic Maths,Stats and Programing</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">14.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmaths-for-data-science-by-datatrained%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Maths for Data Science by DataTrained</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">55min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">10th class Level math</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">15.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdata-science-for-business-leaders-machine-learning-defined%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Science for Business Leaders: Machine Learning Defined</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 58min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">16.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fcomplete-deep-learning-course-with-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Science: Intro To Deep Learning With Python In 2021</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.3/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 54min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python Basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">17.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fhow-to-build-a-career-in-data-analytics-and-data-science%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">How To Build a Career in Data Analytics and Data Science</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.2/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 39min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">18.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fthe-complete-numpy-course-for-data-science%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">NumPy for Data Science Beginners: 2021</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.2/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 51min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python Basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">19.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmust-know-in-machine-learning%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">50 Must-Know</span> <span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">Concepts,</span> <span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">Algorithms in Machine Learning</span></span></a></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.0/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">54min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Machine Learning basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">20.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fsql-crash-course-for-aspiring-data-scientist%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">SQL Crash Course for Aspiring Data Scientist</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 24min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">21.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintro-to-machine-learning-course%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Intro To Machine Learning Course With Python: Internship</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.2/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">40min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">22.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fexplore-track-and-predict-the-iss-in-realtime-with-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Explore, Track, Predict the ISS in Realtime With Python</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.9/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 13min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">23.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fimplementation-of-ml-algorithm-using-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Implementation of ML Algorithm Using Python</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">48min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">24.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fsql-for-real-world-data-analysis%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">SQL for Data Analysis: Solving real-world problems with data</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 57min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">25.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fknime-bootcamp%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Bootcamp for KNIME Analytics Platform</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4hr 13min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">26.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flearn-python-in-80-minutes%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn Python: Python in 80 Minutes for Beginners</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 20min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">27.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintroduction-to-for-natural-language-processing%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Introduction to Spacy for Natural Language Processing</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 34min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python and Machine Learning basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">28.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flearn-data-analysis-using-pandas-and-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn Data Analysis using Pandas and Python</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.2/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 39min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">29.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fai-foundations-for-business-professionals%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">AI foundations for business professionals</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">2hr </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">30.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fweka-data-mining-with-open-source-machine-learning-tool%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">WEKA – Data Mining with Open Source Machine Learning Tool</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3hr 30min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic maths</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">31.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintroduction-to-data-analysis-for-government%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Introduction to Data Analysis for Government</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 12min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">You should be a government employee</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">32.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fr-basics%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">R Basics – R Programming Language Introduction</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4hr 6min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basics of statistics and data structure</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">33.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Ffind-actionable-insights-using-machine-learning-and-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Find Actionable Insights using Machine Learning and XGBoost</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">37min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">34.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fassociation-mining-for-machine-learning%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Association Mining for Machine Learning</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 48min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">35.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmaster-data-analysis-with-python-intro-to-pandas%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Master Data Analysis with Python – Intro to Pandas</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">5hr 9min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python Basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">36.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flogistic-regression-cancer-detection-case-study%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Logistic Regression Practical Case Study</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 4min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">The basic theory of Logistic Regression</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">37.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Facumen-presents-prasad-setty-on-googles-people-analytics%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Acumen Presents: Prasad Setty of Google on People Analytics</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">35min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">38.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fsocialcops-planning-for-data-collection%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Planning for Data Collection</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.3/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">30min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">39.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmachinelearning-analytics%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Augmented Data Visualization with Machine Learning</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3hr 15min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic Understanding of Statistics & Business Analysis</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">40.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fsmnr004-python-for-data-analysis%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Python for Data Analysis</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 10min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">41.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmachlearn2%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Polynomial Regression, R, and ggplot</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.8/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 5min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic R programming</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">42.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fnumpy-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Deep Learning Prerequisites: The Numpy Stack in Python V2</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 59min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Linear Algebra, Probability, and Python Programming</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">43.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flinear-regression-with-artificial-neural-network%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Artificial Neural Network for Regression</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 11min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Deep Learning Basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">44.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Faugmented-analytics%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Modern Data Visualization with Oracle Analytics Cloud</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3hr 54min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic Understanding of Reports and Analysis</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">45.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmachlearn1%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">R, ggplot, and Simple Linear Regression</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">2hr 14min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">46.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdata-analysis-decision-making-model-dashboards-using-excel%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Fundamentals Data Analysis & Decision Making Models – Theory</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.0/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">31min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">47.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fbaseball2%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Baseball Data Wrangling with Vagrant, R, and Retrosheet</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">2hr 10min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">R Programming basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">48.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmatplotlib-for-data-visualization-with-python-programming-language%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Visualization in Python Masterclass™ for Data Scientist</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 48min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">49.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fbig-data-analysis-with-pandas-data-frame%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Big Data Analysis With Pandas Data Frame</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 43min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">50.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flearn-data-cleaning-with-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn Data Cleaning with Python</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.1/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">50min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">51.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flearn-tableau-fundamentals%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Tableau Fundamentals for Aspiring Data Scientists</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.2/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 58min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">52.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fstatistics-literacy-for-non-statisticians%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Statistics literacy for non-statisticians</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 36min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">53.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Ftest-the-pyla-waters%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Python for linear algebra (for absolute beginners)</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.8/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 49min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">54.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fcreate-well-designed-excel-graphs%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Microsoft Excel – Basic Data Visualization in Excel</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 1min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic understanding of Excel formulas</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">55.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fpractical-deep-learning-projects%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Practical Deep Learning Projects</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.9/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 54min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Machine Learning basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">56.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fbig-data-and-hadoop-essentials-free-tutorial%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Big Data and Hadoop Essentials</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.2/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">43min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">57.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Ftechlatestnet-ai-ml%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Python AI and Machine Learning for Production & Development</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 43min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python Basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">58.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fthe-ultimate-python-and-pandas-data-analysis-course%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">The Ultimate Python and Pandas Data Analysis Course</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.2/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 1min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python Basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">59.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdataviz-with-excel%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Visualization with Excel – Crash Course</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">33min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">60.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flearn-statistical-data-analysis-with-python%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn Statistical Data Analysis with Python</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 2min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">61.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fexecutive-data-storytelling%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Executive Data Storytelling</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">30min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">62.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdata-visualization-rdkulkarni%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Visualization</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 10min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">63.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fexcel-data-visualization-for-business-analysts%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Excel Data Visualization for Business Analysts</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.3/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 12min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Excel basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">64.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintroduction-to-r%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Introduction to R</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.4/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">10hr 4min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic understanding of maths and statistics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">65.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fdata-warehouse-for-absolute-beginners%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Data Warehouse basics for absolute beginners in 30 mins</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">34min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic Database Understanding</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">66.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fexcel-data-validation-for-beginners%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Excel Data Validation For beginners</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 23min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Microsoft Excel basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">67.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fr-and-rstudio-for-beginners-a-quick-introduction%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">R and RStudio for Beginners – A Quick Introduction</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 2min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">68.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fmachlearn3%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Training Sets, Test Sets, R, and ggplot</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 30min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Basic understanding of linear and polynomial regression.</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">69.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fintroduction-to-bayesian-statistics%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Introduction to Bayesian Statistics</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 19min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Understanding of probability basics.</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">70.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fpivot-table-basics%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Microsoft Excel Pivot Tables – The Beginner Course</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/6</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">50min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Excel basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">71.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Flearnkeras%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn Keras: Build 4 Deep Learning Applications</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.3/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 29min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Python basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">72.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Ftraining-in-r-for-business-analytics-a-beginners-guide%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Learn R for Business Analytics from Basics</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3.8/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 43min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">73.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fbaseball1%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Baseball Database Queries with SQL and dplyr</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.5/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">3hr 2min</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">R Basics</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">74.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fcatboost-vs-xgboost-a-gentle-introduction%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">CatBoost vs XGBoost – Quick Intro and Modeling Basics</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.6/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">50min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">Some Python and Modeling experience</span></td></tr><tr style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline; width: 40px;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="font-size: small;">75.</span></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;"><a href="https://click.linksynergy.com/deeplink?id=Vrr1tRSwXGM&mid=39197&murl=https%3A%2F%2Fwww.udemy.com%2Fcourse%2Fgenetic-algorithm-for-machine-learning%2F" style="background-color: transparent; border: 0px; box-sizing: inherit; color: #29d0d8; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 0px; text-decoration-line: none; transition: all 0.2s linear 0s; vertical-align: baseline;"><span style="font-size: small;">Genetic Algorithm for Machine Learning</span></a></span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">4.7/5</span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">1hr 32min </span></td><td style="border-color: rgba(0, 0, 0, 0.1); border-image: initial; border-style: solid; border-width: 0px 1px 1px 0px; box-sizing: inherit; font-style: inherit; font-weight: inherit; margin: 0px; outline: 0px; padding: 8px; vertical-align: baseline;"><span style="font-size: small;">None</span></td></tr></tbody></table></figure><p style="border: 0px; box-sizing: inherit; font-size: 19px; margin: 0px 0px 1.6em; outline: 0px; padding: 0px; vertical-align: baseline;">And here the list end. So, these are the <span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">75 FREE Data Science Courses on Udemy</span>. I will keep adding <span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">more free courses</span> to this list.</p><h3 style="border: 0px; box-sizing: inherit; clear: both; font-size: 1.31579rem; font-weight: normal; line-height: 1.4; margin: 0px 0px 20px; outline: 0px; padding: 0px; vertical-align: baseline;"><span style="border: 0px; box-sizing: inherit; font-size: 25px; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">Conclusion</span></h3><p style="border: 0px; box-sizing: inherit; font-size: 19px; margin: 0px 0px 1.6em; outline: 0px; padding: 0px; vertical-align: baseline;">I hope these <span style="border: 0px; box-sizing: inherit; font-style: inherit; font-weight: 700; margin: 0px; outline: 0px; padding: 0px; vertical-align: baseline;">FREE Data Science Courses on Udemy</span> will definitely help you to enhance your data science and machine learning skills. If you have any doubt or questions, feel free to ask me in the comment section.</p><p style="border: 0px; box-sizing: inherit; font-size: 19px; margin: 0px 0px 1.6em; outline: 0px; padding: 0px; vertical-align: baseline;">All the Best!</p><p style="border: 0px; box-sizing: inherit; font-size: 19px; margin: 0px 0px 1.6em; outline: 0px; padding: 0px; vertical-align: baseline;">Enjoy Learning!</p></figure>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-18292636576301857362021-03-03T11:43:00.005+07:002021-03-03T11:43:48.768+07:00Phân tích khách hàng 360 độ là gì?<p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">#BigData #CustomerAnalytics360 #LeoCDP #Dataism</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"></span></p><div class="separator" style="clear: both; text-align: center;"><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiBdOzKfKASaxE4RKZWLDDrXUB7IIueqt28eh2YXNlp-czxdXAdB_N3hS28N1d8xNQ-oHJGk-7QCrDCWvS-IMgJG7dk7-FxxKkcUsELh-bEZq4s1AxsAQGqyVqLpQ6JWDbbV6VrkX43PZ4/s1424/154995692_10158220218669506_9107035553801808132_o.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1408" data-original-width="1424" height="633" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiBdOzKfKASaxE4RKZWLDDrXUB7IIueqt28eh2YXNlp-czxdXAdB_N3hS28N1d8xNQ-oHJGk-7QCrDCWvS-IMgJG7dk7-FxxKkcUsELh-bEZq4s1AxsAQGqyVqLpQ6JWDbbV6VrkX43PZ4/w640-h633/154995692_10158220218669506_9107035553801808132_o.jpeg" width="640" /></a></span></div><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><br /><span style="background-color: white; font-size: 14px;"><br /></span></span><p></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">Các ngành bán lẻ (Retail) và thương mại điện tử (E-commerce) thường tận dụng phân tích dữ liệu lớn để có thông tin chi tiết về khách hàng. Điều đó cho phép họ xây dựng chế độ xem khách hàng 360 (360 customer view)</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;"><b><i>Phân tích khách hàng 360 độ là gì?</i></b></span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">Phân tích khách hàng 360 độ là một bản tổng hợp rộng rãi và chính xác của tất cả thông tin về khách hàng hữu ích từ quan điểm kinh doanh.</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">Các công ty có được thông tin như vậy thông qua:</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">* Dữ liệu mạng xã hội (Social Media Analytics)</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">* Khảo sát khách hàng (Customer Survey)</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">* Dữ liệu các cuộc gọi ở bộ phận chăm sóc khách hàng</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">* Dịch vụ khách hàng, tư vấn sản phẩm</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">* Thống kê lưu lượng truy cập trang web (web analytics)</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">* Nghiên cứu thị trường</span></span></p><p><span style="font-family: system-ui, -apple-system, system-ui, .SFNSText-Regular, sans-serif;"><span style="background-color: white; font-size: 14px;">Bạn càng biết nhiều về thói quen của khách hàng, bạn càng có thể điều chỉnh sản phẩm và dịch vụ của mình để phù hợp với nhu cầu của họ. Điều đó giúp xây dựng mối quan hệ lâu dài với khách hàng của bạn. Nó cũng làm tăng khả năng giữ chân khách hàng và tạo điều kiện thuận lợi cho quá trình phát triển sản phẩm.</span></span></p>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-91180267371715007132021-01-07T15:31:00.003+07:002021-01-07T15:31:30.201+07:00On AI and the Management of Customer Relationships<p> <span style="color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px;">To a great extent, the CRM revolution that took off in the 1990s depended upon technology. Input and storage technologies enabled firms to start collecting and storing data on individual customers, and thereafter to analyze customers' profitability over time (</span><a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0085" name="bbb0085" style="box-sizing: border-box; color: #0c7dbb; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Blattberg, Glazer, & Little, 1994</a><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px;">), while smarter manufacturing systems promised mass customization (</span><a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0190" name="bbb0190" style="box-sizing: border-box; color: #0c7dbb; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gilmore & Pine, 1997</a><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px;">). Research done by leading consulting firms cited the role of the retention rate—until then, an infrequently used measure—as a significant driver of a firm's profitability (</span><a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0430" name="bbb0430" style="box-sizing: border-box; color: #0c7dbb; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Reichheld & Sasser, 1990</a><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px;">). With the first wave of the rise in data collection, storage, and analysis abilities, marketers began taking a customer lifetime value approach to managing customers (</span><a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0080" name="bbb0080" style="box-sizing: border-box; color: #0c7dbb; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Berger and Nasr, 1998</a><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px;">,</span><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px;"> </span><a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0220" name="bbb0220" style="box-sizing: border-box; color: #0c7dbb; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gupta and Lehmann, 2003</a><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px;">).</span></p><div style="box-sizing: border-box; color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px; margin: 0px; padding: 0px;"><p id="p0030" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Technology infusion into relationship management continues apace: Information technology and advanced analytics support ubiquitous customer communication and increasing availability of customer data, in turn enabling firms to offer personalized services and curating customer relationships to grow more profitable customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0445" name="bbb0445" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Rust and Huang, 2014</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0215" name="bbb0215" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gupta et al., 2020</a> this issue). At the center of marketers' attention in this regard are the emerging technologies of <em style="box-sizing: border-box; margin: 0px; padding: 0px;">artificial intelligence (AI),</em> which refer to “a system's ability to <em style="box-sizing: border-box; margin: 0px; padding: 0px;">correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”</em> (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0290" name="bbb0290" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kaplan & Haenlein, 2019</a>, p. 15). In the context of customer relationship management, these technologies enable firms to analyze data and interact with consumers faster and on a larger scale. In the longer term, enabling human-like interactions between AI-driven systems and customers will allow the provision of widespread personalized services at low cost, possibly altering the nature of customer service as they do so (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0290" name="bbb0290" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kaplan and Haenlein, 2019</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0275" name="bbb0275" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Hoyer et al., 2020</a> this issue; <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0205" name="bbb0205" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Grewal, Kroschke, Mende, Roggeveen, & Scott, 2020</a> this issue). Combining the two notions of AI and CRM, we suggest that <em style="box-sizing: border-box; margin: 0px; padding: 0px;">any CRM system exhibiting sufficiently flexible adaptation can be labeled an artificially intelligent CRM system or AI-CRM.</em></p><p id="p0035" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Our aim in this article is to examine AI systems' fundamental effects on how firms manage their relationships with their customers. There has been burgeoning discussion, in a plethora of recent publications, of the expected development of AI systems, their future ability to replace humans, and the specifics of the technologies that fall under the rubric “AI” (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0005" name="bbb0005" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Agrawal et al., 2018</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0250" name="bbb0250" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Haenlein and Kaplan, 2019</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0290" name="bbb0290" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kaplan and Haenlein, 2019</a>). Some of this work is customer-related and has focused on the expected change in the nature of customer service (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0280" name="bbb0280" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Huang and Rust, 2018</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0315" name="bbb0315" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kumar et al., 2015</a>). While we touch on some of these areas, our aim here is not to conduct another review of this topic. Instead, our focus is on the broader implications of the effects of AI-CRM on the nature of customer relationships, and in particular, the outcomes for customers and other stakeholders.</p><p id="p0040" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">The discourse on AI systems' effect on society swings wildly between utopian and dystopian (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0165" name="bbb0165" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Friend, 2018</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0500" name="bbb0500" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Tegmark, 2017</a>). Some experts cite smart machines' ability to enable individuals to have more leisure time, choose not to work at all, and enjoy longer life expectancy. Others raise the potential of massive job losses (mainly among relatively disadvantaged population segments), a fear that the machines will “take over from humans,” and an increase in disparity as the less affluent members of society are last in line to enjoy the fruits of AI (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0010" name="bbb0010" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Agrawal, Gans, & Goldfarb, 2019</a>).</p><p id="p0045" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">In terms of customer management, the overall sentiment seems positive. While there is a question of a rise in job losses in the increasingly automated service sector (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0555" name="bbb0555" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">West, 2018</a>), the emergence of AI tools is perceived as beneficial to all facets of the customer relationship management process: making it easier for consumers to obtain more personalized goods and services while at the same time increasing firms' profitability (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0320" name="bbb0320" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kumar et al., 2019</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0445" name="bbb0445" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Rust and Huang, 2014</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0215" name="bbb0215" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gupta et al., 2020</a> this issue). Yet despite the rosy picture in the marketing literature, questions remain as to the fate of customers in an AI-driven future.</p><p id="p0050" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Essentially, AI-CRM systems driven by machine learning and its successor technologies will enable managers to make improved predictions based on large quantities of collected data (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0010" name="bbb0010" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Agrawal et al., 2019</a>). This means a de facto better estimation of future individual transactions (which is to say, Customer Lifetime Value, or CLV) along with improved ability to create individual-level granular price and quality discrimination designed to increase firms' profits and reduce (or even eliminate) consumer surplus. As we will discuss, the improved ability to target and discriminate among individuals based on real-time data will likely contribute to increasing social inequality (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0550" name="bbb0550" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Wertenbroch, 2019</a>). At the same time, the loss of consumer autonomy in the age of AI (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0025" name="bbb0025" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">André et al., 2018</a>) may result in reduced consumer perception of being manipulated or discriminated against.</p><p id="p0055" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">In this article, we conduct a critical examination of how AI systems may affect the basic nature of customer relationship management. In particular, we focus on how AI's emerging abilities to manage customer relationships may result in differential treatment of customers and the implications thereof. Enhanced personalization can confer well-documented economic advantages to firms (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0305" name="bbb0305" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Khan, Lewis, & Singh, 2009</a>). In particular, the issues of identifying and leveraging the potentially significant differences across customers in terms of lifetime value have been fundamental for customer relationship management over the last two decades (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0455" name="bbb0455" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Rust, Lemon, & Zeithaml, 2004</a>). Moreover, the idea of “customer-centricity” demands the identification of a customer minority who should enjoy more attention from marketers as compared to other customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0155" name="bbb0155" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Fader, 2012</a>).</p><p id="p0060" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">AI systems' emergence is not expected to overthrow relationship marketing, but instead will render it more accurate, discriminating, and scalable. This may have a substantial effect on the fundamental nature of customer-firm relationships in multiple domains and may increase customer equity. It may have implications not only for differentiation among customers but also among firms, some of which will find competing for customers a more significant challenge over time. We argue that marketing researchers and thought leaders must gain a better understanding of AI-CRM's potential implications when contemplating how firm-customer relationships will evolve.</p><div style="box-sizing: border-box; margin: 0px; padding: 0px;"><p id="p0065" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Our paper follows the process depicted in <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#f0005" name="bf0005" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Fig. 1</a>. We first discuss two critical capabilities enabled by AI: the ability to leverage big customer data and the ability to communicate, understand, and create the way humans do. Then we move to its effects on the tasks of customer relationship management: customer acquisition, development, and retention. We conclude by focusing on AI-CRM's potential outcomes for consumers, firms, and society in general.</p><figure class="figure text-xs" id="f0005" style="border-bottom: 1px solid rgb(185, 185, 185); border-top: 1px solid rgb(185, 185, 185); box-sizing: border-box; font-size: 0.7rem; line-height: 1.57; margin: 0px 0px 20px; padding: 8px 0px 0px;"><span style="box-sizing: border-box; margin: 0px; padding: 0px;"><img alt="Fig. 1" aria-describedby="ca0005" height="230" src="https://ars.els-cdn.com/content/image/1-s2.0-S1094996820300839-gr1.jpg" style="border-style: none; box-sizing: border-box; height: auto; margin: 0px 0px 10px; max-width: 100%; padding: 0px; width: auto;" /><br /></span><span class="captions" style="box-sizing: border-box; color: #323232; font-size: 16px; line-height: 22px; margin: 16px 24px; padding: 0px;"><span id="ca0005" style="box-sizing: border-box; margin: 0px; padding: 0px;"><p id="sp0005" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;"><span class="label" style="box-sizing: border-box; margin: 0px; padding: 0px;">Fig. 1</span>. The AI-CRM effect.</p></span></span></figure></div><p id="p0070" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">We note that our focus is not prescriptive. We believe that in this stage we need to highlight the issues that arise and the problems that emerge as AI changes the ability to manage customers, and in particular to differentiate among them. A normative piece on what to do will require a separate effort. However, we do consider the matter toward the end of the paper when we discuss the role of regulators. One issue is that “doing it right” may differ depending on which perspective (firms or consumers) is weighted more heavily. It may be that similar to the case of privacy; regulators may have to intervene to make things “right” when the balance of power changes.</p><section id="s0005" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h2 class="u-h3 u-margin-l-top u-margin-xs-bottom" id="st0020" style="box-sizing: border-box; color: #505050; font-size: 1.2rem !important; font-weight: 400 !important; line-height: 1.333 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 32px !important; padding: 0px;">Capabilities</h2><p id="p0075" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">We have recently witnessed an increase in what software can do, imbued as it is with sufficient capabilities to justify the term intelligence, as defined above. We are now nearly inured to computer vision; advanced, if imperfect, robot and automotive mobility; speech recognition; real-time language translation; and victories over our human brethren in chess, go, no-limit Texas Hold'em poker and even the video game StarCraft II. Nor is there any sign that the AI capabilities trend line is diminishing. As such, it is now time to ask how such capabilities will be applied to CRM.</p><p id="p0080" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">When we refer to AI-CRM capabilities, we mean those AI capabilities useful for the interrelated CRM tasks of customer acquisition, customer retention, and customer development. Given that, we will discuss two AI-CRM capabilities: (i) leveraging big customer data, and (ii) communicating, understanding, and creating the way humans do. We believe that the prevalence of machine learning techniques in CRM has already made the potential of AI-CRM abundantly clear. Machine learning has been used to enhance relationship-acquisition advertising campaigns (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0470" name="bbb0470" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Schwartz, Bradlow, & Fader, 2017</a>) to create superior recommendations to develop existing relationships (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0410" name="bbb0410" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Overgoor, Chica, Rand, & Weishampel, 2019</a>) and to detect churn sooner to enhance relationship retention (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0045" name="bbb0045" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Ascarza, 2018</a>). Also, using human-like chatbots for communication became a well-established method for dealing with service failure and hence churn avoidance (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0120" name="bbb0120" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">De Keyser, Arne, Alkire, Verbeeck, & Kandampully, 2019</a>). These precursor examples highlight the potential for AI-CRM to leverage vast amounts of data in predicting what ads customers will click on, what products customers will like, or which customers will churn.</p><section id="s0010" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h3 class="u-h4 u-margin-m-top u-margin-xs-bottom" id="st0025" style="box-sizing: border-box; color: #505050; font-size: 1rem !important; font-weight: 400 !important; line-height: 1.4 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Leverage Big Customer Data</h3><p id="p0085" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">The Internet of Things, and related quantification and digitalization trends, lead to the obvious expectation that we will see much larger CRM datasets used by firms in the future than are used currently. Data, therefore, are increasingly a foundation for value creation and extraction. We illustrate this principle with two historical anecdotes. In 2009, Google bought the telecom company GrandCentral and rebranded it Google Voice. Among other strategic advantages, this gave Google access to an ever-growing corpus of voice messages. Google software specialists used the corpus to learn how to produce voicemail transcripts (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0075" name="bbb0075" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Beaufays, 2015</a>) and thereby gain experience with spoken speech. This capability would eventually be used in the AI behind Google's voice-activated assistant. Along the same lines, Amazon picked books as its first product category. In addition to the wide assortment of books in the market place, we believe that the choice also allowed Amazon to attract the right (i.e., more affluent, and thus more valuable) customers and leverage their browsing and transaction data to refine their future growth into other product categories. In both cases, we witnessed a unique historic opportunity to create an imperfectly imitable resource (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0060" name="bbb0060" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Barney, 1991</a>).</p><p id="p0090" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Of the three Big Data Vs (volume, variety, and velocity), we believe variety is the strongest driver of competitive advantage. In the context of AI-CRM, variety refers to the breadth and the scope of the customer database. Already, companies have house lists with thousands of data fields (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0130" name="bbb0130" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Deighton, 2019</a>). Importantly, a firm will need to be perceived as trustworthy to achieve Big Data variety through establishing multiple partnerships with external entities, thereby rendering trust (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0065" name="bbb0065" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Bart et al., 2005</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0535" name="bbb0535" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Urban et al., 2000</a>). Even more important, every time a firm seeks to capture a new type of data, there is an opportunity for the external entity that provides that data to rethink the value exchange. While increasing variety is more challenging than increasing volume, we suspect that once the volume is sufficient for separating training, test, and validation data, expanding the scope of customer data yields a proportionately stronger impact on firm performance: The more data types there are, the more opportunities there are for discovering associations therein.</p><p id="p0095" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">In summary, acquiring and maintaining more diverse data sets will be a significant source of AI-CRM competitive advantage. Interestingly enough, a firm will need to be perceived as trustworthy to achieve Big Data variety through establishing multiple partnerships with external entities, thereby rendering trust even more critical (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0065" name="bbb0065" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Bart et al., 2005</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0535" name="bbb0535" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Urban et al., 2000</a>); every time a firm seeks to capture a new type of data, there is an opportunity for the external entity providing that data to rethink the value exchange.</p></section><section id="s0015" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h3 class="u-h4 u-margin-m-top u-margin-xs-bottom" id="st0030" style="box-sizing: border-box; color: #505050; font-size: 1rem !important; font-weight: 400 !important; line-height: 1.4 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Communicate, Understand, and Create the Way Humans Do</h3><p id="p0100" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Long before our current AI era, Alan Turing suggested that one could assess AI by checking if it could fool humans into believing that they were communicating with other humans (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0520" name="bbb0520" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Turing, 1950</a>). With the growth of service chatbots, Twitter bots, and voice-activated digital assistants, it is increasingly evident that software is getting better at communicating like a human. For example, Precire is a German company whose software listens to recordings of recruitment interviews. This allows firms to do an initial screening of candidates, eliminating those whose speech rate, speech volume, number of filler sounds, sentence complexity, and word choice that can predict failure at the job (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0370" name="bbb0370" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Morrison, 2017</a>). Communications capabilities of bots and automated assistants now allow for near-human customer contact at only a modest marginal cost per contact.</p><p id="p0105" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">AI appears to be moving along a trajectory that began at mechanical capabilities, passed through analytical capabilities and intuition, and has nearly arrived at empathic capabilities, necessary to recognize and understand human emotions (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0280" name="bbb0280" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Huang & Rust, 2018</a>). We have already seen that algorithms can score one's personality better than friends, or even than oneself (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0585" name="bbb0585" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Youyou, Kosinski, & Stillwell, 2015</a>). Indeed, not only computer scientists can improve AI, but neuroscientists also work on AI, as understanding how both computers and humans learn can inform algorithm design.</p><p id="p0110" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">In fact, AI-CRM capabilities do not need to achieve full human empathy to complement or even replace human CRM judgment. Consider employees of advertising agencies as an illustration. Whether these are the mass-market advertising specialists who come up with ad execution, high-performance sales personnel who close the deal, or direct marketing copywriters whose words jump off the screen, the ability to tell a brand's story or write compelling copy has thus far been restricted to humans. There is reason to believe that this human monopoly on creative marketing capabilities has ended or will shortly end. Recently, a computer-generated work of art sold for $432,000 (for a review of AI in art and related topics, see <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0055" name="bbb0055" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Bailey, 2018</a>), and ad agencies already experiment with offering clients AI-produced ads that perform better than human-made ones (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0405" name="bbb0405" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">O'Reilly, 2017</a>).</p><p id="p0115" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">An approach known as <em style="box-sizing: border-box; margin: 0px; padding: 0px;">generative adversarial networks</em> is one example of an algorithmic approach to creative AI (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0200" name="bbb0200" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Goodfellow et al., 2014</a>). In the technique, two opposing neural networks compete against each other. One network, called the <em style="box-sizing: border-box; margin: 0px; padding: 0px;">discriminator</em>, is trained to categorize input examples (like art) as genuine or fabricated, producing a number close to or equal to 0 if the discriminator predicts that the input is fabricated, and close to or equal to 1 if the prediction is that the creative input is genuine. The other neural network, called the <em style="box-sizing: border-box; margin: 0px; padding: 0px;">generator</em>, fabricates art, feeds it to the discriminator along with real examples, and receives feedback (as mentioned, in the interval [0,1]) on how well it fooled that network. As the discriminator gets better at categorizing genuine creative work vs. the poseur's fabricated generator output, the generator gets better at creating the material that can fool the discriminator. We see no reason that such generative adversarial networks cannot be applied to executing creative CRM tasks. One near-future implementation will be making chatbots appear more human in service interactions (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0355" name="bbb0355" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Luo, Tong, Fang, & Qu, 2019</a>).</p><p id="p0120" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">We expect that the AI-CRM capabilities described above will not be easy to acquire. Competition will likely be fierce for those with the knowledge and skills to utilize AI-CRM. As location and proximity matter in the transmission of knowledge (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0050" name="bbb0050" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Audretsch & Feldman, 1996</a>), it is likely that the expertise required to train and utilize AI-CRM will concentrate within a small number of geographically proximate technology due to hubs' ability to facilitate information flow and knowledge transfer between firms (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0300" name="bbb0300" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Ketchen, Snow, & Hoover, 2004</a>). The importance of regional clusters may be mitigated by the global growth in business analytics programs.</p><p id="p0125" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">If the implementation of pre-AI CRM technology in a customer relationship context is any indication (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0100" name="bbb0100" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Bohling et al., 2006</a>), building out AI-CRM might not always go smoothly. In general, managing value creation has shifted away from managing people and things toward managing software assets like AI-CRM (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0265" name="bbb0265" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Hofacker, 2019</a>). It remains unclear how well marketers will handle this shift. Rendering AI-CRM implementation all the more daunting is the fact that AI-CRM capabilities may not reside within a single CRM system: Firms generally supplement CRM packages like SugarCRM, Salesforce CRM, or SAP CRM with a campaign management system for customer selection and targeting; and with an ERP system for tracking costs. AI-CRM requires combining different data sources stored in various applications that are often not (well) integrated.</p><p id="p0130" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">To summarize, we believe that AI-CRM will move toward improved leveraging of big customer data, and communicating, understanding, and creating the way humans do. As we will outline next, we are skeptical that all of this will lead to a value exchange utopia for both firms and customers. Let us see how this plays out in the next section, as we consider the impact on firms' abilities to acquire, develop, and retain customers and the consequent outcomes.</p></section></section><section id="s0020" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h2 class="u-h3 u-margin-l-top u-margin-xs-bottom" id="st0035" style="box-sizing: border-box; color: #505050; font-size: 1.2rem !important; font-weight: 400 !important; line-height: 1.333 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 32px !important; padding: 0px;">Customer Relationships</h2><section id="s0025" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h3 class="u-h4 u-margin-m-top u-margin-xs-bottom" id="st0040" style="box-sizing: border-box; color: #505050; font-size: 1rem !important; font-weight: 400 !important; line-height: 1.4 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Acquisition</h3><p id="p0135" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">We proceed by outlining AI-CRM's potential to improve acquisition efforts. Given that CRM, in general, aims to increase a firm's customer equity, we discuss its potential incremental effects on: (1) CLV of new customers, (2) customer acquisition costs, and (3) number of new customers.</p><p id="p0140" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Generally, firms rely on internal data to select prospects (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0105" name="bbb0105" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Cao & Gruca, 2005</a>). A recent study by <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0510" name="bbb0510" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Tillmanns, Ter Hofstede, Krafft, and Goetz (2017)</a> proposed a machine-learning algorithm to select targets for customer acquisition using data from an external vendor with personal, household, and neighborhood information. While these data are already valuable, we expect tighter integration of external data sources with individual buying behavior and interests, and broader availability at large scale with increased variety and scope. Such data will feed algorithms to further improve the selection of prospects, leading to more data, and therefore creating a positive feedback loop. In sum, AI-CRM will enhance a firm's ability to predict prospects' CLV and to use this information in managing the customer acquisition process through <em style="box-sizing: border-box; margin: 0px; padding: 0px;">selective acquisition</em>, whereby only more profitable (“better”) customers will be acquired. Furthermore, we expect AI-CRM to generate more detailed insights into the quality of acquired customers by considering the path by which the customer is acquired; that is, gaining knowledge about decision journeys of current customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0070" name="bbb0070" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Batra & Keller, 2016</a>) enables optimizing acquisition path not only in terms of the number of newly acquired customers but also concerning their quality (i.e., CLV) (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0545" name="bbb0545" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Verhoef & Donkers, 2005</a>).</p><p id="p0145" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Moreover, more precise and highly effective targeting will increase the customer conversion rate, thereby reducing customer acquisition costs. Currently, most studies pay little attention to the scope of external data but improvements in data management capabilities will enable firms not only to better identify high-CLV prospects but also to develop offerings that meet these prospects' needs.</p><p id="p0150" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Rich data on individual consumers gathered through variety of available tracking technologies (i.e., variety of data) will provide a holistic view of prospects. Firms will gain insights into prospects' pain points and the gains they are seeking. With the support of AI-CRM, firms will be able to formulate value propositions that address high-CLV prospects' needs. Firms already use morphing tools (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0530" name="bbb0530" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Urban, Liberali, MacDonald, Bordley, & Hauser, 2013</a>) to adjust online and messaging content according to prospects' needs aided. One example is the start-up Brytes, that renders consumers' digital body language visible and uses this information to identify the psychographic traits of every user of a given website in real-time and deliver the information and assistance that a consumer needs. Such developments will decrease customer acquisition costs in general, and will also affect new customers' CLV positively.</p><p id="p0155" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Another possible benefit of predictive AI is the ability to anticipate larger trends and movements, and thereby help formulate value propositions therearound. Recently, several studies using text-mining approaches have demonstrated that colossal quantities of external data like user-generated content (UGC) deliver quick and valuable insights. For example, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0125" name="bbb0125" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Decker and Trusov (2010)</a> formulated an approach to estimate aggregate consumer preferences from UGC; <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0380" name="bbb0380" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Netzer, Feldman, Goldenberg, and Fresko (2012)</a> illustrated how UGC provides an understanding of market structures and competitive landscapes; and <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0175" name="bbb0175" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gensler, Völckner, Egger, Fischbach, and Schoder (2015)</a> showed how listening to a firm's customers delivers insights into a brand's image. While in the past such studies often used lexicon-based algorithms to mine UGC, AI-flavored machine learning algorithms such as support vector machines (SVM), random forests (RF), or natural language processing (NLP) are gaining popularity and are improving marketers' ability to extract valuable insights from external text-based data (e.g., <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0260" name="bbb0260" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Hartmann et al., 2019</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0515" name="bbb0515" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Toubia et al., 2019</a>). While research on the (automated) identification of trends based on external data is currently scarce, knowledge about trends can generate a competitive advantage by creating superior value. Google Trends, for instance, has proved to be a valuable aid for firms to identify trends. For example, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0135" name="bbb0135" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Du, Hu, and Damangir (2015)</a> examined the potential of using trends in online searches for feature-related keywords as indicators of trends in the relative importance of the corresponding product features. They showed that augmenting marketing-mix data with feature search data in a market response model substantially improves such models' fit. Such developments will also facilitate the acquisition of new customers.</p><p id="p0160" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Beyond the scope of learning about prospects and trends, AI could also help firms to gather information about competitors in existing markets. For example, it could determine who is a customer of which firm and enable companies to target high CLV customers of specific competitors with personalized offerings. Furthermore, AI tools can leverage UGC to identify dissatisfied customers of competitors and to proactively address them with counteroffers. Beyond wooing away high-value competitors' customers, firms could also utilize AI to learn about their competitors' strategies by observing which customers are being targeted. In summary, AI-CRM that utilizes and combines internal and external data opens up new possibilities in the customer acquisition process, helping firms to grow their customer equity.</p></section><section id="s0030" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h3 class="u-h4 u-margin-m-top u-margin-xs-bottom" id="st0045" style="box-sizing: border-box; color: #505050; font-size: 1rem !important; font-weight: 400 !important; line-height: 1.4 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Development and Retention</h3><p id="p0165" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Following customer acquisition, two aspects of customer relationship management are key to the creation of customer profitability: <em style="box-sizing: border-box; margin: 0px; padding: 0px;">Customer development</em> refers to efforts to increase per-period profit from current customers such as increasing margin, frequency, cross-selling, or upselling. <em style="box-sizing: border-box; margin: 0px; padding: 0px;">Customer retention</em> relates to efforts to increase the <em style="box-sizing: border-box; margin: 0px; padding: 0px;">duration</em> of the customer–firm relationship. These two processes can be interrelated (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0225" name="bbb0225" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gupta & Lehmann, 2005</a>), and we will discuss possible shifts in light of several developments that we anticipate in markets where AI-CRM systems are deployed. Many AI capabilities enhancing value to the customer that were discussed in the context of customer acquisition are also relevant to development and retention. However, this section focuses on the major issues particularly notable for development and retention: <em style="box-sizing: border-box; margin: 0px; padding: 0px;">personalization</em>, <em style="box-sizing: border-box; margin: 0px; padding: 0px;">habit formation</em>, and the effect of <em style="box-sizing: border-box; margin: 0px; padding: 0px;">social networks.</em></p><section id="s0035" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h4 class="u-margin-m-top u-margin-xs-bottom" id="st0050" style="box-sizing: border-box; font-size: 1rem; font-weight: 400; line-height: 1.4; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Personalization</h4><p id="p0170" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Following our view of <em style="box-sizing: border-box; margin: 0px; padding: 0px;">AI-CRM</em> systems as those exhibiting sufficiently flexible adaptation, notable use of such systems is to enable firms to create a more personalized dialogue with customers that takes into account the former's purchasing history and interactions, and adapt the resulting marketing mix elements to the individual customer (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0320" name="bbb0320" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kumar et al., 2019</a>). While AI systems mostly perform mechanical and analytical tasks today, they will gradually move to perform communication tasks that demand the imitation of human intuition and empathy (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0280" name="bbb0280" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Huang & Rust, 2018</a>). This will, in turn, enable an interactive ability to predict individual customer needs and potentially satisfy them. A straightforward implication thereof is that we can expect greater success in developing customers and retaining them. Thus, customers' lifetime values should increase, and likewise the motivation to invest in customer acquisition.</p><p id="p0175" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">A second implication is that firms can decide who NOT to invest in. While currently, many efforts to develop and retain customers are geared toward the customer population in general, managers are still encouraged to focus only on those customers who will create strategic advantage (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0155" name="bbb0155" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Fader, 2012</a>), and AI-CRM-driven personalization will enable firms to increasingly move in this direction. Thus, we expect to see increasing use of <em style="box-sizing: border-box; margin: 0px; padding: 0px;">selective development and retention</em> that focus only on a subset—sometimes a small one—of customers. Indeed, across a variety of markets such as communications, apparel, cars, travel, and credit cards, the decision to invest and effort to retain (e.g., by better service and perks) is based on customers' expected lifetime value (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0460" name="bbb0460" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Safdar, 2018</a>). Given differences in expected customer profitability, marketers are also advised to be selective about which customers they aim to reactivate (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0315" name="bbb0315" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kumar et al., 2015</a>). Similar considerations apply for the decisions on whether to develop a customer, in particular since some customers are not profitable to begin with (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0490" name="bbb0490" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Shah, Kumar, Qu, & Chen, 2012</a>). Thus, consultancies advise firms to focus on their cross-selling campaigns on high-value customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0480" name="bbb0480" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Senior, Springer, & Sherer, 2016</a>). We will further expand upon selective development when we consider the outcome for customers later.</p></section><section id="s0040" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h4 class="u-margin-m-top u-margin-xs-bottom" id="st0055" style="box-sizing: border-box; font-size: 1rem; font-weight: 400; line-height: 1.4; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Habit formation</h4><p id="p0180" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Considering the role of technology in retention and development raises the need to discuss what has emerged in recent years as a fundamental issue in our understanding of why customers continue to do what they do, or <em style="box-sizing: border-box; margin: 0px; padding: 0px;">habit formation</em> (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0140" name="bbb0140" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Duhigg, 2012</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0485" name="bbb0485" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Shah et al., 2014</a>). New technologies play a unique role in creating habit (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0150" name="bbb0150" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Eyal, 2014</a>), and thus AI is likely to play a role in how habits affect (or not) consumer decision-making.</p><p id="p0185" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Increasingly managers are encouraged to adjust their thinking by focusing on customer habits instead of customer loyalty as the driver of market success (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0325" name="bbb0325" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Lafley & Martin, 2017</a>). That view is consistent with an increasing emphasis in the business and academic literature on habits as critical drivers of customer behavior (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0140" name="bbb0140" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Duhigg, 2012</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0150" name="bbb0150" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Eyal, 2014</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0575" name="bbb0575" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Wood and Rünger, 2016</a>). Habit-forming behavior is, by definition, governed by automaticity. It requires minimal cognitive attention and is strongly related to the frequency of previous behavior occurring in a stable and recurring context (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0485" name="bbb0485" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Shah et al., 2014</a>). Beyond simple repeat purchases, habits may drive decision-making in various other stages of the customer journey such as response to promotions, returning products, and making dedicated shopping trips (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0485" name="bbb0485" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Shah et al., 2014</a>).</p><p id="p0190" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">One might wonder whether the AI revolution is not antithetical to that of habit-forming behavior, because as decisions become less complex, less AI-based intervention will be needed. We contend, however, that AI will make habit-forming behavior more widespread, and help firms to manage their customer relationships via habits.</p><p id="p0195" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">AI-CRM's ability to encourage consumer automaticity can be complemented with the ability to track habit-forming behavior and other aspects of the consumers' environment. Using Internet of Things (IoT) data inputs, various sensors around the consumer can collect and analyze information on the status of products, stockouts, and the need for refills. Easy transmission mechanisms such as Amazon's Alexa enable customers to order products nearly effortlessly. Machine learning algorithms can be used to identify needs promptly and offer customers a reasonable alternative right away. As algorithms do a better job of providing the right product at the right time, consumers' trust therein will increase, as well as their willingness to skip the search process and rely on the firm.</p><p id="p0200" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">This development, in turn, builds up a cumulative advantage over time: the more one uses the firm, the more one is used to it and the habits associated with it, the higher the likelihood that one will continue to purchase therefrom (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0325" name="bbb0325" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Lafley & Martin, 2017</a>). Also, the more data are gathered, the better the firm can learn the individual's needs and preferences, and further use this information to strengthen the habit.</p><p id="p0205" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">With better-tailored solutions, customers of direct-to-consumer businesses will be less likely to shop for alternatives. As buyers increasingly trust the seller, and as data become more available, firms can further enhance current algorithms' abilities to get the right product to the right customer at the right time (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0345" name="bbb0345" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Li, Sun, & Montgomery, 2011</a>). Consequently, we expect the AI-CRM-led “habit economy” to improve firms' ability to cultivate their customers. AI-CRM systems will help to prevent cross-selling to non-profitable customers and increase the motivation for profitable cross-selling activities (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0490" name="bbb0490" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Shah et al., 2012</a>).</p><p id="p0210" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">In terms of retention, once a habit-forming relationship starts, customers put less effort into renewed decision-making, as the latter creates de facto switching costs for the customer. Via past behavior and the information that they have provided in the past, customers have enabled their service provider to learn their tastes and wants. Moving to a new provider would demand new learning, and the better the job current providers do, the higher the switching costs. To the extent that AI-CRM improves CRM, switching costs will increase. Given that even low switching costs can create a lock-in effect with customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0090" name="bbb0090" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Blut et al., 2015</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0590" name="bbb0590" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Zauberman, 2003</a>), we expect AI-CRM leaders to improve their retention of desirable customers.</p><p id="p0215" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Note, though, that AI systems may not only increase switching costs for current customers, but new firms may be able to use the AI-driven learning process to reduce switching costs to them and so attract customers, as we also discuss in the <em style="box-sizing: border-box; margin: 0px; padding: 0px;">Acquisition</em> section. The question is then which force will be stronger, retention or acquisition? AI capabilities depend heavily upon the use of large volume and variety of customer data to learn and adapt, and these data are much more likely to be available for current rather than potential customers. Thus, we expect that overall, AI-CRM effect on increasing switching costs for current customers will be higher than its effect on lowering switching costs by competitors.</p><p id="p0220" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;"><em style="box-sizing: border-box; margin: 0px; padding: 0px;">Agents and habit formation</em>. AI enabled the rising popularity of smart assistants such as Alexa, Siri, or Bixby that help individuals in their everyday activities, many of which are consumption-related. As AI-CRM systems develop and smart assistants gain more access to product data and consumer input on a wide range of products, habits, and practices, they may become much better in identifying products and solutions that meet customer needs.</p><p id="p0225" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">This contributes to the process of habit formation: The more the smart assistants learn how to anticipate and understand user needs, the more customers will get into the habit of trusting them to make decisions, with the implications for development and retention discussed above. However, the assistants operate at the platform level, not at the individual brand level, and thus platform-enabled brand choice by customers may be affected by the economic interests of the platform. Further, platforms may restrict brand access to customer data, to preserve the advantage in understanding customer needs. This would mean that for consumers who buy directly from the brand, personalization and habit formation may help to create higher brand-specific customer lifetime value. For consumers buying through assistants, lifetime value depends on the assistant's actions. In other words, the assistant's interests and preferences will mediate the brand-related lifetime value created in this case.</p><p id="p0230" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">The ability of agents to affect habit formation raises an important point that should be emphasized. AI can be used not only to build on and sustain existing customer habits but also to learn how to form new or break old habits. AI systems can leverage customers' responses to past interventions for stimulating habit formation. More generally, using AI-CRM to optimize timing, frequency and intensity of firm interventions can create and strengthen customer habits much more effectively than marketers do this today.</p></section><section id="s0045" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h4 class="u-margin-m-top u-margin-xs-bottom" id="st0060" style="box-sizing: border-box; font-size: 1rem; font-weight: 400; line-height: 1.4; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Role of Social Networks</h4><p id="p0235" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Emerging research points to the role of social influence in customer development and retention. Due to the expected homophily in purchase patterns among social network members (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0255" name="bbb0255" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Haenlein & Libai, 2013</a>), information on members of the social network and their consumption can serve as valuable input into the choices of which products are optimal candidates for the development of focal customers. Given the evidence on customer churn's social impact (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0230" name="bbb0230" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Haenlein, 2013</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0395" name="bbb0395" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Nitzan and Libai, 2011</a>), the social network information can become an integral part of churn prediction and management.</p><p id="p0240" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Despite of the established importance of social networks' role in customer decision-making and profitability (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0330" name="bbb0330" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Lamberton and Stephen, 2016</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0375" name="bbb0375" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Muller and Peres, 2019</a>), most marketers are still not taking advantage of customer connectivity information given the difficulties in the identification and analysis of customer networks for specific products. Due to the complexity of the analysis, much of the investigation to date had been restricted to using data on relatively small social networks. AI applications will allow such investigations to expand and deepen, enabling a much better leveraging of customer network data. Advanced machine-learning tools allow for the identification of social networks and of particular communities within the networks using a variety of online data (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0210" name="bbb0210" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Guerrero et al., 2017</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0420" name="bbb0420" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Perozzi et al., 2014</a>). Driven by smartphone ubiquity, location-based data can further enhance the ability to identify customer social networks using advanced machine learning techniques to analyze these large-scale data (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0145" name="bbb0145" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Eagle, Pentland, & Lazer, 2009</a>). This network data can then be used to better personalize the interaction with customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0110" name="bbb0110" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Chung, Wedel, & Rust, 2016</a>).</p><p id="p0245" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">The use of social network information has implications for all three aspects of customer management: acquisition, development, and retention. The role of social network analysis in optimizing customer acquisition, in particular in the context of new product growth, has been much cited in the marketing literature (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0375" name="bbb0375" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Muller and Peres, 2019</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0395" name="bbb0395" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Nitzan and Libai, 2011</a>). Yet, since large-scale data on customers and their social interactions are more available for current customers than for potential ones, we believe that the use of AI to conduct social network analysis will have higher impact on customer development and retention. This will be particularly relevant to products such as digital games, where customers' social network activities are routinely collected (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0350" name="bbb0350" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Liu, Liao, Chen, & Chiu, 2019</a>).</p></section></section></section><section id="s0050" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h2 class="u-h3 u-margin-l-top u-margin-xs-bottom" id="st0065" style="box-sizing: border-box; color: #505050; font-size: 1.2rem !important; font-weight: 400 !important; line-height: 1.333 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 32px !important; padding: 0px;">Outcomes</h2><section id="s0055" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h3 class="u-h4 u-margin-m-top u-margin-xs-bottom" id="st0070" style="box-sizing: border-box; color: #505050; font-size: 1rem !important; font-weight: 400 !important; line-height: 1.4 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Customer-Related Outcomes</h3><p id="p0250" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Given AI's aforementioned abilities, we consider outcomes for customers, firms, and markets in general, starting with customers. Indeed, many customers may enjoy enhanced personal service, the benefit likely to become less costly as technology enables firms to replace humans in an increasing number of service jobs. However, as follows from the previous discussion on selective acquisition, development, and retention, AI-CRM is not likely to deliver such benefits equally to all consumers. We next elaborate on the reasons therefor.</p><section id="s0060" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h4 class="u-margin-m-top u-margin-xs-bottom" id="st0075" style="box-sizing: border-box; font-size: 1rem; font-weight: 400; line-height: 1.4; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Customer Prioritization</h4><p id="p0255" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Historically, as customer databases began to provide indications of concentration in customer profitability (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0595" name="bbb0595" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Zeithaml, Rust, & Lemon, 2001</a>), firms moved toward <em style="box-sizing: border-box; margin: 0px; padding: 0px;">customer prioritization</em> under which customers are treated differently based on expected profitability (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0270" name="bbb0270" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Homburg, Droll, & Totzek, 2008</a>). Overall, customer prioritization is viewed as a useful tool for managing customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0450" name="bbb0450" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Rust, Kumar, & Venkatesan, 2011</a>). Indeed, evidence from multiple industries suggests that service levels are related to customers' expected profitability (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0115" name="bbb0115" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Daily Kos, 2016</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0460" name="bbb0460" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Safdar, 2018</a>) and that the differences may have widened in recent years (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0475" name="bbb0475" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Schwartz, 2016</a>). Differing treatment can apply to any part of the marketing mix, including the level of service, price, and promotion; it can even lead to customer abandonment (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0245" name="bbb0245" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Haenlein & Kaplan, 2012</a>).</p><p id="p0260" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">It is commonly assumed that better CLV prediction by AI-CRM would allow for greater discrimination across the CLV distribution. Since the customer profitability distribution often resembles a Pareto more than a Normal (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0160" name="bbb0160" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Fader & Toms, 2018</a>), AI-CRM's predictive ability will motivate firms to focus their efforts and investments on a relatively small segment of the CLV distribution. The same CLV distribution may therefore further increase disparity (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0400" name="bbb0400" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">O'Neill, 2016</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0550" name="bbb0550" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Wertenbroch, 2019</a>).</p><p id="p0265" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">As data collection and mining techniques have improved, marketers have gained the ability to identify and track individual customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0030" name="bbb0030" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Andrews et al., 2016</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0390" name="bbb0390" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Ngai et al., 2009</a>). Still, up until now, marketers have been restricted in their ability to apply customer prioritization at scale due to limitations on available information on individuals and capabilities required to reliably integrate and analyze information from multiple sources in real-time. For example, consumer spending volatility has been shown to restrict firms' ability to predict customer lifetime value (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0450" name="bbb0450" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Rust et al., 2011</a>).</p><p id="p0270" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">AI-CRM systems will incrementally allow marketers to overcome such issues. AI-CRM will enable rapid response personalization that stems from the improved identification of customers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0435" name="bbb0435" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Roberts, 2019</a>), faster and more precise updates of future profitability using machine learning (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0365" name="bbb0365" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Martínez, Schmuck, Pereverzyev Jr, Pirker, & Haltmeier, 2018</a>), and, more generally, the ability to obtain individual-level information from the traces that consumers leave on their journeys (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0415" name="bbb0415" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Padilla, Ascarza, & Netzer, 2019</a>). It will enable rapid, time-sensitive decisions to invest in the right customer acquisition and the practice of selective development and retention. For some consumers, this will mean higher incentives to become firm customers at the acquisition stage, better goods and services at the development stage, and possibly even getting lower prices motivated by the retention consideration. Other consumers will be selectively under-acquired, under-developed, and under-retained.</p><p id="p0275" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Since by definition only a minority of customers can be prioritized, overall satisfaction of the customer base can decrease (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0180" name="bbb0180" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gerstner & Libai, 2006</a>). Further, customer prioritization affects customer entitlement and word of mouth (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0560" name="bbb0560" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Wetzel, Hammerschmidt, & Zablah, 2014</a>). There can be also legal implications where minorities or other segments are discriminated against (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0525" name="bbb0525" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Ukanwa & Rust, 2018</a>). This does not imply, however, that customers will not be served: For some less profitable customers, new businesses will emerge whose offerings will match their ability and willingness to pay (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0440" name="bbb0440" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Rosenblum, Tomlinson, & Scott, 2003</a>). For many, it will simply mean different levels of the marketing mix. Yet generally and for many consumers, this will mean a substantial reduction in the quality of products and possibly higher prices, of which they may not be even aware: Due to the ability to target individuals and the aforementioned habit formation process, prioritization will not necessarily be noticed.</p><p id="p0280" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">This targeting ability is not restricted to the purchase process but can be implemented in all aspects of the customer relationship spectrum. For example, recent research in the legal literature warns against sellers' ability to use big data and predictive analytics to identify frequently complaining customers and avoid selling to or disarming them before they can draw attention to sellers' misconduct (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0035" name="bbb0035" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Arbel & Shapira, 2020</a>).</p></section><section id="s0065" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h4 class="u-margin-m-top u-margin-xs-bottom" id="st0080" style="box-sizing: border-box; font-size: 1rem; font-weight: 400; line-height: 1.4; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Income Inequality and Prioritization</h4><p id="p0285" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">The considerable increase in income disparity in various parts of the world in the last three decades (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0425" name="bbb0425" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Piketty & Saez, 2014</a>) naturally leads to increased differences in consumption (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0015" name="bbb0015" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Aguiar & Bils, 2015</a>), creating additional skewness in CLV distributions. In a general sense, customer prioritization increases disparity in the population and prods the drift toward a more polarized society wherein some customers will get better and possibly lower-priced products than others. For example, machine learning techniques that have been used on mortgage data of millions of borrows allow for more accurate pricing of default risk and thus for a greater supply of credit. However, the benefits in cheaper mortgages go disproportionately to the more affluent borrowers (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0170" name="bbb0170" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Fuster, Goldsmith-Pinkham, Ramadorai, & Walther, 2018</a>). Recent research has demonstrated that such techniques can even help to identify defaulting borrowers by the text they write when asking for the loan (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0385" name="bbb0385" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Netzer, Lemaire, & Herzenstein, 2019</a>).</p><p id="p0290" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Overall, differential treatment of less affluent consumers will raise difficult moral and political questions about impact of AI-CRM systems on an increasingly polarized society.</p></section><section id="s0070" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h4 class="u-margin-m-top u-margin-xs-bottom" id="st0085" style="box-sizing: border-box; font-size: 1rem; font-weight: 400; line-height: 1.4; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Role of Consumer Technology Skills</h4><p id="p0295" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">It has long been established that disadvantaged consumers may pay more than higher-income customers due to the former's limited scope of purchases and the ability to take advantage of market opportunities (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0195" name="bbb0195" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Goldman, 1976</a>). One might imagine that AI systems can help such consumers in this regard. They may use AI-based smart assistants that capture and analyze their preferences to help them face increasingly complex marketplaces. In that sense, some bottom-of-the-pyramid customers who are traditionally less able to take advantage of value-based market opportunities can use such assistants to get better value for a lower price.</p><p id="p0300" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">The question of skills and AI's effect may be task-dependent. For simpler tasks such as finding a product to purchase in a certain category, an AI-based device such as Alexa can help less-skilled individuals to navigate the marketplace with the help of technology. However, for more complicated tasks (such as finding the optimal product, overcoming marketers' attempts to draw the customer in a certain direction) the efficient use of AI may depend on skills that may start even with the knowledge of which software and technology to use (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0005" name="bbb0005" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Agrawal et al., 2018</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0570" name="bbb0570" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Wilson et al., 2017</a>). Taking advantage of increasingly sophisticated assistants will demand skills that are not necessarily available to large segments of the population. Given that, even consumer-side AI may increase disparity among customers.</p><p id="p0305" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Consider the case of Alexa and Echo smart speakers. Together they enable customers to order products seamlessly and at a rather affordable cost, providing the possible basis for a smarter household shopping environment. Yet, the market opportunity draws more higher-income users than others (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0310" name="bbb0310" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kinsella, 2018</a>). One of the reasons for this is that even this seemingly simple IoT environment demands some technical know-how (e.g., setting up a household profile) that may create obstacles for disadvantaged population segments.</p></section><section id="s0075" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h4 class="u-margin-m-top u-margin-xs-bottom" id="st0090" style="box-sizing: border-box; font-size: 1rem; font-weight: 400; line-height: 1.4; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Transition Period</h4><p id="p0310" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">While AI may eventually create a flawless service environment, the transition between classic CRM and AI-CRM will not be flawless. For example, while chatbots may be more cost-effective than human employees, the service experience that they provide can be subpar in the earlier stage, generating consumer frustration (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0285" name="bbb0285" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kannan, 2019</a>). As with other self-service systems, factors such as age, gender, and socio-economic status will likely affect users' technological savvy, and likewise their aptness, or resistance, to the new technology (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0095" name="bbb0095" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Blut et al., 2016</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0540" name="bbb0540" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Venkatesh et al., 2012</a>). Furthermore, it has been found that older and lower-income individuals may adopt innovations later and tend to perceive innovations as less useful (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0040" name="bbb0040" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Arts et al., 2011</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0335" name="bbb0335" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Laukkanen, 2016</a>). This will affect how fast the disadvantaged consumers will adopt and start using AI-driven tools. At this transition time, highly skilled individuals find it less challenging to use service systems partly driven by AI, whereas the technologically disadvantaged will find it hard to benefit therefrom.</p></section></section><section id="s0080" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h3 class="u-h4 u-margin-m-top u-margin-xs-bottom" id="st0095" style="box-sizing: border-box; color: #505050; font-size: 1rem !important; font-weight: 400 !important; line-height: 1.4 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Firm-Related Outcomes</h3><p id="p0315" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">As discussed above, AI-CRM is a highly resource-dependent activity for companies to engage in. Consistent with the resource-based view (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0060" name="bbb0060" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Barney, 1991</a>), this implies that firms with superior resources will gain a competitive advantage that can, in turn, lead to monopolies or oligopolies. Note that in the context of AI, necessary resources include, among others, big data, properly skilled staff, management agility, and superior computing power, as well as proprietary use of top-performing algorithms.</p><p id="p0320" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">There are some cases wherein smaller startups can use their agility and technical orientation to take advantage of the promises AI offers in the context of customer relationships. However, we believe that in most cases, larger firms have the potential to benefit more due to their access to resources. Among the essential resources that larger firms possess, two are notable. One is access to large databases that will enable the machine learning to train and increase effectiveness. The second is the access to trained professionals that will manage the process, which is especially important in light of the AI skills crisis (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0360" name="bbb0360" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Marr, 2018</a>), where the demand for AI professionals is much larger than the possible supply. Large companies have a much better ability to invest in recruitment, compensation, and organizing AI professionals in large enough departments that will enable the creation of effective knowledge centers in the organization.</p><p id="p0325" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">While most AI-CRM benefits derived by firms relate to an improved value proposition, AI-CRM also often reduces the cost of serving consumers, as the emerging technologies in many industries allow substitution of human labor with cheaper machines and automated decision making to optimize interactions with consumers at various points on their journeys. As aforementioned, the more data's scope and variety increases, the more the firm can learn individuals' needs and preferences. Such acquired knowledge can then be leveraged into offering better value propositions to these individuals not only in the product category where the data were collected but also in other product categories.</p><p id="p0330" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Consequently, as AI-CRM enables companies to derive more value (on average) from consumer acquisition by leveraging customer data across multiple product categories, we expect the competition among firms at the acquisition stage to intensify. Further, we expect to see more mergers and acquisitions that focus on the value of merging (or acquiring) consumer data, compared with other firm capabilities. Finally, the increased importance of fast, direct access to consumer data may generate a higher sustainable competitive advantage for direct-to-consumer brands competing with traditional retail brands.</p><p id="p0335" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Given the increasingly more granular nature of consumer data becoming available, such competition will be focused not on a consumer segment level, as it traditionally has been, but instead, firms will be competing for each consumer. Further, given the improved prediction of customer lifetime value, we should expect such competition to be uneven across consumers. For consumers with high expected lifetime value, the competition will intensify, resulting in such consumers deriving higher value (e.g., airlines tend to offer more value to current and potential customers who are expected to fly often). On the other hand, the competition will become less intense for consumers with lower expected lifetime value, resulting in a lower value for them. It is possible, however, that such increased discrimination in provided value may be mitigated in industries where delivering horizontal differentiation is easier, such as apparel.</p></section><section id="s0085" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h3 class="u-h4 u-margin-m-top u-margin-xs-bottom" id="st0100" style="box-sizing: border-box; color: #505050; font-size: 1rem !important; font-weight: 400 !important; line-height: 1.4 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 24px !important; padding: 0px;">Regulation</h3><p id="p0340" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Rise of market concentration usually associated with regulators intervening and breaking up existing structures. Yet recent examples, such as the US aviation market, have shown that this is not necessarily the case, at least for a certain transition period (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0505" name="bbb0505" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">The Economist, 2018</a>). For the case of AI, the problem is particularly pressing, as the traditional argument of protecting consumers against price gauging resulting from monopolies often cannot be invoked, as many companies in this sphere provide their services free of charge (e.g., Google, Facebook). For those services that are not free, the competitive advantage of superior resources may enable monopolists to offer higher value to customers due to a combination of providing superior value (e.g., due to network effects) at a lower cost (e.g., due to economies of scale, fewer marketing expenditures).</p><p id="p0345" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">As lower costs make applying anti-trust regulation quite challenging, firms may fully take advantage of their market power, which will raise concerns on the parts of regulators. The question, however, is whether, at that stage, regulation will even be possible. Moreover, in countries where companies are allowed to invest some of their profits in lobbying (e.g., such as the United States), imposing regulation may be associated with significant political risks.</p><p id="p0350" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">It is also possible that AI may create a system that self-regulates. The same AI systems that help firms provide superior product offers can help customers identify the companies most adapted to their needs. We may witness the rise of third-party providers enabling high-value customers, or customers with superior data profiles, to find the perfect companies with which to interact. This would function in much the same way as recommendation sites do today. The danger, however, is the selective discrimination we have discussed above – customers who are considered unprofitable or barely profitable will be abandoned by most firms (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0240" name="bbb0240" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Haenlein & Kaplan, 2009</a>). This, in turn, may lead to the rise of new competitors specializing in this type of client base (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0440" name="bbb0440" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Rosenblum et al., 2003</a>), as well as more intense competition among firms who abandoned them (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0495" name="bbb0495" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Subramanian, Raju, & Zhang, 2014</a>). Also, receiving consistently lower service may push such lower-value customers to falsify their online data and generate fake online profiles. Such information is inherently difficult to spot, as the recent discussion around fake news indicates.</p><p id="p0355" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">What all of this implies is that smart customers will leverage AI's power to become more strategic themselves (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0235" name="bbb0235" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Haenlein, 2017</a>, <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0340" name="bbb0340" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Lewis, 2005</a>). Customers will learn how to better negotiate with firms, use their personal data as a strategic advantage, and generally shift value capture away from firms. Automatic and AI-enabled solutions will emerge to support customers in those activities. As we discussed, AI will allow firms to better discriminate among customers and to avoid providing superior customer service or better products to customers who do not “deserve” this treatment. Yet the same AI may help some customers to identify the decision rules used by firms in providing such service and leverage those rules to their advantage. This counter-strategizing may widen the chasm between high-value and lower-value customers as differences between customers will stem not only from the increased ability of certain firms to discriminate but also from the increased ability of certain (most likely higher-value) customers to navigate firms' strategies to their advantage.</p><p id="p0360" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">In such a world, CRM would become a constant race between firms trying to predict customer behavior, alongside a segment of customers trying to anticipate or reverse-engineer firms' decision rules. At the same time, a large number of customers may become more and more frustrated by the nature of the firms' marketing mix decisions that drive increasing consumer disparity, therefore increasing pressure on regulators to take action to mitigate it. Governments already recognized some of the problems that big data and the ability to analyze it create in this regard (e.g., <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0565" name="bbb0565" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">White House, 2015</a>).</p><p id="p0365" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Ultimately, intervention by regulators may be needed to balance the resource-driven concentration of firms with the emergence of falsified data and strategic customer behavior. Such a need will become more pronounced as more companies start discriminating against relatively low-value customers. Examples of such interventions can range from regulating the use of automated solutions (e.g., in France, some self-service solutions are only allowed to operate during usual business hours, and not 24/7), to disproportionally taxing AI-enabled value creation (to compensate for the advantage such systems extend compared to hiring human personnel), to the dismantling of monopolies (e.g., as suggested by the #BreakUpBigTech movement).</p><p id="p0370" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">Yet regulating AI may not be that easy (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0465" name="bbb0465" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Scherer, 2016</a>). AI is difficult to regulate because of the definitional, ex-post, as well as ex-ante problem. First, we need a clear and legally binding definition of the object to be regulated. This does not yet exist in the case of AI. Second, there are several regulatory problems at the ex-ante stage (R&D of the targeted AI system) as well as the ex-post stage (whenever AI is put on the market) (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0465" name="bbb0465" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Scherer, 2016</a>).</p><p id="p0375" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">What amplifies complexity even further are the different systems of thoughts about regulation. While the US is relatively reluctant to regulate, Europe has been making more use of its regulatory powers lately (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0295" name="bbb0295" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Kaplan & Haenlein, 2020</a>). In China, the government and state-affiliated entities are leading AI development and application of AI-CRM systems in multiple domains, which creates another set of challenges and considerations. Cultural dimensions also must be considered: European legislation is less tolerant of asking customers to share data, while the US and especially China, have fewer restrictions thereon.</p><p id="p0380" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">This highly complex interplay may explain why some in the corporate world are advocating for more regulation. Companies such as Facebook are calling for government intervention (e.g., <a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0020" name="bbb0020" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Anderson, 2019</a>) and Microsoft's president Brad Smith recently called for “thoughtful government regulation” of technological advances in facial recognition. Elon Musk stated early on, “I'm increasingly inclined to think there should be some regulatory oversight, maybe at the national and international level” (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0185" name="bbb0185" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Gibbs, 2014</a>).</p></section></section><section id="s0090" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h2 class="u-h3 u-margin-l-top u-margin-xs-bottom" id="st0105" style="box-sizing: border-box; color: #505050; font-size: 1.2rem !important; font-weight: 400 !important; line-height: 1.333 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 32px !important; padding: 0px;">Conclusion</h2><p id="p0385" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">One could argue that much of AI's contribution to how firms will manage their customer relationships can be considered simple enhancements of technology-enabled processes that have been unfolding for some time. Indeed, an information-intensive world in which customers are managed individually, and their demand is well predicted, has been envisioned for decades (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0085" name="bbb0085" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Blattberg et al., 1994</a>). However, until AI methods began emerging, the pace of progress was moderate, and much of this futuristic vision has not yet materialized. As this future vision is rapidly becoming our new reality, we argue that marketers should not only focus on how new methods of customer interactions are conducted but also their overall consequences for the fundamental ways that firms build “relationships” with customers.</p><p id="p0390" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;">The implications thereof are not trivial: We are moving toward an economic system wherein customer prioritization may dominate much of customer relationships, and where only a minority of customers is capable of taking advantage of the new technologies. While in some cases marketers will find that customer discrimination is not always optimal from an economic standpoint (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0525" name="bbb0525" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">Ukanwa & Rust, 2018</a>), this will not necessarily represent the majority of cases. We expect that there will be groups of individuals that may be affected by this prioritization wherever they consume. Hence, AI-CRM systems may become a concern and a consideration of both regulators and human rights groups (<a class="workspace-trigger" href="https://www.sciencedirect.com/science/article/pii/S1094996820300839#bb0580" name="bbb0580" style="box-sizing: border-box; color: #0c7dbb; margin: 0px; padding: 0px; text-decoration-line: none; word-break: break-word;">World Economic Forum, 2018</a>). Marketing academics' experience and knowledge of this matter give them a particular responsibility to be an active voice that follows AI-CRM systems' development, identifies the concerns, and makes recommendations on how to address the new environment of customer relationships that we all face.</p></section></div><section id="s0095" style="box-sizing: border-box; margin: 0px 0px 8px; padding: 0px;"><h2 class="u-h3 u-margin-l-top u-margin-xs-bottom" id="st0110" style="box-sizing: border-box; color: #505050; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 1.2rem !important; font-weight: 400 !important; line-height: 1.333 !important; margin-bottom: 8px !important; margin-left: 0px; margin-right: 0px; margin-top: 32px !important; padding: 0px;">Acknowledgement</h2><p id="p0395" style="box-sizing: border-box; color: #2e2e2e; font-family: NexusSerif, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif; font-size: 18px; margin: 0px 0px 16px; padding: 0px;">This paper evolved from discussions at the “Big Data, Data-Driven CRM and Artificial Intelligence” held in 2019 in Lisbon. The authors thank the conference organizers, Manfred Krafft, Michael Haenlein, and Laszlo Sajtos, and various conference participants, for support and advice.</p><p id="p0395" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;"><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, Times New Roman, Times, STIXGeneral, Cambria Math, Lucida Sans Unicode, Microsoft Sans Serif, Segoe UI Symbol, Arial Unicode MS, serif;"><span style="font-size: 18px;">Source:</span></span><br /><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, Times New Roman, Times, STIXGeneral, Cambria Math, Lucida Sans Unicode, Microsoft Sans Serif, Segoe UI Symbol, Arial Unicode MS, serif;"><span style="font-size: 18px;"><a href="https://www.sciencedirect.com/science/article/pii/S1094996820300839" target="_blank">https://www.sciencedirect.com/science/article/pii/S1094996820300839</a></span></span></p><p id="p0395" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;"><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, Times New Roman, Times, STIXGeneral, Cambria Math, Lucida Sans Unicode, Microsoft Sans Serif, Segoe UI Symbol, Arial Unicode MS, serif;">PDF download:</span></p><p id="p0395" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;"><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, Times New Roman, Times, STIXGeneral, Cambria Math, Lucida Sans Unicode, Microsoft Sans Serif, Segoe UI Symbol, Arial Unicode MS, serif;"><a href="https://drive.google.com/file/d/1M53rHLFaUbu7N_Mqf_0J4HfG45Jsvh7p/view?usp=sharing">https://drive.google.com/file/d/1M53rHLFaUbu7N_Mqf_0J4HfG45Jsvh7p/view?usp=sharing</a></span></p><p id="p0395" style="box-sizing: border-box; margin: 0px 0px 16px; padding: 0px;"><span style="color: #2e2e2e; font-family: NexusSerif, Georgia, Times New Roman, Times, STIXGeneral, Cambria Math, Lucida Sans Unicode, Microsoft Sans Serif, Segoe UI Symbol, Arial Unicode MS, serif;"><br /></span></p></section>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-33014529747500936202020-12-23T14:16:00.003+07:002020-12-24T15:45:38.747+07:00Big Data và ứng dụng trong hoạt động tài chính, ngân hàng<p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEidzhw2YQtcoJZWtOhyphenhyphentwiiGZk7Dldjo2Ruuxk3WEfQImACQUuHGc8QjaKDGoHwcQv3GooFJaWIbqFycCrUs0dCRtMnvCujFEmBjkW6evnBAGBzvyfnPVUQOTrJltM8yyplnwNZnKYC9Qo/s1199/big-data-analytics-banking-industry-video.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="789" data-original-width="1199" height="422" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEidzhw2YQtcoJZWtOhyphenhyphentwiiGZk7Dldjo2Ruuxk3WEfQImACQUuHGc8QjaKDGoHwcQv3GooFJaWIbqFycCrUs0dCRtMnvCujFEmBjkW6evnBAGBzvyfnPVUQOTrJltM8yyplnwNZnKYC9Qo/s1199/big-data-analytics-banking-industry-video.png" width="640" /></a></div><br /><span face="Roboto-Bold" style="color: #333333; font-size: 14px;"><br /></span><p></p><p><span face="Roboto-Bold" style="color: #333333; font-size: 14px;">Trong thời đại ngày nay, để phát triển một doanh nghiệp, ngoài vốn và nhân lực thì “dữ liệu” (data) được coi là nguồn lực không thể thiếu được. Ai cũng đã từng ngạc nhiên nhận thấy khi mua sắm online trên các trang thương mại điện tử như eBay, Amazon, Sendo hay Tiki, trang này cũng sẽ gợi ý một loạt các sản phẩm có liên quan và phù hợp với nhu cầu của bạn. Ví dụ khi xem điện thoại, trang mua sắm trực tuyến sẽ gợi ý cho bạn mua thêm ốp lưng, pin dự phòng; hoặc khi mua áo thun thì sẽ có thêm gợi ý quần jean, dây nịt...</span></p><div style="color: #333333; font-family: Roboto; font-size: 14px; text-align: justify;"><strong>Lời mở đầu</strong><br /> </div><div style="color: #333333; font-family: Roboto; font-size: 14px; text-align: justify;">Bí ẩn đằng sau các trang web thông minh này là mọi sự chào mời sản phẩm đều dựa trên các nghiên cứu về sở thích, thói quen của khách hàng cũng như phân loại được các nhóm khách hàng khác nhau... Vậy những thông tin để phân tích này có được từ đâu và nó có tác động thế nào đến việc sản xuất kinh doanh của doanh nghiệp? Thứ nhất, dữ liệu khổng lồ về khách hàng có thể có từ các thông tin mà các doanh nghiệp thu thập trong lúc khách hàng ghé thăm, tương tác hay mua sắm trên website của mình; dữ liệu này cũng có thể được mua lại từ các công ty chuyên cung cấp dữ liệu khách hàng. Các thông tin này không chỉ giúp nhà cung ứng hàng hóa, dịch vụ tăng lợi nhuận cho chính họ mà còn tăng trải nghiệm mua sắm của người dùng. Một mặt, nhờ quá trình tìm hiểu, phân tích khách hàng, doanh nghiệp có thể tạo ra các sản phẩm đáp ứng nhu cầu của khách hàng, cũng như xây dựng chính sách phân phối và bán sản phẩm đến tay người tiêu dùng một cách có hiệu quả nhất. Mặt khác, bản thân người tiêu dùng có thể tiết kiệm thời gian và yên tâm trong trải nghiệm mua sắm của mình. Hơn thế nữa, ở tầm ngành và vĩ mô, ứng dụng dữ liệu lớn (big data) có thể giúp các tổ chức và chính phủ dự đoán được tỉ lệ thất nghiệp, xu hướng nghề nghiệp của tương lai để đầu tư cho những hạng mục đó, hoặc cắt giảm chi tiêu, kích thích tăng trưởng kinh tế,... thậm chí là ra phương án phòng ngừa trước một dịch bệnh nào đó.</div><div style="color: #333333; font-family: Roboto; font-size: 14px; text-align: justify;"><br /></div><div style="text-align: justify;"><div style="color: #333333; font-family: Roboto; font-size: 14px;">Là một tổ chức cung ứng dịch vụ tài chính cho hầu hết các chủ thể trong nền kinh tế, ngành Ngân hàng không thể đứng ngoài xu thế ứng dụng dữ liệu lớn giống như các doanh nghiệp bán lẻ khác. Đặc thù của hoạt động ngân hàng (cơ sở khách hàng rộng lớn, bao quát mọi mặt tài chính của nền kinh tế) cho phép mỗi ngân hàng xây dựng một cơ sở dữ liệu khổng lồ, từ dữ liệu có cấu trúc (như lịch sử giao dịch, hồ sơ khách hàng) tới những dữ liệu phi cấu trúc (như hoạt động của khách hàng trên website, ứng dụng mobile banking hay trên mạng xã hội). Ứng dụng Big Data nếu được khai thác hiệu quả sẽ đem lại những lợi thế cạnh tranh và hiệu quả to lớn trong lĩnh vực ngân hàng đặc biệt trong bối cảnh thị trường dịch vụ tài chính đang bão hòa. Bài viết này nhằm hệ thống những vấn đề cơ bản về Big Data, trên cơ sở đó phân tích những ứng dụng của Big Data và các điều kiện nhằm ứng dụng Big Data ở lĩnh vực ngân hàng trong bối cảnh cách mạng công nghệ 4.0. </div><div style="color: #333333; font-family: Roboto; font-size: 14px;"> </div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><strong>1. Tổng quan về Big Data</strong><br /> </div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><em><strong>Khái niệm Big Data</strong></em><br /> </div><div style="color: #333333; font-family: Roboto; font-size: 14px;">Big Data là thuật ngữ dùng để chỉ một tập hợp dữ liệu rất lớn và rất phức tạp đến nỗi những công cụ, ứng dụng xử lí dữ liệu truyền thống không thể nào đảm đương được (theo Kevin Taylor-Sakyi, 2016; Mashooque A. Memon và cộng sự, 2017). Bằng việc tổng hợp một lượng thông tin lớn từ các nguồn khác nhau khiến cho Big Data trở thành một công cụ rất mạnh cho việc ra các quyết định kinh doanh, nhận diện hành vi và xu hướng nhanh hơn và tốt hơn rất nhiều so với cách thức truyền thống. Big Data được nhận diện trên ba khía cạnh chính: Dữ liệu (Data), Công nghệ (Technology), Quy mô (Size). Thứ nhất, dữ liệu (data) bao gồm các dữ liệu thuộc nhiều định dạng khác nhau như hình ảnh, video, âm nhạc… trên Internet; gồm các dữ liệu thu thập từ các hệ thống cảm biến có kết nối với hệ thống máy chủ; dữ liệu của khách hàng ở các ứng dụng thông minh và các thiết bị có kết nối mạng; dữ liệu của người dùng để lại trên các platform của mạng xã hội. Vì các dữ liệu được cập nhật qua các thiết bị kết nối mạng từng giờ, từng phút, từng giây và đến từ nhiều nguồn khác nhau nên khối lượng dữ liệu này là rất lớn (Big). Hiện nay, Big Data được đo lường theo đơn vị Terabytes (TB), Petabytes (PB) và Exabytes (EB). </div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><br /></div><div style="color: #333333; font-family: Roboto; font-size: 14px;">Có thể dễ dàng lấy một vài ví dụ như Walmart xử lý hơn 1 triệu giao dịch của khách hàng mỗi giờ, dữ liệu nhập vào ước tính hơn 2,5 PB; Twitter tạo ra 12 TB dữ liệu mỗi ngày hay Airbus A380 tạo ra 10 TB dữ liệu mỗi 30 phút bay. Yếu tố nhận diện thứ hai của Big Data là công nghệ (technology). Công nghệ thường được thiết kế và hình thành một hệ sinh thái từ dưới đi lên để có khả năng xử lý các dữ liệu lớn và phức tạp. Một trong những hệ sinh thái mạnh nhất hiện nay phải kể đến Hadoop với khả năng xử lý dữ liệu có thể được tăng lên cùng mức độ phức tạp của dữ liệu, năng lực này là một công cụ vô giá trong bất kỳ ứng dụng Big Data nào. Yếu tố nhận diện thứ ba của Big Data là quy mô dữ liệu. Hiện nay vẫn chưa có câu trả lời chính xác cho câu hỏi dữ liệu thế nào gọi là lớn. Theo ngầm hiểu thì khi dữ liệu vượt quá khả năng xử lý của các hệ thống truyền thống thì sẽ được xếp vào Big Data.<br /> </div><div style="color: #333333; font-family: Roboto; font-size: 14px;">Việc bản thân các doanh nghiệp cũng đang sở hữu Big Data của riêng mình đã trở nên phổ biến. Chẳng hạn, như trang bán hàng trực tuyến eBay thì sử dụng hai trung tâm dữ liệu với dung lượng lên đến 40 petabyte để chứa những truy vấn, tìm kiếm, đề xuất cho khách hàng cũng như thông tin về hàng hóa của mình. Hay nhà bán lẻ online Amazon.com thì phải xử lí hàng triệu hoạt động mỗi ngày cũng như những yêu cầu từ khoảng nửa triệu đối tác bán hàng. Tương tự, Facebook cũng phải quản lí 50 tỉ bức ảnh từ người dùng tải lên, YouTube hay Google thì phải lưu lại hết các lượt truy vấn và video của người dùng cùng nhiều loại thông tin khác có liên quan. Theo kết quả khảo sát được thực hiện bởi Qubole - công ty hàng đầu về cung cấp giải pháp, nền tảng quản lí dữ liệu hạ tầng đám mây phục vụ phân tích - và bởi Dimensional Research - một tổ chức nghiên cứu thị trường công nghệ, lĩnh vực chăm sóc khách hàng, kế hoạch công nghệ thông tin, quy trình bán hàng và hoạt động tài chính là các lĩnh vực thu lợi nhiều nhất từ Big Data. Qua đó, thấy được là mục đích khai thác Big Data của các nhà cung ứng hàng hóa, dịch vụ toàn cầu là hướng đến chăm sóc khách hàng, phân tích dữ liệu khách hàng để phát triển sản phẩm, dịch vụ; ứng dụng thông minh để tăng trải nghiệm của khách hàng và giữ chân khách hàng khi sự cạnh tranh ngày càng gay gắt giữa các nhà cung ứng ở hầu hết các lĩnh vực kinh doanh. Với các công cụ phân tích, đặc biệt là công cụ phân tích dự báo (Predictive Analytics) và khai thác dữ liệu (Data mining), Big Data giúp các doanh nghiệp đo lường, phân tích các vấn đề liên quan đến sản phẩm, phát hiện các cơ hội và nguy cơ rủi ro, đồng thời, dự báo doanh thu từ hoạt động kinh doanh hàng ngày.<br /> </div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><em><strong>Các đặc điểm của Big Data</strong></em><br /> </div><div style="color: #333333; font-family: Roboto; font-size: 14px;">Doug Laney (trích trong nghiên cứu của Meta Group năm 2011 với tiêu đề <em>“3D data management: Controlling data volume, variety and velocity”</em>), đã đưa ra định nghĩa 3Vs nói về ba đặc điểm chính của Big Data bao gồm Dung lượng (volume), Tốc độ (velocity), Tính đa dạng (variety). Dung lượng của Big Data đang tăng lên mạnh mẽ từng ngày. Theo tài liệu của Intel vào tháng 9/2013, cứ mỗi 11 giây, 1 petabyte dữ liệu được tạo ra trên toàn thế giới, tương đương với một đoạn video HD dài 13 năm. Về Tốc độ (Velocity) phản ánh tốc độ mà tại đó dữ liệu được phân tích bởi các công ty để cung cấp một trải nghiệm người dùng tốt hơn. Với sự ra đời của các kỹ thuật, công cụ, ứng dụng lưu trữ, nguồn dữ liệu liên tục được bổ sung với tốc độ nhanh chóng. Tổ chức McKinsey Global ước tính lượng dữ liệu đang tăng trưởng với tốc độ 40%/năm, và sẽ tăng 44 lần từ năm 2009 đến 2020. Về Tính đa dạng (Variety) của dữ liệu cho thấy, dữ liệu của Big Data được thu thập từ nhiều nguồn, có thể khái quát thành ba nguồn cơ bản sau đây. (Sơ đồ 1)</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwx3G82b9XpuX75BtXKi9t3K1dhkZz2xS2VvMT8E3gv0itgVUnz_4UcOlE4aweZEsIcRAYUgd6OW2q1u0mktly7i9qyXi5TIiCEOHSy8vK1hLl5UxH62xR31gLsHcAaO-j4T1KODL_WKI/s477/bank+-+so+do+1.jpeg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="323" data-original-width="477" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwx3G82b9XpuX75BtXKi9t3K1dhkZz2xS2VvMT8E3gv0itgVUnz_4UcOlE4aweZEsIcRAYUgd6OW2q1u0mktly7i9qyXi5TIiCEOHSy8vK1hLl5UxH62xR31gLsHcAaO-j4T1KODL_WKI/s16000/bank+-+so+do+1.jpeg" /></a></div><br /><div style="color: #333333; font-family: Roboto; font-size: 14px;"><br /></div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><br /></div><div style="color: #333333; font-family: Roboto; font-size: 14px;">Về sau này, đặc điểm Tính thay đổi (variability) và Tính phức tạp (complexity) được bổ sung vào bởi SAS - một công ty đi đầu trong lĩnh vực phân tích dữ liệu và tư vấn của Mỹ. Tính thay đổi phản ánh sự thay đổi hàng ngày của dữ liệu. Tính phức tạp thể hiện trong quá trình lưu giữ, quản lý, xử lý và truyền tải dữ liệu do dữ liệu đến từ nhiều định dạng khác nhau. Theo Oracle, hai đặc điểm Giá trị (value) và Tính xác thực (veracity) cần được coi là đặc điểm cơ bản của Big Data. Giá trị thể hiện ở những ứng dụng đa dạng của Big Data nếu được thu thập, phân tích và xử lý đúng cách. Sau cùng, vì Big Data được thu thập từ nhiều nguồn khác nhau nên tính xác thực của các dữ liệu cũng cần được đặc biệt cân nhắc. (Sơ đồ 2)</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgFgKmrVkgMPrUxuXUUQr1H3CbUMQQ6UgVfUgpcB_DHSGudKnoDV65zMSVu3BXE8rhTk60GoHQss9K6K_DbSXrIazPP6O7mPSlTbbddCF4SJWO8rNXmqxsz20ehuiPdAmRYMVFXoXVXBBU/s480/bank+-+so+do+2.jpeg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="336" data-original-width="480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgFgKmrVkgMPrUxuXUUQr1H3CbUMQQ6UgVfUgpcB_DHSGudKnoDV65zMSVu3BXE8rhTk60GoHQss9K6K_DbSXrIazPP6O7mPSlTbbddCF4SJWO8rNXmqxsz20ehuiPdAmRYMVFXoXVXBBU/s16000/bank+-+so+do+2.jpeg" /></a></div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><br /> <table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://edgemarkets.s3-ap-southeast-1.amazonaws.com/pictures/chart-lenddoefl_pw7-tem1204_theedgemarkets.jpg" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="714" data-original-width="800" height="571" src="https://edgemarkets.s3-ap-southeast-1.amazonaws.com/pictures/chart-lenddoefl_pw7-tem1204_theedgemarkets.jpg" width="640" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><b><i>Quy trình chấm điểm tín dụng tài chính với công nghệ Big Data</i></b></td></tr></tbody></table><div class="separator" style="clear: both; text-align: center;"><br /></div></div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><div><strong>2. Các ứng dụng của Big Data trong hoạt động ngân hàng</strong><br /> </div><div>Hiện nay, hầu hết các tổ chức chức ngân hàng, dịch vụ tài chính và bảo hiểm đang nỗ lực để áp dụng một cách tiếp cận mới theo hướng khai thác dữ liệu để phát triển và đổi mới sản phẩm. Mặc dù, các tổ chức đang thay đổi cách thức khai thác dữ liệu bằng cách thu thập một khối lượng dữ liệu khổng lồ và tiến hành phân tích, thực hiện bước đầu tiên trong quy trình khai thác Big Data. Khi khối lượng khách hàng tăng lên, nó ảnh hưởng đáng kể đến mức độ, khả năng cung cấp dịch vụ của từng tổ chức. Thực tiễn cho thấy việc phân tích dữ liệu hiện tại đã đơn giản hóa quá trình theo dõi và đánh giá khách hàng tín dụng của các ngân hàng và các tổ chức tài chính, dựa trên khối lượng lớn dữ liệu như thông tin, hồ sơ cá nhân và các thông tin bảo mật khác. Với sự giúp đỡ của Big Data, các ngân hàng có thể theo dõi hành vi của khách hàng, xác định các nguồn dữ liệu cần thiết để thu thập phục vụ cho việc đưa ra giải pháp. <br /> </div><div>Các ứng dụng của Big Data trong lĩnh vực ngân hàng bao gồm:<br /> </div><div><em>Thứ nhất, phân tích các thói quen chi tiêu của khách hàng</em><br /> </div><div>Các ngân hàng có khả năng truy cập trực tiếp nguồn thông tin, dữ liệu lịch sử dồi dào liên quan đến các thói quen, hành vi chi tiêu của khách hàng. Các ngân hàng còn nắm thông tin chi tiết về nguồn thu của khách hàng trong một năm, khoản chi tiêu, các dịch vụ ngân hàng mà khách hàng sử dụng… Điều này cung cấp cơ sở, cơ hội để các ngân hàng tiếp cận và phân tích dữ liệu sâu hơn. Áp dụng các chức năng sàng lọc thông tin, ví dụ như, khi lọc ra thời điểm dịp lễ hay mùa lễ và điều kiện vĩ mô (lạm phát, tỷ lệ thất nghiệp…) mà nhân viên ngân hàng có thể hiểu được nguyên nhân của biến động trong thu nhập hay chi tiêu của ngân hàng. Đây là một trong các yếu tố quan trọng trong quá trình đánh giá rủi ro, thẩm định hồ sơ cho vay, mở rộng dịch vụ cung cấp hay bán chéo sản phẩm đến khách hàng. Bên cạnh đó, nhờ nắm được thông tin về nguồn tiền nhàn rỗi của khách hàng, ngân hàng có thể tận dụng thu hút tiền gửi để thực hiện các hoạt động đầu tư.<br /> </div><div><em>Thứ hai, phân khúc khách hàng và thẩm định hồ sơ.</em><br /> </div><div>Phân khúc khách hàng là một trong những nhân tố quan trọng trong chiến lược marketing và thiết kế sản phẩm của ngân hàng. Một khi các phân tích ban đầu về thói quen chi tiêu của khách hàng cùng với xác định các loại hình dịch vụ, kênh giao dịch được khách hàng ưu tiên (ví dụ khách hàng muốn gửi tiết kiệm hay muốn đầu tư các khoản vay) được hoàn tất thì các ngân hàng sẽ có được một cơ sở dữ liệu phục vụ cho quá trình phân khúc, phân loại khách hàng một cách phù hợp dựa vào thông tin và hồ sơ khách hàng cung cấp. Big Data sẽ cung cấp cho các ngân hàng những hiểu biết, kiến thức chuyên môn sâu về nhu cầu tiềm ẩn bên trong, thói quen và xu hướng chi tiêu của khách hàng, trợ giúp cho nhiệm vụ xác định nhu cầu và mong muốn của họ. Bằng cách nắm các thông tin liên quan đến giao dịch, ngân hàng có thể xác định được khách hàng của mình thuộc các nhóm nào, ví dụ nhóm có chi tiêu dễ dàng, nhóm nhà đầu tư thận trọng, nhóm thanh toán nợ nhanh chóng, nhóm khách hàng trung thành… Bên cạnh đó, biết được hồ sơ cá nhân của tất cả các khách hàng giúp ngân hàng đánh giá chi tiêu và thu nhập dự kiến trong tháng tới và lập kế hoạch chi tiết để đảm bảo lợi nhuận cho chính tổ chức và lợi ích cho chính khách hàng. <br /> </div><div><em>Thứ ba, bán chéo thêm các dịch vụ khác</em><br /> </div><div>Dựa vào cơ sở dữ liệu ngân hàng có được, ngân hàng có thể thu hút thêm, hay giữ chân khách hàng bằng cách giới thiệu thêm các dịch vụ khác. Ví dụ, ngân hàng có thể giới thiệu các khoản đầu tư có lãi suất hấp dẫn đến các khách hàng có lượng tiền nhàn rỗi hoặc những nhà đầu tư thận trọng. Ngân hàng cũng có thể đề xuất các khoản vay ngắn hạn cho các khách hàng có thói quen chi tiêu dễ dàng để đáp ứng nhu cầu hàng ngày hoặc những khoản vay đáp ứng nhu cầu thanh khoản ngắn hạn của doanh nghiệp. Phân tích một cách chính xác về hồ sơ cá nhân của khách hàng, ngân hàng có thể bán kèm các dịch vụ khác với các ưu đãi được tập trung chính xác vào nhu cầu khách.<br /> </div><div><em>Thứ tư, nâng cao chất lượng dịch vụ thông qua xây dựng hệ thống thu thập các phản hồi khách hàng và phân tích chúng</em><br /> </div><div>Khách hàng có thể để lại phản hồi sau mỗi lần giao dịch hay mỗi lần nhận được tư vấn từ trung tâm hỗ trợ chăm sóc khách hàng hoặc qua các biểu mẫu phản hồi; nhưng thường xuyên (hay có thể nói nhiều khả năng) chia sẻ ý kiến thông qua các phương tiện truyền thông xã hội hơn, ví dụ Facebook, Zalo,…Các công cụ Big Data có thể tìm kiếm chọn lọc thông qua các thông tin, feedback công khai trên các phương tiện truyền thông và thu thập tất cả những dữ liệu đề cập về thương hiệu của ngân hàng để có thể phản hồi nhanh chóng và đầy đủ đến khách hàng, ngoài ra, cũng hỗ trợ ngăn chặn các tin đồn thất thiệt ảnh hưởng đến hoạt động kinh doanh và niềm tin nơi khách hàng. Khi khách hàng cảm thấy ngân hàng lắng nghe, đánh giá cao ý kiến và thực hiện những cải tiến, thay đổi theo yêu cầu của họ thì sự trung thành dành cho thương hiệu sẽ gia tăng, hơn nữa cải thiện hình ảnh của ngân hàng.<br /> </div><div><em>Thứ năm, marketing theo hướng cá nhân hóa.</em><br /> </div><div>Sau khi có được phân khúc khách hàng thì các ngân hàng cần tận dụng để marketing nhắm tới mục tiêu khách hàng dựa trên trên những hiểu biết về thói quen chi tiêu cá nhân của họ. Ngoài việc thu thập dữ liệu về lịch sử giao dịch của khách hàng, ngân hàng có thể kết hợp dữ liệu phi cấu trúc được lấy ra từ mạng xã hội để có được một bức tranh đầy đủ hơn về nhu cầu của khách hàng dựa trên các phân tích về tâm lý, mong muốn khách hàng ở mọi thời điểm. Từ đó, ngân hàng có thể đưa ra các giải pháp, kế hoạch marketing phù hợp để có được tỷ lệ phản hồi cao hơn từ khách hàng. Ví dụ, các ngân hàng sử dụng công cụ email marketing để gửi đến khách hàng các thông tin mới nhất về những dịch vụ cho vay ngắn hạn với lãi suất vừa phải hay gửi tiết kiệm với lãi suất hấp dẫn, hoặc các chương trình ưu đãi khác,…<br /> </div><div><em>Thứ sáu, thay đổi cách thức cung cấp dịch vụ đến khách hàng</em><br /> </div><div>Hệ thống Big Data có thể là một hệ thống phức tạp liên kết giữa nhiều bộ phận chức năng khác nhau với vai trò đơn giản hóa các nhiệm vụ trong một tổ chức. Bất cứ khi nào tên một khách hàng hoặc số tài khoản được nhập vào hệ thống, hệ thống Big Data sẽ hỗ trợ sàng lọc tất cả các dữ liệu và chỉ truyền đi hay cung cấp các dữ liệu được yêu cầu để phục vụ cho quá trình phân tích. Điều này cho phép các ngân hàng tối ưu hóa quy trình làm việc và tiết kiệm cả thời gian và chi phí. Big Data cũng cho phép các tổ chức xác định và khắc phục các vấn đề trước khi khách hàng bị ảnh hưởng.<br /> </div><div><em>Thứ bảy, phát hiện và ngăn chặn hành vi lừa đảo, vi phạm pháp luật</em><br /> </div><div>Big Data sẽ cho phép các ngân hàng đảm bảo không có giao dịch trái phép nào được thực hiện, cung cấp mức độ an toàn, nâng cao tiêu chuẩn bảo mật của toàn bộ ngành. Nhờ vào dữ liệu về lịch sử giao dịch và hồ sơ tín dụng của khách hàng, ngân hàng có thể nhận diện những bất thường trong quá trình cung cấp dịch vụ đến khách hàng. Ví dụ, khoản rút tiền lớn bất thường từ thẻ ATM có thể do thẻ bị mất cắp, từ đó, ngân hàng có những biện pháp an ninh để xác minh giao dịch. Ngân hàng khai thác Big Data để phân biệt giữa các giao dịch là hành vi phạm tội với các giao dịch hợp pháp bằng các thuật toán phân tích dữ liệu và machine learing (học máy). Các hệ thống phân tích sẽ tự động phát hiện, trích xuất các giao dịch bất hợp pháp ở thời gian thực và đề xuất các hành động ngay lập tức.<br /> </div><div><em>Thứ tám, kiểm soát rủi ro, tuân thủ luật pháp và minh bạch trong báo cáo tài chính</em><br /> </div><div>Các thuật toán của Big Data còn giúp giải quyết các vấn đề về tuân thủ quy định pháp luật về kế toán, kiểm toán và báo cáo tài chính, từ đó giảm được các chi phí quản lý. Bên cạnh đó, hệ thống Big Data thu thập và lưu trữ dữ liệu lớn giúp ngân hàng tiến hành phân tích một cách nhanh nhất khi có các dấu hiệu về rủi ro xảy ra, từ đó đưa ra các biện pháp xử lý. Big Data cũng đóng một vai trò quan trọng trong việc phối hợp giữa các bộ phận, phòng, ban và yêu cầu xử lý dữ liệu của ngân hàng vào một hệ thống trung tâm duy nhất; qua đó, hỗ trợ kiểm soát, ngăn chặn vấn đề mất dữ liệu, giảm thiểu rủi ro và gian lận.<br /> </div><div><em>Thứ chín, tham gia vào việc kiểm soát đánh giá và nâng cao hiệu quả làm việc của nhân viên</em><br /> </div><div>Hệ thống Big Data hỗ trợ thu thập phân tích, đánh giá và truyền tải dữ liệu về hiệu quả làm việc của nhân viên. Trước đây, để thu thập các thông tin này cần rất nhiều công đoạn mang tính thủ công, thì nay, Big Data sẽ giúp xử lý các công việc này một cách nhanh chóng và chính xác. Kết quả phân tích sẽ giúp các nhà lãnh đạo có cái nhìn về tình hình, thực trạng làm việc hiện tại của nhân viên, đặc biệt xem xét mức độ hài lòng của ngân viên về môi trường làm việc, phúc lợi… của ngân hàng dành cho họ.</div><div> </div><div><strong>3. Các điều kiện để ứng dụng Big Data trong hoạt động ngân hàng</strong><br /> </div><div><em>Thứ nhất, cần thay đổi tư duy trong đội ngũ quản lí ngân hàng về tầm quan trọng của dữ liệu và các phương pháp xử lý dữ liệu hiện đại</em><br /> </div><div>Trong các cuộc phỏng vấn quản lý một số ngân hàng, có một quan điểm vẫn còn tồn tại là quyết định có thể đưa ra dựa trên kinh nghiệm mà không cần dựa vào các kết quả phân tích dữ liệu lớn. Quan điểm trên không sai trong quá khứ. Thực tế cho thấy, những nhà quản lý có thâm niên trong lĩnh vực tài chính, ngân hàng đã từng đưa ra được nhiều quyết định chính xác. Tuy nhiên, đó là khi thị trường ngân hàng với các dịch vụ còn đơn giản, khi nhu cầu của khách hàng chưa nhiều và đặc biệt là khi khách hàng chưa tiếp cận được với các công nghệ thông minh và hiện đại. Ngày nay, khi mà các công ty công nghệ, các công ty viễn thông, các nhà bán lẻ không ngừng thay đổi, đầu tư và áp dụng công nghệ mới để đáp ứng nhu cầu ngày càng cao của khách hàng thì một làn sóng không nhỏ khách hàng truyền thống của ngân hàng đã và đang chuyển dần sang sử dụng dịch vụ được cung ứng từ các đối thủ của ngân hàng. Nổi bật là các dịch vụ thanh toán với tốc độ xử lý giao dịch nhanh, an toàn, tiện lợi và đặc biệt là chi phí thấp với những cái tên tiêu biểu như Momo, ViettelPay… rồi ngày nay là các dịch vụ tín dụng P2P. <br /> </div><div>Trên thế giới, các nhà quản lý ngân hàng đã sớm nhận ra mình không phải là người duy nhất để khách hàng có thể cho vay, nhận tiền gửi và cung cấp dịch vụ thanh toán. Các bên cho vay khác xuất hiện như công ty tài chính, cửa hàng cầm đồ hay các bên trung gian kết nối người cho vay với người vay tiền. Khách hàng cũng có thể đầu tư trái phiếu, chứng chỉ quỹ thay cho gửi tiết kiệm. Dịch vụ thanh toán cũng được cung cấp bởi nhiều công ty trung gian sử dụng công nghệ hiện đại. Khi khách hàng có nhiều sự lựa chọn, nhu cầu của họ cũng tăng lên. Điều này khiến cho ngân hàng buộc phải thay đổi mình. Chẳng hạn, trước kia quá trình thẩm định khách hàng được thực hiện một cách thủ công, qua nhiều bước và tốn kém thời gian. Các hồ sơ vay vốn hoặc khoản thanh toán từ khi đệ trình tới khi được phê duyệt có thể phải trải qua nhiều cuộc họp kéo dài trong nhiều ngày. Tuy nhiên, với sự hỗ trợ của công nghệ lưu trữ và phân tích dữ liệu, ngân hàng có thể nhanh chóng so sánh, đánh giá tín dụng đối với khách hàng. Việc áp dụng công nghệ Big Data giúp một số ngân hàng giảm thời gian thẩm định khách hàng từ nhiều ngày xuống chỉ còn vài phút. Mạng lưới dữ liệu liên kết và công nghệ nhận diện danh tích khách hàng thông qua các trang mạng xã hội thậm chí còn có thể giúp ngân hàng xác định được khách hàng đang ở đâu, làm gì và có các mối quan hệ nào. Điều này giúp quá trình quản lý sau giải ngân trở nên hiệu quả hơn. Các ngân hàng cũng áp dụng công nghệ phân tích dữ liệu lớn để lựa chọn vị trí thuận lợi nhất khi mở chi nhánh mới.<br /> </div><div><em>Thứ hai, ngân hàng phải xây dựng được quy trình liên quan đến dữ liệu từ khâu thu thập dữ liệu đến sử dụng kết quả xử lý dữ liệu</em><br /> </div><div>Ngân hàng thu thập thông tin từ rất nhiều nguồn khác nhau về một hệ thống giám sát xử lý tập trung, nhưng việc duy trì chất lượng dữ liệu về tính chính xác, kịp thời và các yếu tố khác ngày càng trở nên khó khăn. Để giải quyết vấn đền này thì ngân hàng cần thiết lập một quy trình thu thập (collect), rà soát (screening), làm sạch (clean), tổng hợp (reconcile) và phân loại dữ liệu vào một đầu mối tập trung; sau đó lại phân phối dữ liệu đến những bộ phân liên quan để phân tích và đưa ra các thông tin hữu ích. Trong đó, bước rà soát và làm sạch dữ liệu là rất quan trọng để nâng cao chất lượng dữ liệu. Ví dụ như, dữ liệu về tài khoản khách hàng và giao dịch, thường được sử dụng bởi các bộ phận quản lý gian lận, được thu thập từ nhiều nguồn khác nhau ở dưới dạng thô. Quá trình sàng lọc và rà soát sẽ giúp giảm đáng kể số lượng các giao dịch sai, nhờ đó làm giảm thời gian và công sức để xử lý. Bên cạnh đó, ngân hàng cũng cần phải nâng cao công tác quản trị dữ liệu, thiết lập các cơ sở trách nhiệm rõ ràng giữa các bộ phận tham gia vào trong quy trình đảm bảo an toàn an ninh dữ liệu. <br /> </div><div>Cụ thể, quy trình xây dựng dữ liệu cho Big Data sẽ gồm các bước như sau:<br /> </div><div>- Bước 1: Xác định nguồn dữ liệu (từ website, ứng dụng, thiết bị thông minh, mạng xã hội, truyền thông, chính phủ…). Ngân hàng cần phải nắm rõ nguồn dữ liệu cần tìm và cách thức thu thập.</div><div>- Bước 2: Xây dựng các hệ thống thu thập Big Data: xây dựng các phần mềm, ứng dụng hay các thiết bị có thể kết nối với máy chủ để truyển tải thông tin, dữ liệu. Dữ liệu của Big Data thuộc nhiều định dạng khác nhau nên hệ thống thu thập cần phải tiên tiến, tích hợp các công nghệ mới.</div><div>- Bước 3: Xây dựng hệ thống lưu trữ và quản lý để phục vụ cho việc phân tích sau này. Dữ liệu Big Data cần một hệ thống máy chủ lưu trữ. Hệ thống lữu trữ hiện tại gồm 2 loại lưu trữ trên đám mây (cloud) và lưu trữ tại công ty. Để lựa chọn phù hợp thì ngân hàng cần dự báo được khối lượng thông tin cần lưu trữ và các biện pháp bảo mật.</div><div>- Bước 4: Xây dựng hệ thống sàng lọc, làm sạch, phân tích dữ liệu và hệ thống phục vụ báo cáo. Bước này đòi hỏi chất lượng của đội ngũ nhân sự trong việc xây dựng các thuật toán khai thác dữ liệu, ứng dụng các mô hình định lượng thông minh để phân tích đa chiều và đưa ra các dự báo. </div><div>- Bước 5: Sử dụng kết quả phân tích để đưa ra các quyết định.</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://d2h0cx97tjks2p.cloudfront.net/blogs/wp-content/uploads/sites/2/2019/10/big-data-helps-in-risk-management.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="317" data-original-width="596" src="https://d2h0cx97tjks2p.cloudfront.net/blogs/wp-content/uploads/sites/2/2019/10/big-data-helps-in-risk-management.jpg" /></a></div><div class="separator" style="clear: both; text-align: center;"><br /></div><div><br /><br /></div><div><em>Thứ ba, chuẩn bị đội ngũ chuyên viên khoa học dữ liệu là điều kiện không thể thiếu được</em><br /> </div><div>Hiện nay, có một thực tế về nhân sự trong ngành Ngân hàng là cán bộ ngân hàng thì không hiểu rõ về công nghệ thông tin, còn người làm công nghệ thông tin thì không hiểu rõ về nghiệp vụ ngân hàng. Thêm nữa, các mô hình phân tích Big Data tại Việt Nam hiện nay chủ yếu là ứng dụng lại các mô hình có sẵn trên thế giới, phần lớn các chuyên gia về khoa học dữ liệu của Việt Nam còn hạn chế về khả năng phân tích mô hình. Do vậy, các ngân hàng muốn phát triển công nghệ đều phải thuê nhân lực nước ngoài với chi phí đắt đỏ. <br /> </div><div>Chuyên viên khoa học dữ liệu (Data scientist) là một nghề khá mới mẻ không chỉ ở Việt Nam mà ở nhiều nước trên thế giới. Nhóm nhân sự này đòi hỏi phải được đào tạo chuyên môn cao và phải có một sự đam mê tìm tới thế giới Big Data. Họ là những người hiểu rõ làm cách nào để tìm ra câu trả lời cho những quyết định quan trọng từ một khối lượng thông tin khổng lồ không hề có cấu trúc đang “dồn dập ập đến như những cơn sóng thần”. Với sự thành thạo về lĩnh vực kỹ thuật số, họ có thể nhận thấy và biết cách hình thành những cấu trúc từ khối lượng khổng lồ các dữ liệu sơ khởi và nhờ đó việc phân tích dữ liệu trở nên khả thi. Họ tìm ra những nơi có nguồn dữ liệu phong phú kết hợp với các nguồn dữ liệu chưa hoàn chỉnh khác và làm sạch bảng lưu kết quả truy vấn cơ sở dữ liệu. <br /> </div><div>Các nền kinh tế trong khu vực như Hàn Quốc, Đài Loan đã chuẩn bị lực lượng chất lượng cao, trong khi ở Việt Nam nguồn nhân lực phân khúc này vẫn còn hạn chế. Theo khảo sát của IDG, tại Việt Nam, nhân lực sẵn sàng cho công nghệ số chưa cao, các chương trình đào tạo đại học thay đổi rất chậm so với xu thế. Trong khi đó, nhiều trường đại học tại Mỹ đã đưa các giáo trình về trí tuệ nhân tạo, học máy (machine learning) vào giảng dạy MBA, một chuyên gia cho hay. Khoảng cách về khả năng kỹ thuật số sẽ chỉ ngày càng rộng thêm và ngân hàng nào không thể bắt kịp với xu hướng sẽ bị bỏ lại sau lưng. Bởi thế, việc đào tạo, quan tâm tới chất lượng nguồn nhân lực công nghệ cao cần được thực hiện trong toàn hệ thống tài chính - ngân hàng, đảm bảo đủ khả năng ứng dụng công nghệ thông tin, phương thức làm việc tiên tiến trong điều kiện hội nhập quốc tế sâu rộng.</div><div> </div><div><strong>Kết luận</strong><br /> </div><div>Một trong những lợi thế của ngân hàng truyền thống là khối lượng thông tin tài chính khổng lồ mà các ngân hàng lưu trữ về hàng triệu khách hàng của mình. Hơn thế nữa, ngân hàng có lợi thế về cấu trúc và vốn để khai thác nguồn tài nguyên mới này. Tiềm năng cho việc phân tích dữ liệu đã được nhìn nhận rộng rãi trong ngành tài chính với doanh thu từ Big Data và phân tích dữ liệu kinh doanh tăng từ 130 tỷ đô la Mỹ năm 2016 lên ước tính khoảng 203 tỷ đô la Mỹ năm 2020. Trong đó, lĩnh vực ngân hàng đóng góp tỷ trọng doanh thu lớn nhất khi dành 17 tỷ đô la Mỹ cho các giải pháp về Big Data và phân tích dữ liệu chỉ riêng trong năm 2016. Ứng dụng dữ liệu và phân tích trong ngân hàng là vô cùng. Chúng ta có thể sử dụng dữ liệu cho tiếp thị, phân phối và đa dạng hóa các dịch vụ cá nhân hóa, đáp ứng chính xác nhu cầu của từng khách hàng riêng lẻ. Big Data cũng cho phép các ngân hàng có thể thực hành quản trị rủi ro tốt hơn từ quản trị rủi ro tín dụng truyền thống đến những loại rủi ro thị trường phức tạp khác, từ rủi ro hoạt động nội bộ đến rủi ro từ yếu tố bên ngoài… Không chỉ có vậy, Big Data còn trợ giúp trong việc nâng cao chất lượng dịch vụ, đưa ra các dự báo về tình hình kinh doanh và lập kế hoạch kinh doanh. Với vô vàn ứng dụng của Big Data và sự phổ biến của nó trong các ngân hàng hiện đại, các ngân hàng ở Việt Nam nếu muốn nâng cao năng lực cạnh tranh, cải thiện lợi nhuận thì không còn lựa chọn nào khác ngoài việc gia nhập xu thế này. Và để có thể đảm bảo được tận dụng mọi lợi thế của Big Data thì yếu tố về chính sách, vốn, con người và công nghệ cần được chuẩn bị chu đáo cho bước phát triển này.</div></div><div style="color: #333333; font-family: Roboto; font-size: 14px;"><br /></div><div style="color: #333333; font-family: Roboto; font-size: 14px;">Nguồn blog:</div><div><ul><li><span style="color: #333333; font-family: Roboto;"><span style="font-size: 14px;"><a href="http://tapchinganhang.gov.vn/big-data-va-ung-dung-trong-hoat-dong-ngan-hang.htm">http://tapchinganhang.gov.vn/big-data-va-ung-dung-trong-hoat-dong-ngan-hang.htm</a></span></span></li><li><span style="color: #333333; font-family: Roboto;"><a href="https://www.theedgemarkets.com/article/cover-story-scoring-big-data">https://www.theedgemarkets.com/article/cover-story-scoring-big-data</a></span></li><li><span style="color: #333333; font-family: Roboto;"><a href="http://pubdocs.worldbank.org/en/935891585869698451/CREDIT-SCORING-APPROACHES-GUIDELINES-FINAL-WEB.pdf">http://pubdocs.worldbank.org/en/935891585869698451/CREDIT-SCORING-APPROACHES-GUIDELINES-FINAL-WEB.pdf</a></span></li></ul></div></div>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-1962899300838283022020-10-07T14:54:00.003+07:002020-10-07T14:54:45.107+07:00Marketing Automation - phương thức tối ưu ROI Marketing với Machine Learning và AI<p><b>Tiếp thị tự động hóa (Marketing automation)</b> là một nền tảng phần mềm (software platform) giúp các công ty có được mối quan hệ và trải nghiệm khách hàng được cá nhân hóa cao trên quy mô lớn, bằng cách tự động hóa quy trình làm việc của các chiến dịch tiếp thị để tạo ra nhiều khách hàng tiềm năng hơn, chốt được nhiều giao dịch hơn và đo lường thành công tiếp thị thông qua các kênh truyền thông khác nhau:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgFyy0UuhSlrUXbIQbJt3DwGbNs8RccBkPNa5SuF81xFH4vL_pi7PqkCprYFGY2HpvCX_-KPR_dloZIvWmKYmYPnfp3SOmKveRtHQA7Lb_Q2MBQbAHIMMQc-b8rGz9_TRhC5ua35dAMQG4/s1154/Communication+Channels.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="488" data-original-width="1154" height="270" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgFyy0UuhSlrUXbIQbJt3DwGbNs8RccBkPNa5SuF81xFH4vL_pi7PqkCprYFGY2HpvCX_-KPR_dloZIvWmKYmYPnfp3SOmKveRtHQA7Lb_Q2MBQbAHIMMQc-b8rGz9_TRhC5ua35dAMQG4/w640-h270/Communication+Channels.jpeg" width="640" /></a></div><br /><p>Các công cụ tự động hóa tiếp thị được sử dụng để giải quyết toàn bộ vòng đời của khách hàng bằng cách đồng hành với khách hàng tiềm năng (prospect) và khách hàng (customer) để nâng cao hành trình và nâng cao <a href="https://en.wikipedia.org/wiki/Average_revenue_per_user" target="_blank">ARPU (Doanh thu trung bình tương ứng với mỗi khách hàng)</a> của họ ở mỗi giai đoạn. Các trường hợp sử dụng tự động hóa tiếp thị phổ biến nhất như sau:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi6uZCuLZJ7ChL13sKIZsiXpNe_1zSO538Bo2kV8tCIkLo0ndCcOaffXSbQLYGMNZRk-nJ65iIPN_JdItImZY4aMVCwAb5f4xT4Uf-Hut6IWcVqzbQi-UbGvWgOi3sdM-M2Q46FhA778oM/s868/Marketing+Automation+most+commun+use+cases.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="252" data-original-width="868" height="186" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi6uZCuLZJ7ChL13sKIZsiXpNe_1zSO538Bo2kV8tCIkLo0ndCcOaffXSbQLYGMNZRk-nJ65iIPN_JdItImZY4aMVCwAb5f4xT4Uf-Hut6IWcVqzbQi-UbGvWgOi3sdM-M2Q46FhA778oM/w640-h186/Marketing+Automation+most+commun+use+cases.jpeg" width="640" /></a></div><p><b><i>Tự động hóa tiếp thị tận dụng tiềm năng cao của lượng dữ liệu (Big Data)</i></b> mà các công ty sở hữu, bằng cách sử dụng máy học để chia nhỏ các tập dữ liệu theo nhu cầu cụ thể (segmentation) (tinh chỉnh mục tiêu chiến dịch), cho điểm (đánh giá thái độ của khách hàng) và phát hiện cơ hội (tiết lộ các liên kết và tương quan ẩn), cho phép đảm bảo chiến dịch tiếp thị hiệu quả, đạt hiệu quả hoạt động và tăng trưởng doanh thu nhanh hơn. Các mô hình học máy AI mô tả và dự đoán giúp xác định khách hàng và nhu cầu của họ, để tăng khả năng họ phản hồi với một chiến dịch nhất định thông qua các kênh truyền thông cụ thể:</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMrUKqUCssdItAiTXdICAYV7mIoRa31ItyTsZ1RlXHDZqJvPixXHZBCVvynaVpQ7XTy1syDpy2hfkGQ5arEE1V7QTPhOxQ6H2A5vXAfElLUzZn_K0SERm3MWdA2wnbiD-aUW909DGgQ0E/s1259/Integration+of+Machine+learning+in+Campaign+Management+process.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="277" data-original-width="1259" height="140" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMrUKqUCssdItAiTXdICAYV7mIoRa31ItyTsZ1RlXHDZqJvPixXHZBCVvynaVpQ7XTy1syDpy2hfkGQ5arEE1V7QTPhOxQ6H2A5vXAfElLUzZn_K0SERm3MWdA2wnbiD-aUW909DGgQ0E/w640-h140/Integration+of+Machine+learning+in+Campaign+Management+process.jpeg" width="640" /></a></div><br /><h3 style="text-align: left;">Bước 1: Phân tách tập dữ liệu (Data Segmentation)</h3><div>Phản ứng của khách hàng đối với truyền thông tiếp thị có thể khác nhau tùy thuộc vào nhiều tiêu chí như kênh bán hàng, giới tính khách hàng, vị trí, hoạt động, giao dịch và các thông tin liên quan khác. Phân khúc là một công cụ hiệu quả giúp nhóm các khách hàng có đặc điểm tương tự bằng cách sử dụng dữ liệu lịch sử (hoạt động, thói quen mua hàng và đặc điểm hành vi của họ) và các thuật toán như phân tích thành phần chính (PCA), phương pháp K-means hoặc Two-Step để tìm các cụm. Dưới đây giải thích từng bước về thuật toán PCA để phân chia tập dữ liệu thành từng nhóm giá trị:</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhGQ1HO_LLAjoPkbexSGeutUO98fg8GurhfY9HgvMokkbHwj_hm4DEVRLYt67ef_Je1-RHh_UaP95GZZbZMrccpdR3KRJSMoDKpTnxhplz97SfcsTF52DvIap8NPdObuOV-_WZ7fpDniO0/s728/Principal+component+analysis+%2528PCA%2529+Algorithm+step-by-step.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="690" data-original-width="728" height="606" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhGQ1HO_LLAjoPkbexSGeutUO98fg8GurhfY9HgvMokkbHwj_hm4DEVRLYt67ef_Je1-RHh_UaP95GZZbZMrccpdR3KRJSMoDKpTnxhplz97SfcsTF52DvIap8NPdObuOV-_WZ7fpDniO0/w640-h606/Principal+component+analysis+%2528PCA%2529+Algorithm+step-by-step.jpeg" title="Principal component analysis (PCA) Algorithm step-by-step" width="640" /></a></div><br /><div>Các cụm kết quả (resulting clusters) phải được xây dựng với các nhà tiếp thị, để ánh xạ chúng tới các đặc điểm dễ hiểu thể hiện <b><i>“tính cách người mua”</i></b> riêng biệt. Điều này sẽ giúp <b><i>cá nhân hóa tốt hơn</i></b> việc giao tiếp với khách hàng của công ty, tùy thuộc vào xu hướng phản hồi của họ đối với các ưu đãi hoặc khuyến mại cụ thể, bằng cách xây dựng chiến lược và thông điệp tinh chỉnh cho từng cá nhân (hoặc phân khúc) đó để phù hợp với từng giai đoạn trong hành trình của khách hàng.</div><h3 style="text-align: left;">Bước 2: Chấm điểm hồ sơ khách hàng (Customer Profile Scoring)</h3><div><div>Làm phong phú thông tin khách hàng bằng cách bổ sung cho họ thông tin mới có giá trị cao được tạo ra bởi các thuật toán máy học giúp các nhà tiếp thị tối đa hóa chuyển đổi khách hàng tiềm năng và ARPU của khách hàng, những điểm số này được sử dụng trong chiến dịch tiếp thị làm điều kiện để thực hiện hành động phù hợp:</div><div>Chấm điểm khách hàng tiềm năng: cho phép phân loại khách hàng tiềm năng, bằng cách phân biệt giữa những người thực sự quan tâm đến sản phẩm với những người mới bắt đầu tìm kiếm một số thông tin. cơ hội khách hàng cụ thể sẵn sàng chuyển đổi càng cao. Nó có thể được tính bằng 2 cách:</div><div><ol style="text-align: left;"><li><b>Rules engine (hệ thống chấm điểm theo quy tắc)</b>: bằng cách tăng và giảm điểm số hàng đầu dựa trên tổng trọng số của tương tác, ví dụ: [+1 điểm] cho lượt truy cập trang web, [+5 điểm] nhấp vào Email liên hệ, [+10 điểm] nhấp vào danh mục sản phẩm, [+20 điểm] tải xuống hướng dẫn người mua, [+30 điểm] truy cập hình thức thanh toán, [-10 điểm] sau 1 tháng không hoạt động, [-30 điểm] hủy đăng ký nhận bản tin. Hạn chế: trọng số của tương tác được xác định theo cách thủ công và cần điều chỉnh liên tục</li><li><b>Predictive analytics (Phân tích dự đoán)</b> đặc biệt là <b>regression</b> (hồi quy), chẳng hạn như hồi quy logistic có thể được coi là xác suất chuyển đổi, nó cho phép:</li></ol></div></div><blockquote style="border: none; margin: 0px 0px 0px 40px; padding: 0px; text-align: left;"><blockquote style="border: none; margin: 0px 0px 0px 40px; padding: 0px; text-align: left;"><ul style="text-align: left;"><li>Loại bỏ việc chọn các yếu tố dự đoán theo cách thủ công, bằng cách sử dụng các thuật toán lựa chọn tính năng như lùi lại từng bước để chọn thông tin phù hợp nhất về các khách hàng tiềm năng từ thông tin nhân khẩu học, hành vi trực tuyến và tương tác qua email / xã hội.</li><li>Loại bỏ việc xác định trọng số (weight) vì nó được thuật toán hồi quy tự động xác định trong quá trình đào tạo mô hình.</li></ul></blockquote></blockquote><div><div><b>Tính điểm theo mô hình RFM [Lần truy cập gần đây, Tần suất, Tiền tệ]:</b> nó cung cấp định nghĩa chính xác về những khách hàng tốt nhất, những người trung thành nhất, những người chi tiêu nhiều nhất, những khách hàng gần như rời bỏ dịch vụ.</div><div><ul style="text-align: left;"><li><b>Recency score(điểm số lần truy cập gần đây):</b> Xác định khoảng thời gian [mua ngày gần đây nhất, mua ngày xa nhất] và xếp nó thành 3, 4 hoặc 5 xếp hạng. Những khách hàng đã mua gần đây có nhiều khả năng mua lại hơn là những khách hàng đã mua thêm trong quá khứ.</li><li><b>Frequency score(điểm tần suất):</b> Xác định khoảng thời gian [tần suất mua hàng cao nhất, tần suất mua hàng thấp nhất] và xếp nó thành 3, 4 hoặc 5 xếp hạng. Những khách hàng đã mua nhiều hàng hơn trong quá khứ có nhiều khả năng phản hồi hơn là những khách hàng đã mua ít hơn.</li><li><b>Monetary score (điểm số tiền tệ): </b>Xác định [giá trị tiền tệ cao nhất, giá trị tiền tệ thấp nhất] và xếp nó vào 3, 4 hoặc 5 xếp hạng Những khách hàng đã chi tiêu nhiều hơn (tổng cộng cho tất cả các giao dịch mua) trong quá khứ có nhiều khả năng phản hồi hơn những người đã chi tiêu ít hơn.</li></ul><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://reforge-brevity-uploads-prod.s3.amazonaws.com/brief/uploads/post/image_path/106/emma1535590191724.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="450" data-original-width="800" height="360" src="https://reforge-brevity-uploads-prod.s3.amazonaws.com/brief/uploads/post/image_path/106/emma1535590191724.png" width="640" /></a></div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRdPDgtOm62pfH5bIU6L53o7qbugBeVGMt8iKIc9ZN0xAdAfRF1mnBYa-2O-5vf8UlACKZKvsGq4gBfGA6N6tjXA2uLqq0CS6n4-bdAZGCqPRJkHJh5bTgwqE3RgpQJlqUTD5RwtTAGSc/s1244/RFM+score+step-by-step.jpeg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="372" data-original-width="1244" height="192" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRdPDgtOm62pfH5bIU6L53o7qbugBeVGMt8iKIc9ZN0xAdAfRF1mnBYa-2O-5vf8UlACKZKvsGq4gBfGA6N6tjXA2uLqq0CS6n4-bdAZGCqPRJkHJh5bTgwqE3RgpQJlqUTD5RwtTAGSc/w640-h192/RFM+score+step-by-step.jpeg" width="640" /></a></div><div><br /></div><div><b>Ưu đãi tốt nhất tiếp theo (Next best offer - NBO)</b>: sử dụng các thuật toán liên kết như <a href="https://en.wikipedia.org/wiki/Apriori_algorithm" target="_blank">Apriori</a> và <a href="https://medium.com/@lzpdatascience/what-is-the-difference-between-carma-and-apriori-dcb15ab6bfb5" target="_blank">CARMA</a> được xử lý dựa trên dữ liệu lịch sử (thói quen chi tiêu của khách hàng) để đề xuất cho từng khách hàng các sản phẩm và nâng cấp mới phù hợp nhất với nhu cầu của họ, giúp các công ty áp dụng phương pháp lấy khách hàng làm trung tâm (Customer-centric), tăng chuyển đổi marketing và khuyến khích bán hàng để tối ưu CLV</div><div><a href="https://towardsdatascience.com/churn-prediction-3a4a36c2129a" target="_blank">Churn score</a> (tỷ lệ tiêu hao): dự đoán những khách hàng có khả năng cao sẽ hủy đăng ký một dịch vụ.</div><div><br /></div><div>Dịch từ bài gốc:</div><div><a href="https://medium.com/@fenjiro/enhancing-marketing-automation-with-machine-learning-1abfb09dba93">https://medium.com/@fenjiro/enhancing-marketing-automation-with-machine-learning-1abfb09dba93</a></div><div><br /></div><div><br /></div><div><br /></div>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-84551757312199102662020-10-05T12:27:00.004+07:002020-10-06T09:15:21.400+07:00Fullstack Software Engineer 's Cookbook<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi5zacnQBCK4XjcO0lxSboG8h4DQ4O22NAmO-tU5vp0CNtstxnYUoihagfbjnCuvW-xyQ_qCds0IL66A2mcxvCHf3Ps6QA5oLCc3DT6x58nsmR57cFP7SYH7W3hI3bhQXz8CzuaxD90864/s1200/HOW-TO-BECOME-A-FULL-STACK-DEVELOPER-2019-ROADMAP.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="600" data-original-width="1200" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi5zacnQBCK4XjcO0lxSboG8h4DQ4O22NAmO-tU5vp0CNtstxnYUoihagfbjnCuvW-xyQ_qCds0IL66A2mcxvCHf3Ps6QA5oLCc3DT6x58nsmR57cFP7SYH7W3hI3bhQXz8CzuaxD90864/w640-h320/HOW-TO-BECOME-A-FULL-STACK-DEVELOPER-2019-ROADMAP.jpg" width="640" /></a></div><br /><div class="separator" style="clear: both; text-align: center;"><br /></div><h3 style="text-align: left;">Computer Science Knowledge</h3><p><span style="background-color: white; color: #08090a;">⭐️</span><a href="https://www.edx.org/course/introduction-to-computer-science-and-programming-7" target="_blank">Introduction to Computer Science and Programming Using Python</a></p><h3 style="text-align: left;">How The Internet Works</h3><div style="text-align: left;"><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://github.com/alex/what-happens-when" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">What happens when you go to google.com?<br /></a><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-02-introduction-to-eecs-ii-digital-communication-systems-fall-2012/readings/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Introduction to Networks<br /></a><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://hpbn.co/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Browser Networking<br /></a><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎊 </span><a href="https://pages.di.unipi.it/ricci/501302.pdf" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">IP Addressing<br /></a><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://daniel.haxx.se/http2/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">HTTP/2</a></div><h3 style="text-align: left;">Front End Programming Knowledge</h3><p style="text-align: left;"><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://learn.shayhowe.com/advanced-html-css/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">HTML & CSS</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://github.com/getify/You-Dont-Know-JS" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">JavaScript</a></p><p></p><p style="text-align: left;"><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><span style="background-color: white;"><span face="-apple-system, system-ui, Segoe UI, Roboto, Helvetica, Arial, sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol" style="color: #08090a;"><a href="https://www.youtube.com/watch?v=W6NZfCO5SIk" target="_blank">Learn JavaScript in 1 Hour</a></span></span></p><p style="text-align: left;"><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://www.freecodecamp.org/news/learn-bootstrap-4-in-30-minute-by-building-a-landing-page-website-guide-for-beginners-f64e03833f33/" target="_blank">Learn Bootstrap 4 in 30 minutes</a></p><h3 style="text-align: left;">Operating Systems</h3><div><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://serversforhackers.com/s/start-here" target="_blank">https://serversforhackers.com/s/start-here</a></div><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://launchschool.com/books/command_line" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Using the command line</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="http://markburgess.org/os/os.pdf" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">What is an operating system?</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://www.akkadia.org/drepper/cpumemory.pdf" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Memory</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎊 </span><a href="http://catb.org/esr/writings/taoup/html/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Unix Programming</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://tldp.org/LDP/abs/html/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Bash-Scripting Guide</a></p><h3 style="text-align: left;">Programming Languages</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://en.wikibooks.org/wiki/PHP_Programming" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Know PHP</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://www.rubyguides.com/ruby-tutorial/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Learn Ruby</a></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://beginnersbook.com/java-tutorial-for-beginners-with-examples/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Learn Java</a></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://www.youtube.com/watch?v=grEKMHGYyns" target="_blank">Learn Java 8 - Full Tutorial for Beginners</a></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://www.learnpython.org/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Learn Python</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎊 </span><a href="https://gobyexample.com/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Learn Go</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://github.com/maxogden/art-of-node" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Know Server-Side JavaScript</a></p><h3 style="text-align: left;">Version Control</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://marklodato.github.io/visual-git-guide/index-en.html" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">A Visual Git Reference</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://onlywei.github.io/explain-git-with-d3/#" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Visualizing Git Concepts with D3</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://github.com/tiimgreen/github-cheat-sheet" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Github Cheat Sheet</a></p><h3 style="text-align: left;">Database Concepts</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🌟 </span><a href="https://dev.to/nielsenjared/what-is-object-relational-mapping-how-to-roll-your-own-javascript-orm-4ni3" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Object-Relational Mapping</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://neo4j.com/blog/acid-vs-base-consistency-models-explained/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">ACID</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://medium.com/@bretdoucette/n-1-queries-and-how-to-avoid-them-a12f02345be5" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">N+1 Problem</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">☄️ </span><a href="https://www.digitalocean.com/community/tutorials/understanding-database-sharding" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Sharding</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="http://www.julianbrowne.com/article/brewers-cap-theorem" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">CAP Theorem</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💥 </span><a href="https://dev.to/nexttech/database-normalization-explained-5b1a" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Normalization</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🌟 </span><a href="https://dev.to/helenanders26/sql-series-speed-up-your-queries-with-indexes-3c83" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Indexes</a></p><h3 style="text-align: left;">Relational Databases</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://web.cecs.pdx.edu/~maier/TheoryBook/TRD.html" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Theory of Relational Databases</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://www.techotopia.com/index.php/MySQL_Essentials" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Learn MySQL</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://www.syncfusion.com/ebooks/postgres" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Learn PostgreSQL</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎊 </span><a href="https://www.tutorialspoint.com/mariadb/index.htm" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Learn MariaDB</a></p><h3 style="text-align: left;">NoSQL Databases</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💡 </span><a href="https://www.udemy.com/course/getting-started-with-arangodb/" target="_blank">Getting Started with ArangoDB</a></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💡 </span><a href="https://www.youtube.com/watch?v=uD3p_rZPBUQ" target="_blank">An Introduction To NoSQL Databases</a></p><div><div><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💡 </span><a href="https://www.guru99.com/nosql-tutorial.html">NoSQL Tutorial: Learn NoSQL Features, Types, What is, Advantages</a></div></div><div><br /></div><h3 style="text-align: left;">Big Data, Data Science and Machine Learning </h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://www.udacity.com/course/intro-to-data-analysis--ud170">https://www.udacity.com/course/intro-to-data-analysis--ud170</a></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://www.youtube.com/watch?v=-ETQ97mXXF0" target="_blank">Data Science Full Course - Learn Data Science in 10 Hours</a></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://www.youtube.com/watch?v=9f-GarcDY58" target="_blank">Machine Learning Tutorial</a> </p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://www.youtube.com/watch?v=r-uOLxNrNk8" target="_blank">Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)</a></p><h3 style="text-align: left;">APIs</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://launchschool.com/books/working_with_apis" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Working with APIs</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💥 </span><a href="https://dev.to/drminnaar/rest-api-guide-14n2" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">REST</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💡 </span><a href="https://dev.to/leonardomso/a-beginners-guide-to-graphql-3kjj" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">GraphQL</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">☄️ </span><a href="https://dev.to/radixdlt/json-rpc-vs-rest-for-distributed-platform-apis-3n0m" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">JSON-RPC</a></p><h3 style="text-align: left;">Caching</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://developer.mozilla.org/en-US/docs/Web/HTTP/Caching" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">HTTP caching</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">☄️ </span><a href="https://openmymind.net/2012/1/23/The-Little-Redis-Book/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Redis</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://www.tutorialspoint.com/memcached/index.htm" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Memcached</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🚀 </span><a href="https://dev.to/blarzhernandez/javascript-service-workers-visualized-1683" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Service workers</a></p><h3 style="text-align: left;">Security</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://dev.to/ahmedatefae/web-security-knowledge-you-must-understand-it-part-i-https-tls-ssl-cors-csp-298l" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">HTTPS + TLS</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://dev.to/lydiahallie/cs-visualized-cors-5b8h" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">CORS</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://dev.to/wagslane/very-basic-intro-to-hash-functions-sha-256-md-5-etc-399j" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">MD5</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎊 </span><a href="https://dev.to/wagslane/how-sha-2-works-step-by-step-sha-256-11ci" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">SHA-2</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💡 </span><a href="https://dev.to/wagslane/very-basic-intro-to-the-scrypt-hash-7l5" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">SCrypt</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💥 </span><a href="https://dev.to/sylviapap/bcrypt-explained-4k5c" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">BCrypt</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">☄️ </span><a href="https://owasp.org/www-project-top-ten/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">OWASP</a></p><h3 style="text-align: left;">CI/CD</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://dev.to/thejessleigh/different-types-of-testing-explained-1ljo" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Testing your code</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://www.bogotobogo.com/DevOps/Jenkins/images/Intro_install/jenkins-the-definitive-guide.pdf" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Jenkins</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://github.com/dwyl/learn-travis" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">TravisCI</a></p><h3 style="text-align: left;">Software Development Concepts</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">☄️ </span><a href="https://dev.to/ham8821/solid-principles-to-start-with-object-oriented-programming-1e49" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">SOLID</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://dev.to/getd/kiss-keep-it-simple-short-my-tech-writing-principal-jjn" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">KISS</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💥 </span><a href="https://dev.to/gonedark/practicing-yagni-3n1d" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">YAGNI</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://dev.to/codemouse92/clean-dry-solid-spaghetti-1lgm" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">DRY</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="http://www.infoq.com/minibooks/domain-driven-design-quickly" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Domain-Driven Design</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🌟 </span><a href="https://github.com/grzesiek-galezowski/tdd-ebook" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Test Driven Development</a></p><h3 style="text-align: left;">Software Architecture </h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://www.oreilly.com/programming/free/files/microservices-vs-service-oriented-architecture.pdf" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Microservices and Service Oriented Architecture</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎊 </span><a href="https://msdn.microsoft.com/en-us/library/jj554200.aspx" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">CQRS</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">⭐️ </span><a href="https://docs.microsoft.com/en-us/dotnet/standard/serverless-architecture/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Serverless</a></p><h3 style="text-align: left;">Cloud Computing & Containers</h3><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><span style="background-color: white;"><span face="-apple-system, system-ui, Segoe UI, Roboto, Helvetica, Arial, sans-serif, Apple Color Emoji, Segoe UI Emoji, Segoe UI Symbol" style="color: #08090a;"><a href="https://www.youtube.com/watch?v=RWgW-CgdIk0" target="_blank">Cloud Computing Tutorial for Beginners</a></span></span></p><p><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://dev.to/skaytech/docker-fundamentals-2ibi" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;" target="_blank">Docker Fundamentals</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://www.packtpub.com/free-ebooks/docker-cookbook-second-edition" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Docker Cookbook</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💫 </span><a href="https://www.packtpub.com/free-ebooks/kubernetes-cookbook-second-edition" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Kubernetes Cookbook</a></p><p><span style="background-color: white; color: #08090a;">💫 </span><a href="https://serversforhackers.com/s/docker-in-dev-v2-i">https://serversforhackers.com/s/docker-in-dev-v2-i</a></p><h3 style="text-align: left;">Servers</h3><div style="text-align: left;"><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">☄️ </span><a href="https://github.com/trimstray/nginx-admins-handbook" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Nginx Handbook<br /></a><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💡 </span><a href="https://httpd.apache.org/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Apache<br /></a><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">💥 </span><a href="https://caddyserver.com/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Caddy</a></div><h3 style="text-align: left;">Scalability</h3><div><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">✨ </span><a href="https://www.oreilly.com/content/real-world-maintainable-software/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Real-World Maintainable Software</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🎉 </span><a href="https://12factor.net/" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">The 12 Factor App</a><br style="background-color: white; box-sizing: border-box; color: #08090a; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";" /><span face="-apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"" style="background-color: white; color: #08090a;">🌟 </span><a href="https://dev.to/mmcshinsky/why-frontend-architecture-matters-1ldj" style="background-color: white; box-sizing: border-box; font-family: -apple-system, system-ui, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; text-decoration-line: none;">Architecting Frontend Projects To Scale</a></div><h3 style="text-align: left;">Digital Business Strategy & Customer-Centric IT Strategy</h3><p><span style="background-color: white; color: #08090a;">🌟 </span><a href="https://www.coursera.org/learn/uva-darden-customer-centric-it-strategy">https://www.coursera.org/learn/uva-darden-customer-centric-it-strategy</a></p><p><b><i>Refer links</i></b></p><p></p><ul style="text-align: left;"><li><a href="https://github.com/kamranahmedse/developer-roadmap">https://github.com/kamranahmedse/developer-roadmap</a></li><li><a href="https://github.com/ossu/computer-science">https://github.com/ossu/computer-science</a></li><li><a href="https://dev.to/harshaambati/back-end-developers-roadmap-1icp">https://dev.to/harshaambati/back-end-developers-roadmap-1icp</a></li><li><a href="https://dev.to/ender_minyard/full-stack-developer-s-roadmap-2k12">https://dev.to/ender_minyard/full-stack-developer-s-roadmap-2k12</a></li></ul><p></p>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-33229064165675546702020-08-12T15:01:00.005+07:002020-08-12T15:01:41.970+07:00Hiểu về thế giới từ dữ liệu như thế nào ?<div class="separator" style="clear: both; text-align: center;"><a href="https://kvaes.files.wordpress.com/2013/05/20130531-182549.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="499" data-original-width="580" src="https://kvaes.files.wordpress.com/2013/05/20130531-182549.jpg" /></a></div><p><b>Dữ liệu (Data)</b> được coi là biểu tượng hoặc dấu hiệu, đại diện cho các kích thích hoặc tín hiệu, sự kiện đã xảy ra được ghi nhận bởi tác nhân quan sát (sensor, người hay thiết bị thu thập data chuyên dụng)</p><p><b>Thông ti</b>n được định nghĩa là dữ liệu có ý nghĩa và mục đích. Chúng ta chỉ hiểu được thông tin khi có ngữ cảnh, nơi thế giới mà dữ liệu đã được thu thập khách quan. </p><p><b>Kiến thức</b> là sự kết hợp linh hoạt giữa kinh nghiệm, giá trị, thông tin theo ngữ cảnh, cái nhìn sâu sắc của chuyên gia và nền tảng trực giác bên trong mỗi người, cung cấp một môi trường và khuôn khổ để đánh giá và kết hợp các trải nghiệm và thông tin mới. Nó bắt nguồn và được áp dụng trong tâm trí của chúng ta. </p><p>Trong các tổ chức, nó thường không chỉ được nhúng trong các tài liệu và kho lưu trữ mà còn trong các thói quen, quy trình, thực hành và chuẩn mực của tổ chức.</p><p><b>Sự khôn ngoan</b> là khả năng tăng hiệu quả. Trí tuệ làm tăng thêm giá trị, đòi hỏi chức năng tinh thần mà chúng ta gọi là khả năng phán đoán của người lãnh đạo trong tổ chức. </p><p><b>Các giá trị đạo đức và thẩm mỹ</b> thường có tính nội hàm trong một hệ thống, nó là phản chiếu theo độ đo của theo quan điểm cá nhân và ý thức hệ chính trị/tôn giáo #Ideology </p><div class="separator" style="clear: both; text-align: center;"><a href="https://kvaes.files.wordpress.com/2013/05/20130531-183651.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="298" data-original-width="575" src="https://kvaes.files.wordpress.com/2013/05/20130531-183651.jpg" /></a></div><p><br /></p><p>nguồn dịch từ</p><p>https://kvaes.wordpress.com/2013/05/31/data-knowledge-information-wisdom/</p>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-333805328101593012020-08-02T11:45:00.010+07:002020-10-14T10:32:24.503+07:00How to build Smart Artificial Evolution Loop with Leo CDP<div data-block="true" data-editor="b1gsg" data-offset-key="av820-0-0" style="background-color: white;"><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><div class="separator" style="clear: both; color: #1d2129; font-family: inherit; font-size: 14px; text-align: center; white-space: pre-wrap;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgpKs7MOnSGx1htg2WVHP1tR12T101Qn2R1mDdO6VEj4HbBMB_-1vct9dM36hLHkVcpb3pPNAS8NVuU6FDJ2j-UpFaaZ-aB6HEqKiJfcGhRioy7D7kxGE22-zLkSbkBh0MDiTp77hKfrIw/s1643/How+to+build+Smart+Artificial+Evolution+Loop+with+Leo+Platform.png" style="margin-left: 1em; margin-right: 1em;"> <img border="0" data-original-height="1133" data-original-width="1643" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgpKs7MOnSGx1htg2WVHP1tR12T101Qn2R1mDdO6VEj4HbBMB_-1vct9dM36hLHkVcpb3pPNAS8NVuU6FDJ2j-UpFaaZ-aB6HEqKiJfcGhRioy7D7kxGE22-zLkSbkBh0MDiTp77hKfrIw/s1600/How+to+build+Smart+Artificial+Evolution+Loop+with+Leo+Platform.png" style="width: 96%;" />
</a></div><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><b>Vì sao chỉ dùng ý chí quyết tâm Freewill để thích nghi với hoàn cảnh là không đủ nếu {quốc gia, tổ chức, công ty, gia đình} của bạn có chi phí {nợ, vận hành , tiêu dùng} quá lớn ?</b></font></span></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><span data-offset-key="av820-2-0" style="font-size: 14px; white-space: pre-wrap;"><font color="#1d2129" face="arial"><blockquote>
Tóm tắt:
<i>Thuyết tiến hoá là một lý thuyết khoa học đã thay đổi nhận thức con người về quá trình phát triển sinh học trong tự nhiên, nó cũng đúng một phần với xã hội loài người thời kỳ đầu tiên. Tuy nhiên, chúng ta với tư cách là một loài tiến hoá cao cấp trên hành tinh trái đất có đủ quyền tự do để lựa chọn phương thức tiến hoá có tính tiến bộ nhất.</i></blockquote></font></span></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><span style="font-size: 14px;">
bài viết trình bày quan điểm cá nhân của mình cho câu hỏi trên, cũng như vẽ tầm nhìn mà công ty công nghệ #USPA sẽ xây dựng trong 5 năm tới.
Mình giải thích một số thuật ngữ chính trong hình vẽ như sau:
</span><b style="font-size: 14px;">#Evolution Loop:</b><span style="font-size: 14px;"> là vòng lặp tiến hoá mà các công ty hay sẽ phải thích nghi với hoàn cảnh.
</span></font></span></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><h3 style="text-align: left;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><span style="font-size: 14px;">Có tất cả 3 cấp độ tiến hoá phổ biến (theo quan điểm cá nhân mình)</span></font></span></h3><div><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><span style="font-size: 14px;"><br /></span></font></span></div><h3 style="text-align: left;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><i>1️⃣ Quá trình tiến hoá sinh học để hình thành ý thức giá trị cá nhân</i></font></span></h3><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><b style="font-size: 14px;">#Personal Thinking:</b><span style="font-size: 14px;"> là quá trình tiến hoá, phát triển nhận thức ở cấp độ một cá nhân từ lúc sinh ra, trưởng thành và khẳng định giá trị bản thân với xã hội.
</span><b style="font-size: 14px;">Vòng lặp OODA </b><span style="font-size: 14px;">là bản chất chính trong quá trình phát triển này. Bốn bước chính bao gồm: #Observe (quan sát), #Orient (định hướng), #Decision (quyết định con đường đi) và #Action (hành động)</span></font></span></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><span style="font-size: 14px;">
</span></font></span><h3 style="text-align: left;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial">2️⃣ Quá trình tiến hoá chiến lược để hình thành ý thức hệ tập thể, quốc gia</font></span></h3><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><b style="font-size: 14px;"><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><b>#Strategic Thinking:</b><span> là quá trình tiến hoá thứ 2 sau quá trình tiến hoá sinh học và nhận thức cá nhân. Các cá nhân sẽ liên kết với nhau trong 1 hệ thống luật lê như một nhóm (team hay business unit) để cùng nhau tồn tại và phát triển. Đây là quá trình tiến hoá hình thành các làng xã, các công ty vừa và nhỏ.</span></div></b><span style="font-size: 14px;">
</span><i style="font-size: 14px;">Các quá trình tiến hoá chủ động, có tính chiến lược sẽ diễn ra trong 4 bước </i><span style="font-size: 14px;">
</span><b style="font-size: 14px;">#Analytics:</b><span style="font-size: 14px;"> tổng hợp và phân tích dữ liệu và tổng quát hoá thành các quy trình.
</span><b style="font-size: 14px;">#Visual Thinking:</b><span style="font-size: 14px;"> tư duy ở mức độ quy trình với hoàn cảnh cụ thể, diễn ra trong bộ não các lãnh đạo của nhóm hay tổ chức.
</span><b style="font-size: 14px;">#Critical Thinking:</b><span style="font-size: 14px;"> các lãnh đạo sẽ tổ chức các buổi meeting để tư duy phản biện lẫn nhau
</span><b style="font-size: 14px;">#Strategy Thinking:</b><span style="font-size: 14px;"> một chiến lược cuối cùng sẽ được thông qua để giúp tổ chức từ trạng thái thích nghi bị động sang chủ động trong các tình huống đã được chuẩn bị kỹ lưỡng.
Quá trình tiến hoá kiểu trên đã diễn ra trong lịch sử xã hội loài người trong 5000 năm qua ở nhiều cấp độ khác nhau. </span></font></span></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><span style="font-size: 14px;">Đây là một quá trình đẫm máu vì sự mâu thuẫn quyền lợi diễn ra giữa các lãnh đạo có tư duy chiến lược khác nhau, dẫn đến những cuộc chiến tranh đầy chết chóc. (chiến tranh tôn giáo, chiến tranh quyền lực chính trị, hay giữa các quốc gia để giành tầm ảnh hưởng quyền lực,...)</span></font></span></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial"><span style="font-size: 14px;">
</span></font></span><h3 style="text-align: left;"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129" face="arial">3️⃣ Quá trình tiến hoá tầm nhìn từ thông tin tri thức hay Dataism để hình thành ý thức, các giá trị đạo đức chung và niềm tin về các mô hình chân lý sự thật có giá trị vượt trên không gian và thời gian</font></span></h3><font face="arial"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129"><span style="font-size: 14px;">Vì lý do tiến hoá ở mức độ 1 và 2, trong quá trình tiến hoá xã hội lịch sử, các tôn giáo lớn xuất hiện để giúp con người tiến hoá về mặt ý thức và nhận thức. Nó cân bằng và giảm tính bạo lực do quá trình tiến hoá tự nhiên tạo ra.
<b><i>Tiến hoá về mặt tâm linh và ý thức hệ giúp con người xây dựng những giá trị nhân sinh quan vượt thời gian</i></b> trong hơn 3000 năm qua, từ Do Thái giáo, Kitô giáo, Phật giáo,... đều chứa đựng kiến thức và tri thức để giúp xã hội phát triển, giúp cân bằng giữa bản chất tiến hoá sinh học và tiến hoá nhận thức để con người bớt sống theo bản năng, lấy tri thức và đạo đức là giá trị trung tâm.
VD: Kitô giáo lấy giá trị tình yêu giữa con người trong xã hội làm quan điểm trung tâm, Phật giáo lấy sự tỉnh thức trong tâm trí là khái niệm chính.</span></font></span></font></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><font face="arial"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129"><span style="font-size: 14px;"></span></font></span></font></div><blockquote><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><font face="arial"><span data-offset-key="av820-2-0" style="white-space: pre-wrap;"><font color="#1d2129"><span style="font-size: 14px;">Ở thế kỷ 21, lần đầu tiên con người đang ở xu hướng kỹ thuật số #Digitalization mọi thứ. Chủ nghĩa dữ liệu #Dataism được hình thành để mang lại ý thức hệ đầu tiên ở thiên niên kỷ thứ 3. Điều này vẫn đang xảy ra nhiều tranh luận sôi nổi giữa các nhà triết học, thần học và khoa học. </span></font></span></font><span style="color: #1d2129; font-family: arial; font-size: 14px; white-space: pre-wrap;">Tuy nhiên, mọi hệ thống kỹ thuật số phải được vận hành dựa trên dữ liệu và cuộc sống con người ngày càng phụ thuộc computer, smart phone và Internet. Đây là điều không thể phủ nhận.</span></div></blockquote><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg42MQEmoRLBvfY3dH-5_ITH9mduOJ804MCjrc3SL5gRgk86nh1o6330qVmVvdc3i0pMxFgx1c68Vzoy9paOGY8cC4Sh83Bib00dHbzgPV2LFVolicln8ja4xTNfK14HkvztmbrfggdMYY/s1677/The+Rise+of+Dataism.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1175" data-original-width="1677" height="448" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg42MQEmoRLBvfY3dH-5_ITH9mduOJ804MCjrc3SL5gRgk86nh1o6330qVmVvdc3i0pMxFgx1c68Vzoy9paOGY8cC4Sh83Bib00dHbzgPV2LFVolicln8ja4xTNfK14HkvztmbrfggdMYY/w640-h448/The+Rise+of+Dataism.png" width="640" /></a></div><div class="separator" style="clear: both; text-align: center;"><font size="2"><a href="https://singularityhub.com/2018/09/30/the-rise-of-dataism-a-threat-to-freedom-or-a-scientific-revolution/">https://singularityhub.com/2018/09/30/the-rise-of-dataism-a-threat-to-freedom-or-a-scientific-revolution/</a></font></div><div class="_1mf _1mj" data-offset-key="av820-0-0" style="direction: ltr; position: relative;"><br /></div></div><div data-block="true" data-editor="b1gsg" data-offset-key="99k9t-0-0" style="background-color: white; color: #1d2129; font-size: 14px; white-space: pre-wrap;"></div>
<div style="text-align: center;"><iframe allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" frameborder="0" height="350" src="https://www.youtube.com/embed/xNAJevlQNuk" width="560"></iframe></div><div style="text-align: center;"><br /></div><div style="text-align: left;">Trọng tâm chính ở cấp độ thứ 3 là sử dụng ý thức con người ở thực tại kết hợp quá trình tự nhận thức trong tâm trí, tự học hỏi để tìm ra các quy luật mô hình nhân quả (Causality Model) trong một xã hội cụ thể và tổng quát hoá lên thành các quy luật có tính phổ quát cao (Universal Laws).</div><div style="text-align: left;">Ở mức độ tự nhiên, quá trình này cần những người lãnh đạo có khả năng thiên phú cao, kết hợp sự tự rèn luyện liên tục. </div><div><font size="5"></font><blockquote style="text-align: center;"><font size="5">Ở mức độ kỹ thuật số, câu hỏi đặt ra liệu con người kết hợp máy móc có thể hình thành một đức tin mới ? Đó là câu hỏi mà bản thân mình cũng đang đi tìm câu trả lời </font></blockquote></div>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-46022901154257160632020-07-22T10:46:00.001+07:002020-07-22T10:46:47.645+07:00Data Science Courses<div style="background-color: white; color: #414141; font-family: Lora, Lora, Times, serif; font-size: 16px; line-height: 1.5; margin-bottom: 1em; margin-top: 1em; overflow-wrap: break-word !important;">
<span style="font-weight: 700;">Note: This section includes a lot of Massive Open Online Courses (MOOCs). If you want to enroll in a free version of a MOOC, please select the "Full Course, No Certificate" (edX) or "<a href="https://www.youtube.com/watch?v=TfXmw6KMgTM" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 24px; outline: none; text-decoration-line: none;">Audit</a>" (Coursera) option. If you opt to take the course for a certificate/credential, you will be charged.</span></div>
<ul style="background: none rgb(255, 255, 255); color: #414141; content: ""; font-family: Lora, Lora, Times, serif; font-size: 16px; margin: 0px 0px 0px 1.2rem; padding: 0px 0px 10px;">
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">A Crash Course in Data Science</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fdata-science-course" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Applied Data Science</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Fspecializations%2Fapplied-data-science" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - IBM</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Building a Data Science Team</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fbuild-data-science-team" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Creating Dashboards and Storytelling with Tableau</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fdataviz-dashboards" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - UC Davis</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science (What is Data Science?)</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fwhat-is-datascience" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - IBM</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Databases and SQL for Data Science</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fsql-data-science" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - IBM</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science Ethics </span>- <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-ethics%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - University of Michigan</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: Linear Regression</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-r-basics%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science Methodology</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fdata-science-methodology" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - IBM</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: Probability</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-probability%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: Productivity Tools</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-productivity-tools%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science Tools</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-tools%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - IBM</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: Machine Learning</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-machine-learning%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science Math Skills</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fdatasciencemathskills" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Duke University</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: Probability</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-probability%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: R Basics</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-r-basics%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: Visualization</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-visualization%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Data Science: Wrangling</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fdata-science-wrangling%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Developing Data Products</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fdata-products" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Essential Design Principles for Tableau</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fdataviz-design" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - UC Davis</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Exploratory Data Analysis</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fexploratory-data-analysis" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Getting and Cleaning Data</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearnhttps%3A%2F%2Fwww.coursera.org%2Flearn%2Fdata-cleaning%3F%2Fpython-data-analysis" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Inferential Statistics</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Finferential-statistics" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - University of Amsterdam</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Introduction to Big Data</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fintroduction-to-big-data-2%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Microsoft</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Introduction to Computational Thinking and Data Science</span> - <a href="http://www.openculture.com/2017/06/introduction-to-python-data-science-computational-thinking-free-online-courses-from-mit.html" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Eric Grimson, John Guttag, and Ana Bell, MIT</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Introduction to Data Science in Python</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fpython-data-analysis" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - University of Michigan</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Introduction to Probability</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fintroduction-to-probability%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Introduction to R for Data Science</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fintroduction-to-r-for-data-science-2%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Microsoft</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Linear Regression and Modeling</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Flinear-regression-model" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Duke University</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Machine Learning</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fmachine-learning" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Andrew Ng, Stanford</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Managing Data Analysis</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fmanaging-data-analysis" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Open Source Tools for Data Science</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fopen-source-tools-for-data-science" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - IBM</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Practical Machine Learning</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fpractical-machine-learning" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Probability and Statistics in Data Science using Python</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fprobability-and-statistics-in-data-science-using-p%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - UCSD</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Python for Data Science and AI</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fpython-for-applied-data-science-ai" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - IBM</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Python Data Structures</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fpython-data" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - University of Michigan</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">R Programming</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fr-programming" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Reproducible Research</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Freproducible-research" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">Statistics and R</span> - <a href="https://www.awin1.com/cread.php?awinmid=6798&awinaffid=428885&clickref=&p=%5B%5Bhttps%253A%252F%252Fwww.edx.org%252Fcourse%252Fstatistics-and-r%5D%5D" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Harvard</li>
<li style="background: none 0px 10px no-repeat; line-height: 22.4px; list-style-position: outside; list-style-type: disc; margin-bottom: 0rem; margin-left: 1rem; padding: 0px; zoom: 1;"><span style="font-weight: 700;">The Data Scientist’s Toolbox</span> - <a href="https://click.linksynergy.com/deeplink?id=Cu8bOePBZBg&mid=40328&murl=https%3A%2F%2Fwww.coursera.org%2Flearn%2Fdata-scientists-tools" sl-processed="1" style="color: #0183b2; font-size: inherit; line-height: 22.4px; outline: none; overflow-wrap: break-word; text-decoration-line: none;">Massive Open Online Course (MOOC)</a> - Johns Hopkins</li>
</ul>
Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-66646432226833382372020-07-07T16:03:00.002+07:002020-07-08T17:59:09.651+07:0020 cách thực tế để triển khai khoa học dữ liệu (Data Science) trong Marketing <div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg0JYZ6gE6ytndW2kguVfna2LQLE570utZnEUrrs-d2ZMB1FFp1C6nA038kwJYADXq0IDAn2UAGy8LKkf4dbLjbitUnKj1YQeStjOAVscI92ZNtYQIstmN3fXg_W3MuNZd_91u22_sPNIQ/s1600/20+ca%25CC%2581ch+thu%25CC%259B%25CC%25A3c+te%25CC%2582%25CC%2581+%25C4%2591e%25CC%2582%25CC%2589+trie%25CC%2582%25CC%2589n+khai+Data+Science+trong+Marketing.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="789" data-original-width="940" height="335" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg0JYZ6gE6ytndW2kguVfna2LQLE570utZnEUrrs-d2ZMB1FFp1C6nA038kwJYADXq0IDAn2UAGy8LKkf4dbLjbitUnKj1YQeStjOAVscI92ZNtYQIstmN3fXg_W3MuNZd_91u22_sPNIQ/s400/20+ca%25CC%2581ch+thu%25CC%259B%25CC%25A3c+te%25CC%2582%25CC%2581+%25C4%2591e%25CC%2582%25CC%2589+trie%25CC%2582%25CC%2589n+khai+Data+Science+trong+Marketing.png" width="400" /></a></div>
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Trong thập kỷ qua, mức tiêu thụ thông tin trực tuyến đã tăng mạnh do khả năng phát triển rộng rãi của Internet. Ước tính có hơn 6 tỷ thiết bị được kết nối với internet ngay bây giờ. Khoảng 2,5 triệu terabyte dữ liệu được tạo ra mỗi ngày. Đến năm 2020, cứ mỗi một người, sẽ có 1,7 MB dữ liệu được tạo ra mỗi giây.</div>
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Đối với các nhà tiếp thị, lượng dữ liệu đáng kinh ngạc này là một mỏ vàng. Nếu dữ liệu này có thể được xử lý và phân tích chính xác, nó có thể cung cấp những hiểu biết có giá trị mà các nhà tiếp thị có thể sử dụng để nhắm mục tiêu khách hàng. Tuy nhiên, giải mã khối dữ liệu khổng lồ là một nhiệm vụ thách thức. Đây là nơi khoa học dữ liệu có thể giúp đỡ rất nhiều.<br />
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<a href="https://www.researchgate.net/profile/Eduardo_Garcia_Del_Valle/publication/327612291/figure/fig4/AS:670200676511747@1536799701256/Sequence-of-functional-units-of-a-data-science-pipeline-including-data.ppm" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="377" data-original-width="800" height="300" src="https://www.researchgate.net/profile/Eduardo_Garcia_Del_Valle/publication/327612291/figure/fig4/AS:670200676511747@1536799701256/Sequence-of-functional-units-of-a-data-science-pipeline-including-data.ppm" width="640" /></a></div>
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Khoa học dữ liệu là một lĩnh vực khai thác thông tin có ý nghĩa từ dữ liệu và giúp các nhà tiếp thị sáng suốt những hiểu biết đúng đắn về thị trường và khách hàng. Những hiểu biết này có thể là về các khía cạnh tiếp thị khác nhau như ý định của khách hàng, kinh nghiệm, hành vi, vv sẽ giúp họ tối ưu hóa hiệu quả các chiến lược tiếp thị của họ và thu được doanh thu tối đa.</div>
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<b><i>Hãy cùng xem qua 20 cách thực tế để Khoa học dữ liệu có thể triển khai trong Marketing:</i></b></div>
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<b>1. Tối ưu hóa ngân sách tiếp thị (Marketing Budget Optimization)</b></div>
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Các nhà tiếp thị luôn ở trong một ngân sách nghiêm ngặt. Mục tiêu chính của mỗi nhà tiếp thị là lấy ROI tối đa từ ngân sách được phân bổ của họ. Đạt được điều này luôn luôn là khó khăn và tốn thời gian. Mọi thứ không phải lúc nào cũng đi theo kế hoạch và việc sử dụng ngân sách hiệu quả không được thực hiện.</div>
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Bằng cách phân tích dữ liệu chi tiêu và mua lại của nhà tiếp thị, một nhà khoa học dữ liệu có thể xây dựng mô hình chi tiêu có thể giúp sử dụng ngân sách tốt hơn. Mô hình có thể giúp các nhà tiếp thị phân phối ngân sách của họ trên các vị trí, kênh, phương tiện và chiến dịch để tối ưu hóa cho các số liệu chính của họ.</div>
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<b>2. Tiếp thị đúng đối tượng (Marketing to the Right Audience)</b></div>
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Nói chung, các chiến dịch tiếp thị được phân phối rộng rãi không phân biệt vị trí và đối tượng (mass targeting). Kết quả là, có nhiều cơ hội cao cho các nhà tiếp thị để vượt quá ngân sách của họ. Họ cũng có thể không đạt được bất kỳ mục tiêu và mục tiêu doanh thu nào.</div>
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Tuy nhiên, nếu họ sử dụng khoa học dữ liệu để phân tích dữ liệu của họ một cách chính xác, họ sẽ có thể hiểu vị trí và nhân khẩu học nào mang lại cho họ ROI cao nhất.</div>
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<b>3. Xác định các kênh phù hợp (Identifying the Right Channels)</b></div>
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Khoa học dữ liệu có thể được sử dụng để xác định kênh nào đang mang lại lực nâng thích hợp cho nhà tiếp thị. Sử dụng mô hình chuỗi thời gian, một nhà khoa học dữ liệu có thể so sánh và xác định các loại thang máy nhìn thấy trong các kênh khác nhau. Điều này có thể rất có lợi vì nó cho nhà tiếp thị biết chính xác kênh và phương tiện nào đang mang lại lợi nhuận phù hợp.</div>
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<b>4. Xây dựng chiến lược tiếp thị từ khách hàng (Matching Marketing Strategies with Customers)</b></div>
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Để có được giá trị tối đa từ các chiến lược tiếp thị của họ, các nhà tiếp thị cần kết hợp chúng với đúng khách hàng. Để làm điều này, các nhà khoa học dữ liệu có thể tạo ra một mô hình giá trị trọn đời của khách hàng có thể phân khúc khách hàng theo hành vi của họ. Các nhà tiếp thị có thể sử dụng mô hình này cho nhiều trường hợp sử dụng. Họ có thể gửi mã giới thiệu và cung cấp hoàn lại tiền cho khách hàng giá trị cao nhất của họ. Họ có thể áp dụng các chiến lược duy trì cho những người dùng có khả năng rời khỏi cơ sở khách hàng của họ, v.v.</div>
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<b>5. Nhắm mục tiêu ở những khách hàng tiềm năng nhất (Lead Targeting)</b></div>
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Các nhà tiếp thị có thể sử dụng khoa học dữ liệu để nhắm khách hàng mục tiêu ở thị trường niche và biết tất cả về hành vi và ý định trực tuyến của họ. Bằng cách xem xét dữ liệu lịch sử, các nhà tiếp thị có thể xác định các yêu cầu kinh doanh của họ và loại nhãn hiệu mà họ đã liên kết trong năm qua.</div>
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<b>6. Chấm điểm khách hàng theo hành vi tương tác (Advanced Lead Scoring)</b></div>
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Mỗi khách hàng tiềm năng mà một nhà tiếp thị mua sắm không chuyển đổi thành khách hàng. Nếu nhà tiếp thị có thể phân chia chính xác khách hàng theo sở thích của họ, điều đó sẽ làm tăng hiệu suất của bộ phận bán hàng, và cuối cùng là doanh thu.</div>
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Khoa học dữ liệu cho phép các nhà tiếp thị tạo ra một hệ thống chấm điểm để dự đoán giá trị khách hàng (predictive lead scoring system). Hệ thống này là một thuật toán có khả năng tính toán xác suất chuyển đổi và phân đoạn danh sách khách hàng tiềm năng của bạn. Danh sách này có thể được phân loại thành các mục sau: khách hàng háo hức, khách hàng tiềm năng tò mò và khách hàng không quan tâm.</div>
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<b>7. Tối ưu mô hình khách hàng lý tưởng Personas (Customer Personas and Profiling)</b></div>
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Trong khi tiếp thị một sản phẩm / dịch vụ, các nhà tiếp thị nhìn vào việc tạo ra khách hàng. Họ liên tục xây dựng danh sách cụ thể về triển vọng để nhắm mục tiêu. Với khoa học dữ liệu, họ có thể quyết định chính xác những diện mạo nào cần được nhắm mục tiêu. Họ có thể tìm ra số lượng personas và loại đặc điểm họ cần để tạo cơ sở khách hàng của họ.</div>
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<b>8. Sáng tạo chiến lược nội dung (Content Strategy Creation)</b></div>
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Các nhà tiếp thị luôn phải cung cấp nội dung có liên quan và có giá trị để thu hút khách hàng của họ. Khoa học dữ liệu có thể giúp họ kéo dữ liệu đối tượng sẽ lần lượt giúp tạo ra nội dung tốt nhất cho mọi khách hàng. Ví dụ: nếu một khách hàng đến qua Google bằng cách tìm kiếm một từ khóa nhất định, nhà tiếp thị sẽ biết sử dụng từ khóa đó nhiều hơn trong nội dung của họ.</div>
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<b>8. Phân tích trải nghiệm và tâm lý khách hàng (Sentiment Analysis)</b></div>
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Các nhà tiếp thị có thể sử dụng khoa học dữ liệu để phân tích tình cảm. Điều này có nghĩa là họ có thể đạt được những hiểu biết tốt hơn về niềm tin, ý kiến và thái độ của khách hàng. Họ cũng có thể theo dõi cách khách hàng phản ứng với các chiến dịch tiếp thị và liệu họ có tham gia vào hoạt động kinh doanh hay không.</div>
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<b>9. Phát triển sản phẩm (Product Development)</b></div>
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Khoa học dữ liệu có thể giúp các nhà tiếp thị thu thập, tổng hợp và tổng hợp dữ liệu trên các sản phẩm của họ cho một số nhân khẩu học khác nhau. Dựa trên những hiểu biết được cung cấp bởi dữ liệu này, họ có thể phát triển sản phẩm và tạo các chiến dịch tiếp thị được nhắm mục tiêu cao theo nhân khẩu học dự định của họ.</div>
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<b>10. Chiến lược giá (Pricing Strategy)</b></div>
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Khoa học dữ liệu có thể giúp các nhà tiếp thị khi cải thiện chiến lược giá của họ. Bằng cách tập trung vào các yếu tố như sở thích của khách hàng cá nhân, lịch sử mua hàng trong quá khứ và tình hình kinh tế, các nhà tiếp thị có thể xác định chính xác điều gì thúc đẩy giá và ý định mua hàng của khách hàng cho từng phân khúc sản phẩm.</div>
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<b>11. Truyền thông sáng tạo đến khách hàng (Customer Communication)</b></div>
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Bằng cách phân tích dữ liệu chính xác, các nhà tiếp thị có thể xác định thời điểm thích hợp để giao tiếp với khách hàng và khách hàng tiềm năng của họ. Ví dụ, họ có thể hiểu rằng một khách hàng đọc và trả lời email nhưng họ rất dễ tiếp nhận trên SMS. Những hiểu biết như vậy có thể giúp các nhà tiếp thị hiểu đúng thời điểm và kênh để giao tiếp.</div>
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<b>12. Tiếp thị tương tác thời gian thực (Real-Time Interaction Marketing)</b></div>
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Khoa học dữ liệu có thể tạo ra thông tin về các sự kiện thời gian thực và cho phép các nhà tiếp thị khai thác các tình huống đó để nhắm mục tiêu khách hàng. Ví dụ, các nhà tiếp thị của một công ty khách sạn có thể sử dụng khoa học dữ liệu trong thời gian thực để xác định khách du lịch có chuyến bay bị hoãn. Sau đó, họ có thể nhắm mục tiêu cho họ bằng cách gửi chiến dịch quảng cáo trực tiếp đến thiết bị di động của họ.<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://miro.medium.com/max/1400/1*--HwGOSNS9TkKeeuIFGiNg.png" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="342" data-original-width="800" height="170" src="https://miro.medium.com/max/1400/1*--HwGOSNS9TkKeeuIFGiNg.png" width="400" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><span style="font-size: small;"><i>Quy trình tổng quát từ Data Science đến Machine Learning và ứng dụng Smart Logistics</i></span></td></tr>
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<b>13. Cải thiện trải nghiệm khách hàng từ dữ liệu phản hồi (Improving Customer Experience)</b></div>
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Cung cấp trải nghiệm khách hàng phong phú luôn là một yếu tố quan trọng để đạt được thành công tiếp thị. Với khoa học dữ liệu, các nhà tiếp thị có thể thu thập các mẫu hành vi người dùng sẽ dự đoán ai có thể muốn hoặc cần các sản phẩm cụ thể. Điều này cho phép họ tiếp thị hiệu quả và cung cấp cho khách hàng những trải nghiệm phong phú.</div>
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<b>14. Lòng trung thành của khách hàng (Customer Loyalty)</b></div>
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Khách hàng trung thành là những người giúp duy trì dòng tiền (cash flow) trong một doanh nghiệp. Họ ít tốn kém hơn so với việc tìm kiếm khách hàng mới. Khoa học dữ liệu có thể giúp các nhà tiếp thị cải thiện tiếp thị cho khách hàng hiện tại và do đó thúc đẩy lòng trung thành của họ. Ví dụ: Target đã sử dụng khoa học dữ liệu để có được hồ sơ của phụ nữ mang thai dựa trên giao dịch mua trước khi mang thai. Công ty sau đó nhắm mục tiêu những khách hàng này với lời đề nghị sản phẩm trong thời gian mang thai của họ. Chiến lược tiếp thị này hóa ra là một thành công lớn về mặt mua hàng và lòng trung thành cho công ty.</div>
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<b>15. Tiếp thị truyền thông xã hội (Social Media Marketing)</b></div>
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Ngày nay, khách hàng rất tích cực trên các trang truyền thông xã hội như Facebook, LinkedIn và Twitter. Các nhà tiếp thị có thể sử dụng khoa học dữ liệu để xem khách hàng tiềm năng nào đang khám phá trang truyền thông xã hội của họ, nội dung họ đã nhấp và hơn thế nữa. Với những hiểu biết như vậy, họ có thể xây dựng một chiến lược tương tác truyền thông xã hội phù hợp.</div>
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<b>16. Nhóm cộng đồng (Community Groupings)</b></div>
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Khoa học dữ liệu có thể được sử dụng để nhắm mục tiêu các nhóm phương tiện truyền thông xã hội cụ thể để truy cập phản hồi của khách hàng. Điều này được thực hiện bằng cách giúp các nhà tiếp thị xác định các chủ đề được thảo luận thường xuyên nhất dựa trên tần suất từ khóa.</div>
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<b>17. Hiểu biết sâu sắc các từ khoá mà khách hàng thường tìm kiếm (Going Beyond Word Clouds)</b></div>
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Để phân tích các cuộc trò chuyện xã hội, các nhà tiếp thị luôn dựa vào các đám mây từ khoá. Tuy nhiên, các đám mây từ khoá rất hữu ích khi có mức độ hoạt động xã hội cao. Nếu mức độ hoạt động xã hội ít hơn, các nhà tiếp thị thường kết thúc bằng cách sử dụng các từ khóa không liên quan. Với khoa học dữ liệu và thuật toán xử lý ngôn ngữ tự nhiên, chúng có thể vượt ra khỏi đám mây từ khoá bằng cách bối cảnh hóa việc sử dụng từ và cung cấp những hiểu biết có ý nghĩa.</div>
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<b>18. Tối ưu tỉ lệ chuyển đổi quảng cáo</b></div>
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Các nhà tiếp thị có thể sử dụng khoa học dữ liệu để nhắm mục tiêu quảng cáo cụ thể đến khách hàng và đo lường số lần nhấp và kết quả của các chiến dịch. Nó có thể đảm bảo rằng đúng người đang xem quảng cáo biểu ngữ và cải thiện cơ hội được click.</div>
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<b>19. Chiến dịch email marketing</b> </div>
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Khoa học dữ liệu có thể được sử dụng để tìm ra email nào thu hút khách hàng nào. Các email này thường được đọc như thế nào, khi nào gửi chúng ra, loại nội dung nào cộng hưởng với khách hàng, v.v ... Những hiểu biết như vậy cho phép các nhà tiếp thị gửi các chiến dịch email theo ngữ cảnh và nhắm mục tiêu khách hàng với các ưu đãi phù hợp để cá nhân hoá thông tin (Personalization)</div>
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<b>20. Nền tảng tiếp thị kỹ thuật số</b></div>
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Nền tảng tiếp thị kỹ thuật số phát triển mạnh về dữ liệu. Các nhà tiếp thị có thể thu thập những hiểu biết tốt hơn bằng cách cung cấp cho các nền tảng này dữ liệu chi tiết. Khoa học dữ liệu có thể cải thiện các nền tảng tiếp thị kỹ thuật số bằng cách cung cấp dữ liệu phù hợp và từ đó cho phép các nhà tiếp thị xác định những gì họ phải làm để đạt được mục tiêu tiếp thị của họ.<br />
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<div class="separator" style="clear: both; text-align: center;">
<a href="https://cdn.chiefmartec.com/wp-content/uploads/2018/03/marketing_ops.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="351" data-original-width="800" height="280" src="https://cdn.chiefmartec.com/wp-content/uploads/2018/03/marketing_ops.png" width="640" /></a></div>
<blockquote class="tr_bq">
<i>Để có tiếp cận kiến thức <b>Data Science</b> chuyên sâu và các công nghệ <b>Marketing Analytics</b>, bạn hãy cập nhật thêm tại fanpage sau<b>: </b></i> </blockquote>
<blockquote class="tr_bq">
<i><a href="https://www.facebook.com/USPA.tech/" style="font-weight: bold;">https://www.facebook.com/USPA.tech/</a></i></blockquote>
<br /></div>
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Dịch từ:</div>
<div>
<a href="https://towardsdatascience.com/20-practical-ways-to-implement-data-science-in-marketing-e10da4a6d0b2" target="_blank">https://towardsdatascience.com/20-practical-ways-to-implement-data-science-in-marketing-e10da4a6d0b2</a></div>
Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-29773190372766086532020-06-28T16:46:00.002+07:002020-06-28T16:46:50.961+07:00Data collection, processing & organization with USPA framework<div class="separator" style="clear: both; text-align: center;">
<a href="https://image.slidesharecdn.com/datacollectionprocessingorganizationwithuspaframework-200628093924/95/data-collection-processing-organization-with-uspa-framework-1-1024.jpg?cb=1593337281" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="450" data-original-width="800" height="112" src="https://image.slidesharecdn.com/datacollectionprocessingorganizationwithuspaframework-200628093924/95/data-collection-processing-organization-with-uspa-framework-1-1024.jpg?cb=1593337281" width="200" /></a></div>
<div dir="ltr" style="line-height: 1.2; margin-bottom: 0pt; margin-top: 0pt;">
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<div dir="ltr" style="line-height: 1.2; margin-bottom: 0pt; margin-top: 0pt;">
<span style="background-color: transparent; color: black; font-family: "arial"; font-size: 11pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre;">1) How to think in the age of Dataism with USPA framework ?</span></div>
<div dir="ltr" style="line-height: 1.2; margin-bottom: 0pt; margin-top: 0pt;">
<span style="background-color: transparent; color: black; font-family: "arial"; font-size: 11pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre;">2) How to collect customer data </span></div>
<div dir="ltr" style="line-height: 1.2; margin-bottom: 0pt; margin-top: 0pt;">
<span style="background-color: transparent; color: black; font-family: "arial"; font-size: 11pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre;">3) Data Segmentation Processing for flexibility and scalability </span></div>
<div dir="ltr" style="line-height: 1.2; margin-bottom: 0pt; margin-top: 0pt;">
<span style="background-color: transparent; color: black; font-family: "arial"; font-size: 11pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre;">4) Data Organization for personalization and business activation </span></div>
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<span style="background-color: transparent; color: black; font-family: "arial"; font-size: 11pt; font-style: normal; font-variant: normal; font-weight: 400; text-decoration: none; vertical-align: baseline; white-space: pre;"><br /></span></div>
<iframe allowfullscreen="true" frameborder="0" height="420" mozallowfullscreen="true" src="https://docs.google.com/presentation/d/e/2PACX-1vSCVoFhQfaDN__fRBL95mmM5gXCICqklgpTiEv_95mtNiwDV_wiJIxom5o1DrNdumRc2vzu5HxttPdC/embed?start=false&loop=false&delayms=3000" style="width: 96%;" webkitallowfullscreen="true"></iframe>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-22784854642388083492020-06-24T20:08:00.003+07:002020-06-24T20:09:24.699+07:00Smart Retail O2O Model (4 6 8 Growth Hacking Model)<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhV7VLV8-DqDRdfwMpbvVQPiQycu0iatAjzaEGvZ2_h7kdptlC0IGtu0krqTXRXaUeubW9iA-10rgPQ-vuPW3HmF5DZ-ssvFSM6aONnJ-q2aPd89yU9_NfO8q0vzN0veAn5rABwLc7CBxc/s1600/Smart+Retail+O2O+Model+%25284+6+8+Growth+Hacking+Model%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"> <img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhV7VLV8-DqDRdfwMpbvVQPiQycu0iatAjzaEGvZ2_h7kdptlC0IGtu0krqTXRXaUeubW9iA-10rgPQ-vuPW3HmF5DZ-ssvFSM6aONnJ-q2aPd89yU9_NfO8q0vzN0veAn5rABwLc7CBxc/s1600/Smart+Retail+O2O+Model+%25284+6+8+Growth+Hacking+Model%2529.png" style="width: 96%;" /></a></div>
<blockquote class="tr_bq">
Các công ty / tập đoàn kinh doanh trong lĩnh vực bán lẻ sẽ phải "thích nghi" như thế nào trong một nền kinh tế suy thoái <b>#Recession</b> ?</blockquote>
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Mô hình <b>Smart Retail O2O</b> được đề xuất như framework để mọi người tham khảo. Trọng tâm của mô hình là tổ chức quản lý dữ liệu khách hàng ngành Retail có tính hệ thống hơn <b>#RightData</b>, sử dụng công nghệ thông minh <b>#RightTech</b> với quy trình tối ưu cho từng nhóm segment khách hàng <b>#RightProcess</b>Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-88857637690695189052020-06-11T23:32:00.004+07:002020-06-11T23:32:53.311+07:00Top Four Retail Analytics Trends of 2020<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjOS_ZOIyPpPJMy11WMDktOLPLUqBYCyv3SdcaGCqWn6I_w_AWKNNcLmtZRM58qa1ZaWyUiuTjESD9nfnPtQDGEhpk5uCHq63KnBJ9IgQokZ3CjaknnGvF5o1OC75DJd6DKHlN8KVzuINk/s1600/retail_analytics_trends_2020_%25283%2529.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="900" data-original-width="1600" height="360" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjOS_ZOIyPpPJMy11WMDktOLPLUqBYCyv3SdcaGCqWn6I_w_AWKNNcLmtZRM58qa1ZaWyUiuTjESD9nfnPtQDGEhpk5uCHq63KnBJ9IgQokZ3CjaknnGvF5o1OC75DJd6DKHlN8KVzuINk/s1600/retail_analytics_trends_2020_%25283%2529.jpg" width="640" /></a></div>
<blockquote class="tr_bq">
The adoption of retail analytics solutions is increasing rapidly as more retailers worldwide are realizing significant returns from using BI and analytics platforms.</blockquote>
<div style="background-color: #fefefe; color: #444444; font-family: "Helvetica Neue", Helvetica, Arial, "Lucida Grande", sans-serif; font-size: 14px; margin-bottom: 1.5em;">
Retail analytics trends of 2020 will help the retail business to adopt an agile and cohesive data management approach and devise new marketing strategies to drive better business outcomes. Retail data analytics is going to change the retail business scenario dramatically in 2020. Here are the top four retail analytics trends to watch out for in 2020:</div>
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<li style="margin: 0px 0px 5px;"><b>Omnichannel experience: </b>When it comes to offering splendid customer experience, retail businesses need to bridge the gap between in-store and online shopping platforms. Retail data analytics solutions are helping cashiers and customers to check the availability of stock and make selections online. Currently, the customer-centric models are helping retail businesses to integrate online and offline platforms to provide an omnichannel experience to customers.</li>
<li style="margin: 0px 0px 5px;"><b>Personalization: </b>Personalization is the major retail analytics trend of 2020. Retail businesses are focusing on retaining customers through various activities like interacting models and recommending items. Such activities help companies to improve their marketing strategies and cut down on marketing spend while providing personalized services to customers.</li>
<li style="margin: 0px 0px 5px;"><b>Predictive Analytics: </b>Currently every retailer is leveraging predictive analytics to interpret and analyze historical data and make predictions. Hence it is the hottest trend of retail data analytics. Predictive analytics enables companies to fetch data related weather patterns and local events that affect the business.</li>
<li style="margin: 0px 0px 5px;"><b>Dynamic pricing models: </b>Dynamic pricing is one of the most important retail analytics trends of 2020. Price elasticity helps in determining product prices based on current market demands. This can further help in increasing demand and enhancing customer satisfaction rates.</li>
</ol>
Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-13284048911828109752020-06-09T14:22:00.002+07:002020-06-09T14:22:41.242+07:00‘Learning is an experience. Everything else is just information’ – Albert Einstein<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSDm6Vq6UHUrCkyfSszWxQjXaI1TRHbSgEM4uRJsDF95GCZstMNrGHahu5_SnAYVAOpe68FZta9vTFawaA5bUZQfpIo1JAya2BpsoJBGkgpHLqwSzIqIz_EuhIjtHW90ne-5rU5Cx-Vyg/s1600/learningexperience.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="600" data-original-width="1200" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSDm6Vq6UHUrCkyfSszWxQjXaI1TRHbSgEM4uRJsDF95GCZstMNrGHahu5_SnAYVAOpe68FZta9vTFawaA5bUZQfpIo1JAya2BpsoJBGkgpHLqwSzIqIz_EuhIjtHW90ne-5rU5Cx-Vyg/s640/learningexperience.jpg" width="640" /></a></div>
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Ever since I read this powerful statement by a German-born theoretical physicist, our super intelligent Mr. Albert Einstein, it has changed my perspective of looking at learning and development process. In such simple words, he has given me wisdom to think about making my each training an experience than a boring classroom session; an experience which people remember for lifetime, a happy learning experience which is a transition from being someone to being someone better, an experience which has made a difference.<br />
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Let me break down the learning process with a relevant example to decipher this statement and understand it well.<br />
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<span style="font-size: large;">Learning starts with awareness</span><br />
An awareness that I need to learn this in order to move forward or change something in my life is the first step towards learning. Learning without the awareness of its requirement doesn’t really help. For an example, an awareness that I need become a healthy person is the first step towards learning how to become a healthy person.<br />
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<span style="font-size: large;">It needs a lot of assumptions and information</span><br />
Second step towards learning is assuming a lot of things and gathering information basis on those assumption. For an example, the assumption for becoming a healthy person is that I need to look lean and to look lean I need to lose weight. And then all the information is being gathered from reliable sources about how to lose weight. As per your information, you start dieting by starving and depriving from food you like and eating the food which are considered to be healthy.<br />
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<span style="font-size: large;">Expert’s advice</span><br />
An expert’s advice is the third step towards your learning curve where an expert validates whether your assumptions and information are right or wrong. An expert also gives you the right direction to move if you are heading towards something wrong. For above example, an expert here will tell you that being lean is not being healthy, but health is a state of complete physical well-being by eating right amount of food at right time with exercising and balancing all the required nutrients. So your assumption here towards a good health is redirected.<br />
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<span style="font-size: large;">Planning how to learn</span><br />
Now when an expert has directed the learning towards right direction, the fourth step towards learning comes when you ask yourself questions like ‘What does it require out of me?’, ‘what is my role going to be and how do I achieve it?’. For example, now you will plan a schedule for your food intakes and exercises like whether to go to a gym or hire a personal trainer or go and learn yoga or just do normal walk every day.<br />
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<span style="font-size: large;">Experiencing and learning</span><br />
Now when we know the right information and we are sure that we are going in right direction to achieve our objective, the learning process starts with an actual experience of it. For an example, you might realise that your hunger still remains the same, your food intake still remains the same, your taste buds are still being satisfied and you are not compromising on anything you feel like eating but all you are doing is eating smaller portions, at slower pace and at regular intervals in a day and within 6 months you lose fat from your body and experience your first transition of learning curve for becoming healthy.<br />
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Now that’s how learning anything is an experience and rest all is just information.<br />
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At BigDataVietnam.org, we understand this process thoroughly and make sure that all the learning services we provide go through all these steps right from getting aware about what needs to be learnt to learning it through an experience in right direction suggested by our experts of the field.Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-16578930736137659672020-06-06T16:19:00.001+07:002020-06-06T16:21:35.934+07:00Online shopping, demand shaping, and personalized recommendations<div style="text-align: center;">
<iframe allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" frameborder="0" height="400" src="https://www.youtube.com/embed/n3RKsY2H-NE" style="margin: auto; width: 96%;"></iframe><br /></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj1d5wLJ77OEqRH6XDcArMDUqSbMv274HfDxY9LP3kWjZqha1u3q2tmJG0K1P4jQ08LpvTcjidG97jXPanrr3TJX8N9Qz3y8ZuqGsOEYwzRAuQc1XUxIJn4JpSq-uX4Y0YnDm6UxeyjjA8/s1600/Screen+Shot+2020-06-06+at+3.59.01+PM.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="778" data-original-width="1272" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj1d5wLJ77OEqRH6XDcArMDUqSbMv274HfDxY9LP3kWjZqha1u3q2tmJG0K1P4jQ08LpvTcjidG97jXPanrr3TJX8N9Qz3y8ZuqGsOEYwzRAuQc1XUxIJn4JpSq-uX4Y0YnDm6UxeyjjA8/s1600/Screen+Shot+2020-06-06+at+3.59.01+PM.png" style="width: 96%;" /></a></div>
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Paper links:</div>
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<a href="https://www.inf.unibz.it/~ricci/ISR/papers/ieeecomputer.pdf">https://www.inf.unibz.it/~ricci/ISR/papers/ieeecomputer.pdf</a></div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="7707" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
As more and more data is collected every day, we are moving from the age of information to the age of recommendation. One of the key reasons why we need recommendations in modern society, is that now people have too much options to choose from. This is possible due to the prevalence of the internet. In the past, people use to shop in a physical store, the availability of options were limited and depended on the size of the store, availability of product and marketing techniques. For instance, the number of movies that can be placed in a store depends on the size of that store. By contrast, nowadays, the internet allows people to access abundant resources online. Netflix, for example, has a huge collection of movies. . Although the amount of available information increased, a new problem arose as people had a hard time selecting the items they actually want to see. This is where the recommender system comes in.</div>
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A recommender system refers to a system that is capable of predicting the future preference of a set of items for a user. It is a subclass of information filtering system that seeks to predict the rating or preference a user would give to a particular item. These systems are utilized enormously across multiple industries. Recommender systems are most commonly used as playlist generators for video and music services like Netflix, YouTube and Spotify, or product recommenders for services such as Amazon, or content recommenders for social media platforms such as Facebook and Twitter. A huge amount of research and wealth is invested by industries to find out techniques to get great recommendation and improve user experience.</div>
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This article will give you a basic understanding of a typical way for building a recommender system, Collaborative Filtering. We will understand and implement Collaborative Filtering together using Apache Spark with Scala programming Language. Since this is going to be a deep dive into Apache Spark’s and Scala internals, I would expect you to have some understanding about both. Although I’ve tried to keep the entry level for this article pretty low, you might not be able to understand everything if you’re not familiar with the general workings of it. Proceed further with that in mind.</div>
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Collaborative Filtering</h1>
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Multiple researcher in different industries use multiple approaches to design their recommendation system. Traditionally, there are two methods to construct a recommender system:</div>
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<span class="jr la" style="box-sizing: inherit; font-weight: 700;">1) Content-based recommendation</span></div>
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<span class="jr la" style="box-sizing: inherit; font-weight: 700;">2) Collaborative Filtering</span></div>
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First one analyses the nature of each item and aims to find the insights of the data to identify the user preferences. Collaborative Filtering, one the other hand, does not require any information about the items or the user themselves. It recommends the item based on user past experience and behavior. The key idea behind Collaborative Filtering is that similar users share similar interest, people with similar interest tends to like similar items. Hence those items are recommended to similar set of users. For example, if a person A has same opinion as a person B on an issue. Then A is more likely to have B’s opinion on different issue.</div>
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Talking in a Mathematical term, assume there are x users and y items, we use a matrix with size x*y to denote the past behavior of users. Each cell in the matrix represents the associated opinion that a user holds. For instance, Matrix[i, j] denotes how user ‘i’ likes item ‘j’. Such matrix is called utility matrix. Collaborative Filtering is like filling the blank (cell) in the utility matrix that a user has not seen/rated before based on the similarity between users or items.</div>
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As mentioned above, Collaborative Filtering (CF) is a mean of recommendation based on user’s past behavior. There are two categories of CF:</div>
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· <span class="jr la" style="box-sizing: inherit; font-weight: 700;">User-based</span>: measure the similarity between target users and other users</div>
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· <span class="jr la" style="box-sizing: inherit; font-weight: 700;">Item-based</span>: measure the similarity between the items that target users rates/ interacts with and other items</div>
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<span class="ay" style="box-sizing: inherit; font-weight: inherit;">Use Case</span></h1>
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For the sake of our use-case, I will explain Item-based Collaborative Filtering but the working is almost same for user-based Collaborative Filtering. We know that we need to find the similarity between the items in order to recommend it to similar users. In this use case, we aim to recommend movies to our customers. In order to do that we will target movie ratings as a domain to find similarity between two movies. You can download the required movie ratings <a class="ch il lc ld le lf" href="https://grouplens.org/datasets/movielens/" rel="noopener nofollow" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank"><span class="jr la" style="box-sizing: inherit; font-weight: 700;"><em class="lg" style="box-sizing: inherit;">dataset</em></span></a><span class="jr la" style="box-sizing: inherit; font-weight: 700;">. </span>This dataset contains two csv’s movies.csv and ratings.csv which looks like below.</div>
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We proceed with the assumption that if a user A has watch movie ‘i’ and rated it as good, then he/she with also like movies with similar ratings overall. But how do we measure similarity? <span class="jr la" style="box-sizing: inherit; font-weight: 700;">Cosine similarity</span> is a measure of <span class="jr la" style="box-sizing: inherit; font-weight: 700;">similarity</span> between two non-zero vectors of an inner product space that measures the <span class="jr la" style="box-sizing: inherit; font-weight: 700;">cosine</span> of the angle between them.</div>
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<img class="s t u eq ai jl jm ao ve" height="403" role="presentation" src="https://miro.medium.com/max/60/1*QyQAqT7DLrPvkS4TK2RYVA.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 403px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 624px;" width="624" /></div>
<img class="fd tu s t u eq ai jo" height="403" role="presentation" sizes="624px" src="https://miro.medium.com/max/1248/1*QyQAqT7DLrPvkS4TK2RYVA.png" srcset="https://miro.medium.com/max/552/1*QyQAqT7DLrPvkS4TK2RYVA.png 276w, https://miro.medium.com/max/1104/1*QyQAqT7DLrPvkS4TK2RYVA.png 552w, https://miro.medium.com/max/1248/1*QyQAqT7DLrPvkS4TK2RYVA.png 624w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 403px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 624px;" width="624" /></div>
</div>
</div>
</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="f9ca" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
As mentioned earlier we will construct a User Ratings vs Movies utility matrix. Say for example, we have x users and y movies. Each cell represent the associated opinion that a user holds about that particular movie. For example M[i,j] represent the opinion of ‘i’th user for ‘j’th movie.</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="df55" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
Hence for this use case, we gather ratings of multiple users for movies A and B and follow following steps:</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="6465" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
1) Consider two movies A and B out of the utility graph.</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="eaca" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
2) For each movie form two vector of the rating score for multiple user.</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="2bd2" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
3) From above two vectors, calculate cosine similarity score.</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="b57e" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
4) If score is above the pre-determined threshold score than those two movies are similar.</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="772e" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
5) Now, we can recommend a user who have watch movie A, that he/she can also watch movie B.</div>
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Apache Spark</h2>
<div class="jp kd fs bk jr b js mc ke ju md kf jw me kg jy mf kh ka mg ki kc gq" data-selectable-paragraph="" id="caad" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 0.86em; word-break: break-word;">
Apache Spark is a highly developed engine for data processing on large scale over thousands of compute engines in parallel. This allows maximizing processor capability over these compute engines. Spark has the capability to handle multiple data processing tasks. Hence we use spark parallel processing in order to achieve our use case.</div>
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<span class="ay" style="box-sizing: inherit; font-weight: inherit;">Scala</span></h2>
<div class="jp kd fs bk jr b js mc ke ju md kf jw me kg jy mf kh ka mg ki kc gq" data-selectable-paragraph="" id="ae28" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 0.86em; word-break: break-word;">
<span class="jr la" style="box-sizing: inherit; font-weight: 700;">Scala</span> helps to dig deep into the <span class="jr la" style="box-sizing: inherit; font-weight: 700;">Spark’s</span> source code that aids developers to easily access and implement new features of <span class="jr la" style="box-sizing: inherit; font-weight: 700;">Spark</span>. Developers can get object oriented concepts very easily. By using <span class="jr la" style="box-sizing: inherit; font-weight: 700;">Scala</span> language, a perfect balance is maintained between productivity and performance. Spark is built on the top of Scala programming language, hence it offers maximum speed with it.</div>
<h1 class="ko kp fs bk bj fp gz kq hb kr ks kt ku kv kw kx ky" data-selectable-paragraph="" id="a42e" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-sans-serif-font, "Lucida Grande", "Lucida Sans Unicode", "Lucida Sans", Geneva, Arial, sans-serif; font-size: 34px; letter-spacing: -0.022em; line-height: 1.12; margin: 1.95em 0px -0.28em;">
<span class="ay" style="box-sizing: inherit; font-weight: inherit;">Code Working</span></h1>
<div class="jp kd fs bk jr b js mc ke ju md kf jw me kg jy mf kh ka mg ki kc gq" data-selectable-paragraph="" id="95d7" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 0.86em; word-break: break-word;">
In order to get maximum understanding of collaborative filtering, I haven’t used any pre-defined library to implement our use case. Code in scala is pretty straight forward and completely based on the steps we discussed above. There are few transformation and structuring of data involved before we calculate similarity between movies. All the functions defined and steps involved in the code is explained as follows:</div>
<ol class="" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; list-style: none none; margin: 0px; padding: 0px;">
<li class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc mh mi mj" data-selectable-paragraph="" id="beef" style="box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; list-style-type: decimal; margin-bottom: -0.46em; margin-left: 30px; margin-top: 2em; padding-left: 0px;">Construct utility matrix by Mapping input RDD with userId, ratings and movieId in following tuple `(userId, (movieID, rating))`.</li>
</ol>
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<br />
<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl mk" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 348px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="ml jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 132px;">
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<img class="s t u eq ai jl jm ao ve" height="132" role="presentation" src="https://miro.medium.com/max/60/1*uwNRguf_NTHxnmrWltg6rw.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 132px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 348px;" width="348" /></div>
<img class="fd tu s t u eq ai jo" height="132" role="presentation" sizes="348px" src="https://miro.medium.com/max/696/1*uwNRguf_NTHxnmrWltg6rw.png" srcset="https://miro.medium.com/max/552/1*uwNRguf_NTHxnmrWltg6rw.png 276w, https://miro.medium.com/max/696/1*uwNRguf_NTHxnmrWltg6rw.png 348w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 132px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 348px;" width="348" /></div>
</div>
</div>
</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="04e0" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
2) Find every movie pair rated by same user, we are achieving this by using a “self-join” operation. At this point we have data in following format</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="d469" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
`(userId, [(movieId, rating), (movieId, Rating), …])`.</div>
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<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl mm" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 453px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="mn jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 123px;">
<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 123px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 453px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="123" role="presentation" src="https://miro.medium.com/max/60/1*XFVtHyygFOtK_dhwHEd8fg.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 123px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 453px;" width="453" /></div>
<img class="fd tu s t u eq ai jo" height="123" role="presentation" sizes="453px" src="https://miro.medium.com/max/906/1*XFVtHyygFOtK_dhwHEd8fg.png" srcset="https://miro.medium.com/max/552/1*XFVtHyygFOtK_dhwHEd8fg.png 276w, https://miro.medium.com/max/906/1*XFVtHyygFOtK_dhwHEd8fg.png 453w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 123px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 453px;" width="453" /></div>
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</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="580f" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
3) Filter out duplicate pairs with same movieId’s.</div>
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<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl mo" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 452px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="mp jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 143px;">
<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 143px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 452px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="143" role="presentation" src="https://miro.medium.com/max/60/1*2PK_Km1WPo367c__gfCGCQ.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 143px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 452px;" width="452" /></div>
<img class="fd tu s t u eq ai jo" height="143" role="presentation" sizes="452px" src="https://miro.medium.com/max/904/1*2PK_Km1WPo367c__gfCGCQ.png" srcset="https://miro.medium.com/max/552/1*2PK_Km1WPo367c__gfCGCQ.png 276w, https://miro.medium.com/max/904/1*2PK_Km1WPo367c__gfCGCQ.png 452w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 143px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 452px;" width="452" /></div>
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</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="2380" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
4) Out of the array of movie and ratings constructed in step 2, construct new map tuple with key as movie pair and value as respective ratings like as follows</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="3ce6" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
`((movieId1, movieId2), (rating1, rating2))`</div>
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<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl mq" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 486px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="mr jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 175px;">
<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 175px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 486px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="175" role="presentation" src="https://miro.medium.com/max/60/1*HcLzqXTSWCIA0nWmgrCfvw.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 175px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 486px;" width="486" /></div>
<img class="fd tu s t u eq ai jo" height="175" role="presentation" sizes="486px" src="https://miro.medium.com/max/972/1*HcLzqXTSWCIA0nWmgrCfvw.png" srcset="https://miro.medium.com/max/552/1*HcLzqXTSWCIA0nWmgrCfvw.png 276w, https://miro.medium.com/max/972/1*HcLzqXTSWCIA0nWmgrCfvw.png 486w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 175px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 486px;" width="486" /></div>
</div>
</div>
</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="3b48" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
5) Apply groupByKey() to get every rating pair found for each movie pair over the map that we have created in step 4.</div>
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<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl ms" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 610px;">
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<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 87px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 610px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="87" role="presentation" src="https://miro.medium.com/max/60/1*bmOLZ_kMX5EsEsmLCdicTA.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 87px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 610px;" width="610" /></div>
<img class="fd tu s t u eq ai jo" height="87" role="presentation" sizes="610px" src="https://miro.medium.com/max/1220/1*bmOLZ_kMX5EsEsmLCdicTA.png" srcset="https://miro.medium.com/max/552/1*bmOLZ_kMX5EsEsmLCdicTA.png 276w, https://miro.medium.com/max/1104/1*bmOLZ_kMX5EsEsmLCdicTA.png 552w, https://miro.medium.com/max/1220/1*bmOLZ_kMX5EsEsmLCdicTA.png 610w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 87px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 610px;" width="610" /></div>
</div>
</div>
</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="bd2d" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
6) From step 5 construct rating vector for each movie in pair and calculate the cosine similarity score from that vector</div>
<br />
<br />
<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl mu" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 519px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="mv jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 407px;">
<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 407px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 519px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="407" role="presentation" src="https://miro.medium.com/max/60/1*XWaB-g8ryHYO8bL8USe5qg.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 407px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 519px;" width="519" /></div>
<img class="fd tu s t u eq ai jo" height="407" role="presentation" sizes="519px" src="https://miro.medium.com/max/1038/1*XWaB-g8ryHYO8bL8USe5qg.png" srcset="https://miro.medium.com/max/552/1*XWaB-g8ryHYO8bL8USe5qg.png 276w, https://miro.medium.com/max/1038/1*XWaB-g8ryHYO8bL8USe5qg.png 519w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 407px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 519px;" width="519" /></div>
</div>
</div>
</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="3236" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
7) Sort, save or cache the similarity result for each movie pair</div>
<br />
<br />
<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl iy" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 624px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="mw jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 92px;">
<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 92px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 624px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="92" role="presentation" src="https://miro.medium.com/max/60/1*IpwrvROhnMMK_L17ADQWlg.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 92px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 624px;" width="624" /></div>
<img class="fd tu s t u eq ai jo" height="92" role="presentation" sizes="624px" src="https://miro.medium.com/max/1248/1*IpwrvROhnMMK_L17ADQWlg.png" srcset="https://miro.medium.com/max/552/1*IpwrvROhnMMK_L17ADQWlg.png 276w, https://miro.medium.com/max/1104/1*IpwrvROhnMMK_L17ADQWlg.png 552w, https://miro.medium.com/max/1248/1*IpwrvROhnMMK_L17ADQWlg.png 624w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 92px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 624px;" width="624" /></div>
</div>
</div>
</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="8f54" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
8) Set a similarity threshold and user engagement number to improve relevance of results.</div>
<br />
<br />
<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl iy" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 624px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="mx jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 241px;">
<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 241px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 624px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="241" role="presentation" src="https://miro.medium.com/max/60/1*9w7daadycR8E5pW1BahOIg.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 241px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 624px;" width="624" /></div>
<img class="fd tu s t u eq ai jo" height="241" role="presentation" sizes="624px" src="https://miro.medium.com/max/1248/1*9w7daadycR8E5pW1BahOIg.png" srcset="https://miro.medium.com/max/552/1*9w7daadycR8E5pW1BahOIg.png 276w, https://miro.medium.com/max/1104/1*9w7daadycR8E5pW1BahOIg.png 552w, https://miro.medium.com/max/1248/1*9w7daadycR8E5pW1BahOIg.png 624w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 241px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 624px;" width="624" /></div>
</div>
</div>
</figure><br />
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="49b5" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
9) Get input parameter and display results with movies names as recommendation</div>
<div class="jp kd fs bk jr b js jt ke ju jv kf jw jx kg jy jz kh ka kb ki kc gq" data-selectable-paragraph="" id="a26a" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 2em; word-break: break-word;">
You can find full working code <a class="ch il lc ld le lf" href="https://github.com/nihitsaxena95/Collaborative_Filtering_Spark" rel="noopener nofollow" style="-webkit-tap-highlight-color: transparent; background-image: url("data:image/svg+xml; background-position: 0px calc(1em + 1px); background-repeat: repeat-x; background-size: 1px 1px; box-sizing: inherit; http: //www.w3.org/2000/svg\"><line x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\" stroke=\"rgba(0, 0, 0, 0.84)\" /></svg>"); text-decoration-line: none;" target="_blank">here</a>.</div>
<h2 class="lq kp fs bk bj fp lr ls lt lu lv lw lx ly lz ma mb" data-selectable-paragraph="" id="ea06" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-sans-serif-font, "Lucida Grande", "Lucida Sans Unicode", "Lucida Sans", Geneva, Arial, sans-serif; font-size: 26px; letter-spacing: -0.022em; line-height: 1.18; margin: 1.72em 0px -0.31em;">
<span class="ay" style="box-sizing: inherit; font-weight: inherit;">Results</span></h2>
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<br />
<figure class="iz ja jb jc jd je gk gl paragraph-image" style="background-color: white; box-sizing: inherit; clear: both; color: rgba(0, 0, 0, 0.8); font-family: medium-content-sans-serif-font, -apple-system, system-ui, "Segoe UI", Roboto, Oxygen, Ubuntu, Cantarell, "Open Sans", "Helvetica Neue", sans-serif; margin: 56px auto 0px;"><div class="gk gl iy" style="box-sizing: inherit; margin-left: auto; margin-right: auto; max-width: 624px;">
<div class="ji r ce fy" style="background-color: rgba(0, 0, 0, 0.05); box-sizing: inherit; margin: auto; position: relative;">
<div class="my jk r" style="box-sizing: inherit; height: 0px; padding-bottom: 154px;">
<div class="cd jf s t u eq ai bw jg jh" style="box-sizing: inherit; height: 154px; left: 0px; opacity: 0; overflow: hidden; position: absolute; top: 0px; transform: translateZ(0px); transition: opacity 100ms ease 400ms; width: 624px; will-change: transform;">
<img class="s t u eq ai jl jm ao ve" height="154" role="presentation" src="https://miro.medium.com/max/60/1*XvxjqSK_bS_NO-M85Vi60w.png?q=20" style="box-sizing: inherit; filter: blur(20px); height: 154px; left: 0px; position: absolute; top: 0px; transform: scale(1.1); transition: visibility 0ms ease 400ms; vertical-align: middle; visibility: hidden; width: 624px;" width="624" /></div>
<img class="fd tu s t u eq ai jo" height="154" role="presentation" sizes="624px" src="https://miro.medium.com/max/1248/1*XvxjqSK_bS_NO-M85Vi60w.png" srcset="https://miro.medium.com/max/552/1*XvxjqSK_bS_NO-M85Vi60w.png 276w, https://miro.medium.com/max/1104/1*XvxjqSK_bS_NO-M85Vi60w.png 552w, https://miro.medium.com/max/1248/1*XvxjqSK_bS_NO-M85Vi60w.png 624w" style="background: rgb(255, 255, 255); box-sizing: inherit; height: 154px; left: 0px; opacity: 1; position: absolute; top: 0px; transition: opacity 400ms ease 0ms; vertical-align: middle; width: 624px;" width="624" /></div>
</div>
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</figure><br />
<h1 class="ko kp fs bk bj fp gz kq hb kr ks kt ku kv kw kx ky" data-selectable-paragraph="" id="fb77" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-sans-serif-font, "Lucida Grande", "Lucida Sans Unicode", "Lucida Sans", Geneva, Arial, sans-serif; font-size: 34px; letter-spacing: -0.022em; line-height: 1.12; margin: 1.95em 0px -0.28em;">
<span class="ay" style="box-sizing: inherit; font-weight: inherit;">Conclusion</span></h1>
<div class="jp kd fs bk jr b js mc ke ju md kf jw me kg jy mf kh ka mg ki kc gq" data-selectable-paragraph="" id="2caa" style="background-color: white; box-sizing: inherit; color: rgba(0, 0, 0, 0.84); font-family: medium-content-serif-font, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 21px; letter-spacing: -0.003em; line-height: 32px; margin-bottom: -0.46em; margin-top: 0.86em; word-break: break-word;">
We have discussed and implemented Collaborative Filtering using Apache Spark with Scala. This techniques have its own pro’s and con’s. As user behavior changes with time the accuracy of this techniques varies time to time. We can also enhance its accuracy and overcome limitations by some pre-processing based on genres, style and content. I feel Apache Spark is a great tool to implement features like this and can serve in more advance and real time recommendations. If you have reached till here, Congrats! you have implemented your own recommendation engine. I will keep on posting more content on big data and data science. Till then stay tuned and Happy Learning!</div>
<br />Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.comtag:blogger.com,1999:blog-7142677491073595653.post-17123389316164442102020-02-20T11:03:00.002+07:002020-02-20T15:29:35.334+07:00All key posts about Customer Data Platform<div class="separator" style="clear: both; text-align: center;">
<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh8PyWbwQEsfjc6YMelZj5AxRePjyE7S1kFiUSJMFM5H13ZRkUq689lqf3Hf-1Vpc4NPZ_lOtwLU-hY8JEYCtYNzIIyw5wNeWqH7CGZNaW-sYW3MtDhrZKUsPqwZx6aFwjb7C_-UMAJb98/s1600/redpoint-cdp-100771487-orig.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="900" data-original-width="1600" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh8PyWbwQEsfjc6YMelZj5AxRePjyE7S1kFiUSJMFM5H13ZRkUq689lqf3Hf-1Vpc4NPZ_lOtwLU-hY8JEYCtYNzIIyw5wNeWqH7CGZNaW-sYW3MtDhrZKUsPqwZx6aFwjb7C_-UMAJb98/s1600/redpoint-cdp-100771487-orig.jpg" style="width: 96%;" /></a></div>
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<span style="font-size: x-small;">A true customer data platform must integrate data from across functional and channel-specific silos into a single customer view that is accessible in real-time</span></div>
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<span style="font-size: x-small;">Source: <a href="https://www.cio.com/article/3305456/these-3-types-of-customer-data-platforms-are-not-one-in-the-same.html" target="_blank">https://www.cio.com/article/3305456/these-3-types-of-customer-data-platforms-are-not-one-in-the-same.html</a></span></div>
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<br />
What is a Customer Data Platform?<br />
<div>
<a href="https://www.bigdatavietnam.org/2019/06/what-is-customer-data-platform.html">https://www.bigdatavietnam.org/2019/06/what-is-customer-data-platform.html</a></div>
<div>
<br /></div>
<div>
<div>
How to build Unified Experience Platform (CDP & DXP)</div>
</div>
<div>
<a href="https://www.bigdatavietnam.org/2019/09/uspatech-open-source-framework-to-build.html">https://www.bigdatavietnam.org/2019/09/uspatech-open-source-framework-to-build.html</a></div>
<div>
<br /></div>
Customer Data & Experience Platform 101<br />
<div>
<a href="https://www.bigdatavietnam.org/p/digital-marketing-customer-da.html">https://www.bigdatavietnam.org/p/digital-marketing-customer-da.html</a></div>
<div>
<br /></div>
<div>
<div>
Customer Data Platform (CDP) – Introduction and Market Overview</div>
</div>
<div>
<a href="https://www.bigdatavietnam.org/2019/07/customer-data-platform-cdp-introduction.html">https://www.bigdatavietnam.org/2019/07/customer-data-platform-cdp-introduction.html</a></div>
<div>
<br /></div>
<div>
<div>
Marketing Technology Infrastructure for Brands (Big Data and A.I for Marketing)</div>
</div>
<div>
<a href="https://www.bigdatavietnam.org/2019/08/marketing-technology-infrastructure-for.html">https://www.bigdatavietnam.org/2019/08/marketing-technology-infrastructure-for.html</a></div>
<div>
<br /></div>
<div>
<div>
Customer Data Platforms: ứng dụng Big Data để xây dựng cái nhìn 360 độ về Profile của khách hàng</div>
</div>
<div>
<a href="https://www.bigdatavietnam.org/2019/08/customer-data-platforms-how-marketers.html">https://www.bigdatavietnam.org/2019/08/customer-data-platforms-how-marketers.html</a></div>
<div>
<br /></div>
<div>
<div>
Customer Data Platform & E-Commerce</div>
</div>
<div>
<a href="https://www.bigdatavietnam.org/2019/10/from-customer-first-marketing-theory-to.html">https://www.bigdatavietnam.org/2019/10/from-customer-first-marketing-theory-to.html</a></div>
<div>
<br /></div>
<div>
<div>
Unified Technology Platform for Customer 360 Insights in data-driven business</div>
</div>
<div>
<a href="https://www.bigdatavietnam.org/2019/08/customer-data-platform-branding.html">https://www.bigdatavietnam.org/2019/08/customer-data-platform-branding.html</a></div>
<div>
<br />
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjtlS1NupwHVMvbPm4aegX24o71TL7FvG2C1IhPwT0TVBiDA6m2NKaTOUJjVk7IZnE34sQr1cXB5YxU-lPRNfOCNzVpCeO-trgzQ1d0noMZwhIx_50w1bDiJLQloFW4blH9OwgTMyKXw6Q/s1600/The+framework+of+Experience+Economy+4.0+%25281%2529.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="1128" data-original-width="1600" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjtlS1NupwHVMvbPm4aegX24o71TL7FvG2C1IhPwT0TVBiDA6m2NKaTOUJjVk7IZnE34sQr1cXB5YxU-lPRNfOCNzVpCeO-trgzQ1d0noMZwhIx_50w1bDiJLQloFW4blH9OwgTMyKXw6Q/s1600/The+framework+of+Experience+Economy+4.0+%25281%2529.png" style="width: 96%;" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><b><span style="font-size: small;"><i>The final goal of CDP is Unified Experience from all data in the World</i></span></b></td></tr>
</tbody></table>
<br /></div>
Trieuhttp://www.blogger.com/profile/00598846141548337228noreply@blogger.com