{"id":24648,"date":"2020-07-20T07:40:00","date_gmt":"2020-07-20T07:40:00","guid":{"rendered":"https:\/\/www.inspirenignite.com\/jntuh\/data-analytics-syllabus-for-mca-3rd-year-1st-sem-r19-regulation-jntuh\/"},"modified":"2020-07-20T07:40:00","modified_gmt":"2020-07-20T07:40:00","slug":"data-analytics-syllabus-for-mca-3rd-year-1st-sem-r19-regulation-jntuh","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/jntuh\/data-analytics-syllabus-for-mca-3rd-year-1st-sem-r19-regulation-jntuh\/","title":{"rendered":"Data Analytics Syllabus for MCA 3rd Year 1st Sem R19 Regulation JNTUH"},"content":{"rendered":"

Data Analytics detailed Syllabus for Master of Computer Applications(MCA), R19 regulation has been taken from the JNTUH<\/a> official website and presented for the students affiliated to JNTUH course structure. For Course Code, Subject Names, Theory Lectures, Tutorial, Practical\/Drawing, Credits, and other information do visit full semester subjects post given below. The Syllabus PDF files can also be downloaded from the universities official website.<\/p>\n

For all other MCA 3rd Year 1st Sem Syllabus for R19 Regulation JNTUH, do visit MCA 3rd Year 1st Sem Syllabus for R19 Regulation JNTUH <\/a>Subjects. The detailed Syllabus for data analytics is as follows. <\/p>\n

Course Objectives:<\/h4>\n

For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App<\/a>
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b>
\"Get<\/a>. <\/p>\n

Course Outcomes:<\/h4>\n

After completion of this course students will be able to<\/p>\n

    \n
  1. Learn basics of R language and learn how to use R to handle the files with data.<\/li>\n
  2. Understand different files formats like .csv and .txt and learn how access these files.<\/li>\n
  3. Design Data Architecture<\/li>\n
  4. Understand various Data Sources<\/li>\n<\/ol>\n

    Unit I<\/h4>\n

    Data Management: Design Data Architecture and manage the data for analysis, understand various sources of Data like Sensors\/Signals\/GPS etc. Data Management, Data Quality(noise, outliers, missing values, duplicate data) and Data Processing and Processing.<\/p>\n

    Unit II<\/h4>\n

    For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App<\/a>
    It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b>
    \"Get<\/a>. <\/p>\n

    Unit III<\/h4>\n

    Regression:Concepts, Blue property assumptions, Least Square Estimation, Variable Rationalization, and Model Building etc. Logistic Regression: Model Theory, Model fit Statistics, Model Construction, Analytics applications to various Business Domains etc.<\/p>\n

    Unit IV<\/h4>\n

    Object Segmentation: Regression Vs Segmentation – Supervised and Unsupervised Learning, Tree Building – Regression, Classification, Overfitting, Pruning and Complexity, Multiple Decision Trees etc. Time Series Methods: Arima, Measures of Forecast Accuracy, STL approach, Extract features from generated model as Height, Average Energy etc and Analyze for prediction<\/p>\n

    Unit V<\/h4>\n

    For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App<\/a>
    It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.<\/b>
    \"Get<\/a>. <\/p>\n

    Text Books:<\/h4>\n
      \n
    1. Students Handbook for Associate Analytics – II, III.<\/li>\n
    2. Data Mining Concepts and Techniques, Han, Kamber, 3rd Edition, Morgan Kaufmann Publishers.<\/li>\n<\/ol>\n

      Reference Books:<\/h4>\n
        \n
      1. Introduction to Data Mining, Tan, Steinbach and Kumar, Addision Wisley, 2006.<\/li>\n
      2. Data Mining Analysis and Concepts, M. Zaki and W. Meira<\/li>\n
      3. Mining of Massive Datasets, Jure Leskovec Stanford Univ. Anand RajaramanMilliway Labs Jeffrey D Ullman Stanford Univ.<\/li>\n<\/ol>\n

        For detail Syllabus of all other subjects of Master of Computer Applications 3rd Year, visit MCA 3rd Year Syllabus<\/a> Subjects.<\/p>\n

        For all MCA results, visit JNTUH MCA all years, and semester results <\/a>from direct links.<\/p>\n","protected":false},"excerpt":{"rendered":"

        Data Analytics detailed Syllabus for Master of Computer Applications(MCA), R19 regulation has been taken from the JNTUH official website and presented for the students affiliated to JNTUH course structure. For […]<\/p>\n","protected":false},"author":2344,"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":[122,130],"tags":[],"class_list":["post-24648","post","type-post","status-publish","format-standard","hentry","category-3rd-year","category-mca"],"_links":{"self":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts\/24648","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/users\/2344"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/comments?post=24648"}],"version-history":[{"count":0,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/posts\/24648\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/media?parent=24648"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/categories?post=24648"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inspirenignite.com\/jntuh\/wp-json\/wp\/v2\/tags?post=24648"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}