{"id":53040,"date":"2023-04-07T07:10:08","date_gmt":"2023-04-07T07:10:08","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/ocs353-data-science-fundamentals-syllabus-for-production-2021-regulation-open-elective-ii\/"},"modified":"2023-04-07T07:10:08","modified_gmt":"2023-04-07T07:10:08","slug":"ocs353-data-science-fundamentals-syllabus-for-production-2021-regulation-open-elective-ii","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/ocs353-data-science-fundamentals-syllabus-for-production-2021-regulation-open-elective-ii\/","title":{"rendered":"OCS353: Data Science Fundamentals syllabus for Production 2021 regulation (Open Elective-II)"},"content":{"rendered":"<p align=\"justify\">Data Science Fundamentals detailed syllabus for Production Engineering (Production) for 2021 regulation curriculum has been taken from the <a class=\"rank-math-link\" href=\"https:\/\/cac.annauniv.edu\/\" style=\"color: inherit\" target=\"_blank\" rel=\"noopener\">Anna Universities<\/a> official website and presented for the Production 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<p align=\"justify\">For Production Engineering 7th Sem scheme and its subjects, do visit <a class=\"rank-math-link\" href=\"..\/production-7th-sem-syllabus-2021-regulation\">Production 7th Sem 2021 regulation scheme<\/a>. For Open Elective-II scheme and its subjects refer to <a class=\"rank-math-link\" href=\"..\/open-elective-ii-syllabus-for-production-2021-regulation\">Production Open Elective-II syllabus scheme<\/a>. The detailed syllabus of data science fundamentals is as follows. <\/p>\n<p>  <title>Data Science Fundamentals<\/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&amp;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 6<\/strong> Data Science: Benefits and uses &#8211; facets of data &#8211; Data Science Process: Overview &#8211; Defining research goals &#8211; Retrieving data &#8211; data preparation &#8211; Exploratory Data analysis &#8211; build the model -presenting findings and building applications &#8211; Data Mining &#8211; Data Warehousing &#8211; Basic statistical descriptions of Data<\/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&amp;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>MACHINE LEARNING 5<\/strong> The modeling process &#8211; Types of machine learning &#8211; Supervised learning &#8211; Unsupervised learning -Semi-supervised learning- Classification, regression &#8211; Clustering &#8211; Outliers and Outlier Analysis<\/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&amp;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>HANDLING LARGE DATA 5<\/strong> Problems &#8211; techniques for handling large volumes of data &#8211; programming tips for dealing with large data sets- Case studies: Predicting malicious URLs, Building a recommender system &#8211; Tools and techniques needed &#8211; Research question &#8211; Data preparation &#8211; Model building &#8211; Presentation and automation.<\/p>\n<h4>Practical Exercises:<\/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&amp;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>Course Outcomes:<\/h4>\n<p>  At the end of this course, the students will be able to:<\/p>\n<ol>\n<li>Gain knowledge on data science process.<\/li>\n<li>Perform data manipulation functions using Numpy and Pandas.<\/li>\n<li>Understand different types of machine learning approaches.<\/li>\n<li>Perform data visualization using tools.<\/li>\n<li>Handle large volumes of data in practical scenarios.<\/li>\n<\/ol>\n<h4>Text Books:<\/h4>\n<ol>\n<li>David Cielen, Arno D. B. Meysman, and Mohamed Ali, Introducing Data Science, Manning Publications, 2016.<\/li>\n<li>Jake VanderPlas, Python Data Science Handbook, OReilly, 2016.<\/li>\n<\/ol>\n<h4>Reference Books:<\/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&amp;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<p align=\"justify\">For detailed syllabus of all the other subjects of Production Engineering 7th Sem, visit <a class=\"rank-math-link\" href=\"..\/category\/production+7th-sem\">Production 7th Sem subject syllabuses for 2021 regulation<\/a>. <\/p>\n<p align=\"justify\">For all Production Engineering results, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-results\/\">Anna University Production all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Science Fundamentals detailed syllabus for Production Engineering (Production) for 2021 regulation curriculum has been taken from the Anna Universities official website and presented for the Production students. For course [&hellip;]<\/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":[63],"tags":[],"class_list":["post-53040","post","type-post","status-publish","format-standard","hentry","category-production"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/53040","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=53040"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/53040\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=53040"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=53040"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=53040"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}