Big Data and Analytics detailed Syllabus for Computer Science & Engineering (CSE), 2018 scheme has been taken from the VTUs official website and presented for the VTU students. For Course Code, Subject Names, Teaching Department, Paper Setting Board, Theory Lectures, Tutorial, Practical/Drawing, Duration in Hours, CIE Marks, Total Marks, Credits and other information do visit full semester subjects post given below. The Syllabus PDF files can also be downloaded from the official website of the university.
For all other VTU CSE 7th Sem Syllabus for BE 2018 Scheme, do visit VTU CSE 7th Sem Syllabus for BE 2018 Scheme Subjects. The detailed Syllabus for big data and analytics is as follows.
Course Objectives:
For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier.
.
Module 1
Introduction to Big Data Analytics: Big Data, Scalability and Parallel Processing, Designing Data Architecture, Data Sources, Quality, Pre-Processing and Storing, Data Storage and Analysis, Big Data Analytics Applications and Case Studies.
Module 2
Introduction to Hadoop (T1): Introduction, Hadoop and its Ecosystem, Hadoop Distributed File System, MapReduce Framework and Programming Model, Hadoop Yarn, Hadoop Ecosystem Tools. Hadoop Distributed File System Basics (T2): HDFS Design Features, Components, HDFS User Commands. Essential Hadoop Tools (T2): Using Apache Pig, Hive, Sqoop, Flume, Oozie, HBase.
Module 3
For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Module 4
MapReduce, Hive and Pig: Introduction, MapReduce Map Tasks, Reduce Tasks and MapReduce Execution, Composing MapReduce for Calculations and Algorithms, Hive, HiveQL, Pig.
Module 5
Machine Learning Algorithms for Big Data Analytics: Introduction, Estimating the relationships, Outliers, Variances, Probability Distributions, and Correlations, Regression analysis, Finding Similar Items, Similarity of Sets and Collaborative Filtering, Frequent Itemsets and Association Rule Mining. Text, Web Content, Link, and Social Network Analytics: Introduction, Text mining, Web Mining, Web Content and Web Usage Analytics, Page Rank, Structure of Web and analyzing a Web Graph, Social Network as Graphs and Social Network Analytics:
Course Outcomes:
For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
Question paper pattern:
- The question paper will have ten questions.
- Each full Question consisting of 20 marks
- There will be 2 full questions (with a maximum of four sub questions) from each module.
- Each full question will have sub questions covering all the topics under a module.
- The students will have to answer 5 full questions, selecting one full question from each module.
Text Books:
- Raj Kamal and Preeti Saxena, Big Data Analytics Introduction to Hadoop, Spark, and Machine-Learning, McGraw Hill Education, 2018 ISBN: 9789353164966, 9353164966
- Douglas Eadline, “Hadoop 2 Quick-Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem”, 1stEdition, Pearson Education, 2016. ISBN-13: 978-9332570351
Reference Books:
For the complete Syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdfs platform to make students’s lives easier..
For detail Syllabus of all other subjects of BE 7th Sem Computer Science & Engineering, visit (CSE) 7th Sem Syllabus Subjects.
For all (CBSE & Non-CBSC) BE results, visit VTU BE all semester results direct links.