ITL801: Big Data Lab Syllabus for IT 8th Sem 2019 Pattern Mumbai University

Big Data Lab detailed syllabus scheme for Information Technology (IT), 2019 regulation has been taken from the University of Mumbai official website and presented for the Bachelor of Engineering students. For Course Code, Course Title, Test 1, Test 2, Avg, End Sem Exam, Team Work, Practical, Oral, Total, and other information, do visit full semester subjects post given below.

For all other Mumbai University Information Technology 8th Sem Syllabus 2019 Pattern, do visit IT 8th Sem 2019 Pattern Scheme. The detailed syllabus scheme for big data lab is as follows.

Big Data Lab Syllabus for Information Technology BE 8th Sem 2019 Pattern Mumbai University

Lab Objectives:

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Lab Outcomes:

Students will be able to:

1. Demonstrate capability to use Big Data Frameworks like Hadoop
2. Program applications using tools like Hive, pig, , NO SQL and MongoDB for Big data Applications
3. Construct scalable algorithms for large Datasets using Map Reduce techniques
4. Implement algorithms for Clustering, Classifying and finding associations in Big Data
5. Design and implement algorithms to analyze Big data like streams, Web Graphs and Social Media data and construct recommendation systems.
6. Apply the knowledge of Big Data gained to fully develop a BDA applications for real life applications.

Prerequisites:

Java, Python

Hardware/Software Requirement

PC i3 or above, 8 GB RAM Virtual Machine, Hadoop Frame work, NOSQL and MongoDb Compilers

Module 1

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Module 2

Programming exercises on Hadoop Using Hive, Pig, Hbase Sqoop NOSQL, MongoDB 04 LO 2

Module 3

Implementing simple algorithms in MapReduce Matrix multiplication, Aggregates, joins, sorting, searching etc. 04 LO3

Module 4

Implementing Algorithms using MapReduce (Any 2)

• Implementing Frequent Item set Mining
• Implementing Clustering algorithms
• Implementing Classification Algorithms 06 LO 4

Module 5

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Module 6

Mini Project: One real life large data application to be implemented (Use standard Datasets available on the web)

1. Twitter data analysis
2. Fraud Detection
3. Text Mining
4. Recommendation Engines (list of datsets also given in the text book. 05 LO 5 LO 6

Text Books:

1. Radha Shankarmani, M Vijayalakshmi, Big Data Analytics, Wiley Publications,
2. Alex Holmes Hadoop in Practice, Manning Press, Dreamtech Press.
3. Professional NoSQL Paperback, by Shashank Tiwari, Dreamtech Press
4. MongoDB: The Definitive Guide Paperback, Kristina Chodorow (Author), Michael Dirolf, O’Reilly Publications

Reference Books:

1. Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, Bart Baesens , WILEY Big Data Series.
2. Hadoop: The Definitive Guide by Tom White, O’Reilly Publications
3. Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services
4. NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence by Pramod J. Sadalage, Addison Wesley

Term Work:

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 pdf platform to make students’s lives easier.
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For detail syllabus of all other subjects of Information Technology (IT) 8th Sem 2019 regulation, visit IT 8th Sem Subjects syllabus for 2019 regulation.