{"id":1448,"date":"2026-06-05T20:42:44","date_gmt":"2026-06-06T00:42:44","guid":{"rendered":"https:\/\/resrvoir.com\/?page_id=1448"},"modified":"2026-06-06T00:14:39","modified_gmt":"2026-06-06T04:14:39","slug":"aidl-courses","status":"publish","type":"page","link":"https:\/\/resrvoir.com\/?page_id=1448","title":{"rendered":"AIDL Courses"},"content":{"rendered":"\n<p>I&#8217;ve completed several courses from DeepLearning and Coursera for AIDL using Python.<\/p>\n\n\n\n<p>One of the most interesting topics is Multi-head masked self-attention in Transformers. That&#8217;s got to be one of the most remarkable breakthroughs in Computer Science of our time. Then there&#8217;s back propagation at core of Neural Networks which is optimizing a cost function using derivatives from Calculus. If you think about it, that is really incredible also. IIRC backprop was invented\/discovered in the 1950&#8217;s or so. I wonder what those researchers would think if they were alive today.<\/p>\n\n\n\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\"><div class=\"wp-block-group__inner-container\">\n<h5 class=\"wp-block-heading\">Natural Language Processing with Attention Models<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/39R93C6PG2K3\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/39R93C6PG2K3<\/a><\/p>\n<\/div><\/div>\n\n\n\n<h5 class=\"wp-block-heading\">Natural Language Processing with Sequence Models<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/FJTVCXJ2EZMQ\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/FJTVCXJ2EZMQ<\/a><\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Natural Language Processing with Probabilistic Models<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/NQB2RM5MQR2R\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/NQB2RM5MQR2R<\/a><\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Natural Language Processing with Classification and Vector Spaces<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/CNAT67ZYNBA2\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/CNAT67ZYNBA2<\/a><\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Sequence Models<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/22FN5NM7SZ6Q\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/22FN5NM7SZ6Q<\/a><\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Convolutional Neural Networks<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/BTG9PEYCXT6D\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/BTG9PEYCXT6D<\/a><\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Structuring Machine Learning Projects<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/EMU4U7MVBPK8\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/EMU4U7MVBPK8<\/a><\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/JDNU4ELTQ4Z5\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/JDNU4ELTQ4Z5<\/a><\/p>\n\n\n\n<h5 class=\"wp-block-heading\">Neural Networks and Deep Learning<\/h5>\n\n\n\n<p><a href=\"https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/5ESUBYG4LKYD\">https:\/\/www.coursera.org\/account\/accomplishments\/certificate\/5ESUBYG4LKYD<\/a><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>I&#8217;ve completed several courses from DeepLearning and Coursera for AIDL using Python. One of the most interesting topics is Multi-head masked self-attention in Transformers. That&#8217;s got to be one of the most remarkable breakthroughs in Computer Science of our time. Then there&#8217;s back propagation at core of Neural Networks which is optimizing a cost function [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1442,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/resrvoir.com\/index.php?rest_route=\/wp\/v2\/pages\/1448"}],"collection":[{"href":"https:\/\/resrvoir.com\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/resrvoir.com\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/resrvoir.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/resrvoir.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1448"}],"version-history":[{"count":11,"href":"https:\/\/resrvoir.com\/index.php?rest_route=\/wp\/v2\/pages\/1448\/revisions"}],"predecessor-version":[{"id":1485,"href":"https:\/\/resrvoir.com\/index.php?rest_route=\/wp\/v2\/pages\/1448\/revisions\/1485"}],"up":[{"embeddable":true,"href":"https:\/\/resrvoir.com\/index.php?rest_route=\/wp\/v2\/pages\/1442"}],"wp:attachment":[{"href":"https:\/\/resrvoir.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1448"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}