{"id":33063,"date":"2021-05-21T08:09:09","date_gmt":"2021-05-21T08:09:09","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/it5602-data-science-and-analytics-syllabus-for-it-6th-sem-2019-regulation-anna-university\/"},"modified":"2021-05-21T08:09:09","modified_gmt":"2021-05-21T08:09:09","slug":"it5602-data-science-and-analytics-syllabus-for-it-6th-sem-2019-regulation-anna-university","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/it5602-data-science-and-analytics-syllabus-for-it-6th-sem-2019-regulation-anna-university\/","title":{"rendered":"IT5602: Data Science and Analytics Syllabus for IT 6th Sem 2019 Regulation Anna University"},"content":{"rendered":"

Data Science and Analytics detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the IT 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 Information Technology 6th Sem scheme and its subjects, do visit IT 6th Sem 2019 regulation scheme<\/a>. The detailed syllabus of data science and analytics is as follows. <\/p>\n

Data Science and Analytics<\/title><\/p>\n<h4>Course Objective:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><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\"><\/a>. <\/p>\n<h4>Unit I<\/h4>\n<p align=\"justify\">\n <strong>Introduction To Data Science and Big Data<\/strong><br \/>\n Data Science – Fundamentals and Components – Data Scientist – Terminologies Used in Big Data Environments – Types of Digital Data – Classification of Digital Data – Introduction to Big Data – Characteristics of Data – Evolution of Big Data – Big Data Analytics -Classification of Analytics – Top Challenges Facing Big Data – Importance of Big Data Analytics – Data Analytics Tools.<\/p>\n<p><i>Suggested Activities:<\/i>\n <\/p>\n<ul>\n<li>Case studies on big data application domain.<\/li>\n<li>Real world domain specific problems involving big data and listing out the challenges.<\/li>\n<li>Demonstration on data analytics tools.<\/li>\n<\/ul>\n<p><i>Suggested Evaluation Methods:<\/i>\n <\/p>\n<ul>\n<li>Student assignment on case studies related to healthcare, climate change, ecommerce, retail business, manufacturing etc.<\/li>\n<li>Group presentation on big data applications with societal need.<\/li>\n<li>Quizzes on topics like big data terminologies, big data applications, etc.<\/li>\n<\/ul>\n<h4>Unit II<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><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\"><\/a>. <\/p>\n<h4>Unit III<\/h4>\n<p align=\"justify\">\n <strong>Predictive Modeling and Machine Learning<\/strong><br \/>\n Linear Regression – Polynomial Regression – Multivariate Regression – Multi Level Models – Data Warehousing Overview – Bias\/Variance Trade Off – K Fold Cross Validation – Data Cleaning and Normalization – Cleaning Web Log Data – Normalizing Numerical Data – Detecting Outliers – Introduction to Supervised And Unsupervised Learning – Reinforcement Learning – Dealing with Real World Data – Machine Learning Algorithms -Clustering -Python Based Application.<\/p>\n<p><i>Suggested Activities:<\/i>\n <\/p>\n<ul>\n<li>Solve numerical problem solving using linear regression models.<\/li>\n<li>Demonstrate data cleaning using WEKA tool.<\/li>\n<li>Demonstration of data preprocessing and machine learning features in Python.<\/li>\n<\/ul>\n<p><i>Suggested Evaluation Methods:<\/i>\n <\/p>\n<ul>\n<li>Simple lab based activities for machine learning in Python using small benchmark datasets.<\/li>\n<li>Tool based assignments on linear, polynomial and multivariate regression using real world case studies.<\/li>\n<li>Assignment on comparative analysis of two or more data sets using their features.<\/li>\n<\/ul>\n<h4>Unit IV<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><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\"><\/a>. <\/p>\n<h4>Unit V<\/h4>\n<p align=\"justify\">\n <strong>Data Science Using Python<\/strong><br \/>\n Introduction to Essential Data Science Packages: Numpy, Scipy, Jupyter, Statsmodels and Pandas Package – Data Munging: Introduction to Data Munging, Data Pipeline and Machine Learning in Python – Data Visualization Using Matplotlib – Interactive Visualization with Advanced Data Learning Representation in Python.<\/p>\n<p><i>Suggested Activities:<\/i>\n <\/p>\n<ul>\n<li>Demonstration of simple Python scripts using NumPy and SciPy Package.<\/li>\n<li>Demonstration on NumPy arrays and matrix operations.<\/li>\n<li>Simple lab activities on dimensionality reduction and feature selection using Python.<\/li>\n<li>Demonstration of experiments on data visualization using matplotlib functions.<\/li>\n<\/ul>\n<p><i>Suggested Evaluation Methods:<\/i>\n <\/p>\n<ul>\n<li>Mini Project using Python for data analytics with benchmark datasets.<\/li>\n<li>Quiz on data visualization functions.<\/li>\n<\/ul>\n<h4>Course Outcome:<\/h4>\n<p id=\"istudy\" style=\"text-align:center\">For the complete syllabus, results, class timetable, and many other features kindly download the <a class=\"rank-math-link\" href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">iStudy App<\/a><br \/><b> It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b><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\"><\/a>. <\/p>\n<h4>Text Books:<\/h4>\n<p align=\"justify\">\n<ol>\n<li>Frank Pane, “Hands On Data Science and Python Machine Learning”, Packt Publishers, 2017.<\/li>\n<li>Seema Acharya, Subhashini Chellapan, “Big Data and Analytics”, Wiley, 2015.<\/li>\n<\/ol>\n<h4>References:<\/h4>\n<p align=\"justify\">\n<ol>\n<li>Alberto Boschetti, Luca Massaron, “Python Data Science Essentials”, Packt Publications, 2nd Edition, 2016.<\/li>\n<li>DT Editorial Services, Big Data, Black Book, Dream Tech Press, 2015.<\/li>\n<li>Yuxi (Hayden) Liu, “Python Machine Learning”, Packt Publication, 2017.<\/li>\n<\/ol>\n<p align=\"justify\">For detailed syllabus of all other subjects of Information Technology, 2019 regulation curriculum do visit <a class=\"rank-math-link\" href=\"..\/category\/it+6th-sem\">IT 6th Sem subject syllabuses for 2019 regulation<\/a>. <\/p>\n<p align=\"justify\">For all Information Technology results, visit <a class=\"rank-math-link\" href=\"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-results\/\">Anna University IT all semester results<\/a> direct link. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Science and Analytics detailed syllabus for Information Technology (IT) for 2019 regulation curriculum has been taken from the Anna Universities official website and presented for the IT students. For […]<\/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":[49,72],"tags":[],"class_list":["post-33063","post","type-post","status-publish","format-standard","hentry","category-6th-sem","category-it"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/33063","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=33063"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/33063\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=33063"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=33063"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=33063"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}