{"id":50610,"date":"2023-03-22T07:13:26","date_gmt":"2023-03-22T07:13:26","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/ad3491-fundamentals-of-data-science-and-analytics-syllabus-for-aids-2021-regulation\/"},"modified":"2023-03-22T07:13:26","modified_gmt":"2023-03-22T07:13:26","slug":"ad3491-fundamentals-of-data-science-and-analytics-syllabus-for-aids-2021-regulation","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/ad3491-fundamentals-of-data-science-and-analytics-syllabus-for-aids-2021-regulation\/","title":{"rendered":"AD3491: Fundamentals of Data Science and Analytics syllabus for AI&DS 2021 regulation"},"content":{"rendered":"

Fundamentals of Data Science and Analytics detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna University<\/a> official website and presented for the AI&DS 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 & Data Science 4th Sem scheme and its subjects, do visit AI&DS 4th Sem 2021 regulation scheme<\/a>. The detailed syllabus of fundamentals of data science and analytics is as follows. <\/p>\n

Fundamentals of Data Science and Analytics<\/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>INTRODUCTION TO DATA SCIENCE 08<\/strong> Need for data science – benefits and uses – facets of data – data science process – setting the research goal – retrieving data – cleansing, integrating, and transforming data – exploratory data analysis – build the models – presenting and building applications.<\/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>INFERENTIAL STATISTICS 09<\/strong> Populations – samples – random sampling – Sampling distribution- standard error of the mean -Hypothesis testing – z-test – z-test procedure -decision rule – calculations – decisions -interpretations – one-tailed and two-tailed tests – Estimation – point estimate – confidence interval -level of confidence – effect of sample size.<\/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>PREDICTIVE ANALYTICS 09<\/strong> Linear least squares – implementation – goodness of fit – testing a linear model – weighted resampling. Regression using StatsModels – multiple regression – nonlinear relationships – logistic regression – estimating parameters – Time series analysis – moving averages – missing values -serial correlation – autocorrelation. Introduction to survival analysis.<\/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>Text Books:<\/h4>\n<ol>\n<li>David Cielen, Arno D. B. Meysman, and Mohamed Ali, Introducing Data Science, Manning Publications, 2016. (first two chapters for Unit I).<\/li>\n<li>Robert S. Witte and John S. Witte, Statistics, Eleventh Edition, Wiley Publications, 2017.<\/li>\n<li>Jake VanderPlas, Python Data Science Handbook, OReilly, 2016.<\/li>\n<\/ol>\n<h4>Reference Books:<\/h4>\n<ol>\n<li>Allen B. Downey, Think Stats: Exploratory Data Analysis in Python, Green Tea Press, 2014.<\/li>\n<li>Sanjeev J. Wagh, Manisha S. Bhende, Anuradha D. Thakare, Fundamentals of Data Science, CRC Press, 2022.<\/li>\n<li>Chirag Shah, A Hands-On Introduction to Data Science, Cambridge University Press, 2020.<\/li>\n<li>Vineet Raina, Srinath Krishnamurthy, Building an Effective Data Science Practice: A Framework to Bootstrap and Manage a Successful Data Science Practice, Apress, 2021.<\/li>\n<\/ol>\n<p align=\"justify\">For detailed syllabus of all other subjects of Artificial Intelligence & Data Science, 2021 regulation curriculum do visit <a class=\"rank-math-link\" href=\"..\/category\/ai-ds+4th-sem\">AI&DS 4th Sem subject syllabuses for 2021 regulation<\/a>. <\/p>\n<p align=\"justify\">For all Artificial Intelligence & Data Science results, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-results\/\">Anna University AI&DS all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Fundamentals of Data Science and Analytics detailed syllabus for Artificial Intelligence & Data Science (AI&DS) for 2021 regulation curriculum has been taken from the Anna University official website and presented […]<\/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":[47,144],"tags":[],"class_list":["post-50610","post","type-post","status-publish","format-standard","hentry","category-4th-sem","category-aids"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/50610","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=50610"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/50610\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=50610"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=50610"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=50610"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}