{"id":50796,"date":"2023-03-22T07:15:57","date_gmt":"2023-03-22T07:15:57","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/al3391-artificial-intelligence-syllabus-for-aiml-2021-regulation\/"},"modified":"2023-03-22T07:15:57","modified_gmt":"2023-03-22T07:15:57","slug":"al3391-artificial-intelligence-syllabus-for-aiml-2021-regulation","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/al3391-artificial-intelligence-syllabus-for-aiml-2021-regulation\/","title":{"rendered":"AL3391: Artificial Intelligence syllabus for AI&ML 2021 regulation"},"content":{"rendered":"

Artificial Intelligence detailed syllabus for Artificial Intelligence & Machine Learning (AI&ML) for 2021 regulation curriculum has been taken from the Anna University<\/a> official website and presented for the AI&ML students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Artificial Intelligence & Machine Learning 4th Sem scheme and its subjects, do visit AI&ML 4th Sem 2021 regulation scheme<\/a>. The detailed syllabus of artificial intelligence is as follows. <\/p>\n

Artificial Intelligence<\/title><\/p>\n<h4>Course Objectives:<\/h4>\n<h4 id=\"istudy\" style=\"text-align:center\"><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" style=\"color: inherit\" target=\"_blank\" rel=\"noopener\">Download the iStudy App for all syllabus and other updates.<\/a><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px;text-align:center\"><\/a><\/h4>\n<h4>Unit I<\/h4>\n<p> <strong>INTELLIGENT AGENTS 9<\/strong> Introduction to AI – Agents and Environments – concept of rationality – nature of environments -structure of agents. Problem solving agents – search algorithms – uninformed search strategies.<\/p>\n<h4>Unit II<\/h4>\n<h4 id=\"istudy\" style=\"text-align:center\"><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" style=\"color: inherit\" target=\"_blank\" rel=\"noopener\">Download the iStudy App for all syllabus and other updates.<\/a><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px;text-align:center\"><\/a><\/h4>\n<h4>Unit III<\/h4>\n<p> <strong>GAME PLAYING AND CSP 9<\/strong> Game theory – optimal decisions in games – alpha-beta search – monte-carlo tree search -stochastic games – partially observable games. Constraint satisfaction problems – constraint propagation – backtracking search for CSP – local search for CSP – structure of CSP.<\/p>\n<h4>Unit IV<\/h4>\n<h4 id=\"istudy\" style=\"text-align:center\"><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" style=\"color: inherit\" target=\"_blank\" rel=\"noopener\">Download the iStudy App for all syllabus and other updates.<\/a><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px;text-align:center\"><\/a><\/h4>\n<h4>Unit V<\/h4>\n<p> <strong>PROBABILISTIC REASONING 9<\/strong> Acting under uncertainty – Bayesian inference – naive Bayes models. Probabilistic reasoning -Bayesian networks – exact inference in BN – approximate inference in BN – causal networks.<\/p>\n<h4>Course Outcomes:<\/h4>\n<h4 id=\"istudy\" style=\"text-align:center\"><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" style=\"color: inherit\" target=\"_blank\" rel=\"noopener\">Download the iStudy App for all syllabus and other updates.<\/a><br \/><a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy&pcampaignid=pcampaignidMKT-Other-global-all-co-prtnr-py-PartBadge-Mar2515-1\" target=\"_blank\" rel=\"noopener\"><img decoding=\"async\" src=\"https:\/\/play.google.com\/intl\/en_us\/badges\/static\/images\/badges\/en_badge_web_generic.png\" alt=\"Get it on Google Play\" style=\"height:65px;text-align:center\"><\/a><\/h4>\n<h4>Reference Books:<\/h4>\n<ol>\n<li>Dan W. Patterson, Introduction to AI and ES, Pearson Education,2007<\/li>\n<li>Kevin Night, Elaine Rich, and Nair B., Artificial Intelligence, McGraw Hill, 2008<\/li>\n<li>Patrick H. Winston, “Artificial Intelligence”, Third Edition, Pearson Education, 2006<\/li>\n<li>Deepak Khemani, Artificial Intelligence, Tata McGraw Hill Education, 2013.<\/li>\n<li>http:\/\/nptel.ac.in\/<\/li>\n<\/ol>\n<p align=\"justify\">For detailed syllabus of all other subjects of Artificial Intelligence & Machine Learning, 2021 regulation curriculum do visit <a class=\"rank-math-link\" href=\"..\/category\/ai-ml+4th-sem\">AI&ML 4th Sem subject syllabuses for 2021 regulation<\/a>. <\/p>\n<p align=\"justify\">For all Artificial Intelligence & Machine Learning results, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-results\/\">Anna University AI&ML all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial Intelligence detailed syllabus for Artificial Intelligence & Machine Learning (AI&ML) for 2021 regulation curriculum has been taken from the Anna University official website and presented for the AI&ML students. […]<\/p>\n","protected":false},"author":2297,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[47,157],"tags":[],"class_list":["post-50796","post","type-post","status-publish","format-standard","hentry","category-4th-sem","category-aiml"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/50796","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/users\/2297"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=50796"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/50796\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=50796"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=50796"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=50796"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}