{"id":379,"date":"2016-11-04T18:12:47","date_gmt":"2016-11-04T18:12:47","guid":{"rendered":"http:\/\/www.inspirenignite.com\/anna-university\/?p=379"},"modified":"2019-07-17T07:18:00","modified_gmt":"2019-07-17T07:18:00","slug":"anna-university-b-tech-it-r13-7th-data-analytics-detailed-syllabus","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/anna-university-b-tech-it-r13-7th-data-analytics-detailed-syllabus\/","title":{"rendered":"Anna University B.Tech IT (R13) 7th Data Analytics Detailed Syllabus"},"content":{"rendered":"<p>Data Analytics Syllabus for B.Tech 7th sem is covered here. This gives the details about credits, number of hours and other details along with reference books for the course.<\/p>\n<p>The detailed syllabus for Data Analytics B.Tech (R13) seventhsem is as follows<\/p>\n<p><strong>OBJECTIVES:<\/strong> The Student should be made to:<\/p>\n<ul>\n<li>Be exposed to big data<\/li>\n<li>Learn the different ways of Data Analysis<\/li>\n<li>Be familiar with data streams<\/li>\n<li>Learn the mining and clustering<\/li>\n<li>Be familiar with the visualization<\/li>\n<\/ul>\n<p><strong>UNIT I : INTRODUCTION TO BIG DATA<\/strong> \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 [8 hours]<br \/>\nIntroduction to Big Data Platform \u2013 Challenges of conventional systems &#8211; Web data \u2013 Evolution of Analytic scalability, analytic processes and tools, Analysis vs reporting &#8211; Modern data analytic tools, Stastical concepts: Sampling distributions, resampling, statistical inference, prediction error.<\/p>\n<p><strong>UNIT II : DATA ANALYSIS<\/strong> \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0[12 hours]<br \/>\nRegression modeling, Multivariate analysis, Bayesian modeling, inference and Bayesian networks, Support vector and kernel methods, Analysis of time series: linear systems analysis, nonlinear dynamics &#8211; Rule induction &#8211; Neural networks: learning and generalization, competitive learning, principal component analysis and neural networks; Fuzzy logic: extracting fuzzy models from data, fuzzy decision trees, Stochastic search methods.<\/p>\n<p><strong>UNIT III : MINING DATA STREAMS \u00a0<\/strong> \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0[8 hours]<br \/>\nIntroduction to Streams Concepts \u2013 Stream data model and architecture &#8211; Stream Computing, Sampling data in a stream \u2013 Filtering streams \u2013 Counting distinct elements in a stream \u2013 Estimating moments \u2013 Counting oneness in a window \u2013 Decaying window &#8211; Realtime Analytics Platform(RTAP) applications &#8211; case studies &#8211; real time sentiment analysis, stock market predictions.<\/p>\n<p style=\"text-align: center\"><strong><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">Download iStudy<\/a> <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\">Android<\/a><a href=\"https:\/\/play.google.com\/store\/apps\/details?id=ini.istudy\" target=\"_blank\" rel=\"noopener\"> App for complete Anna University syllabus, results, timetables and all other updates. There are no ads and no pdfs and will make your life way easier.<\/a><\/strong><\/p>\n<p><strong>[TOTAL: 45 PERIODS]<\/strong><\/p>\n<p><strong>OUTCOMES:<\/strong> The student should be made to:<\/p>\n<ul>\n<li>Apply the statistical analysis methods.<\/li>\n<li>Compare and contrast various soft computing frameworks.<\/li>\n<li>Design distributed file systems.<\/li>\n<li>Apply Stream data model.<\/li>\n<li>Use Visualisation techniques<\/li>\n<\/ul>\n<p><strong> TEXT BOOKS:<\/strong><\/p>\n<ul>\n<li>Michael Berthold, David J. Hand, Intelligent Data Analysis, Springer, 2007.<\/li>\n<li>Anand Rajaraman and Jeffrey David Ullman, Mining of Massive Datasets,Cambridge University Press, 2012.<\/li>\n<\/ul>\n<p><strong>REFERENCES:<\/strong><\/p>\n<ul>\n<li>Bill Franks, Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with advanced analystics, John Wiley &amp; sons, 2012.<\/li>\n<li>Glenn J. Myatt, Making Sense of Data, John Wiley &amp; Sons, 2007 Pete Warden, Big Data Glossary, O\u201fReilly, 2011.<\/li>\n<li>Jiawei Han, Micheline Kamber \u201cData Mining Concepts and Techniques\u201d, Second Edition, Elsevier, Reprinted 2008.<\/li>\n<\/ul>\n<p>For all other B.Tech IT 7th sem syllabus go to <a href=\"http:\/\/www.inspirenignite.com\/anna-university\/anna-university-b-tech-information-technology-7th-sem-course-structure-for-r13-batch\/\">Anna University B.Tech Information Technology (IT) 7th Sem Course Structure for (R13) Batch.<\/a>\u00a0All details and yearly new syllabus will be updated here time to time.<\/p>\n<p>Do share with friends and in case of questions please feel free drop a comment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data Analytics Syllabus for B.Tech 7th sem is covered here. This gives the details about credits, number of hours and other details along with reference books for the course. The [&hellip;]<\/p>\n","protected":false},"author":2259,"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":[1],"tags":[],"class_list":["post-379","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/379","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\/2259"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/comments?post=379"}],"version-history":[{"count":2,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/379\/revisions"}],"predecessor-version":[{"id":10634,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/posts\/379\/revisions\/10634"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/media?parent=379"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/categories?post=379"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/anna-university\/wp-json\/wp\/v2\/tags?post=379"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}