M.Sc Big Data Analytics Syllabus and Subjects

Duration: 2 Years
Avg Fees: ₹90K - 1.8 LPA

The M.Sc Big Data Analytics syllabus is a two-year postgraduate course in data science. The M.Sc Big Data Analytics syllabus and subjects are divided into four semesters. The syllabus includes Introduction to Computer Hardware, Statistics for Data Science, Technical Writing & Paper Presentation, Big Data and Internet of Things, System Software Concepts, Data Warehousing, Projects, Internships, and many more.

Semester Wise M.Sc Big Data Analytics Syllabus

The M.Sc Big Data Analytics course aims to ensure that the students have all the exposure in covering everything from data science to the use of advanced analytic techniques. This M.Sc Big Data Analytics course covers very large heterogeneous data sets, which can contain structured, semi-structured, and unstructured data, as well as data from many sources and sizes ranging from terabytes to zettabytes. Semester-wise M.Sc Big Data Analytics subjects list is given in the table below: 

M.Sc Big Data Analytics First Year Syllabus

Semester I

Semester II

Statistical Methods for Data Analysis

Predictive Analytics

Java Programming

Data Mining

Optimization and Heuristics

Text Analytics

Topics in Analytics in R

Topics in Analytics with Python

Databases and Information Retrieval

Social Network Analysis

Programming Lab Courses/ Project Courses - I

Programming Lab Courses/ Project Courses - II

 

M.Sc Big Data Analytics Second Year Syllabus

Semester III

Semester IV

Analytics for Big Data

Elective I, II, III

Data Visualization

Internship program in Data Analytics.

Data Warehousing

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M.Sc Big Data Analytics Subjects

The M.Sc Big Data Analytics course offers both theoretical and practical aspects of the study. M.Sc Big Data Analytics subjects like Computer Hardware, Statistics for Data Science, Technical Writing & Paper Presentation, Big Data and Internet of Things, System Software Concepts, Data Warehousing, Projects, Internships, and many more. The course curriculum includes theoretical and practical subjects. The compulsory subjects include:

  • Introduction to Computer Hardware
  • Statistics for Data Science
  • Technical Writing & Paper Presentation
  • Big Data and Internet of Things
  • System Software Concepts

M.Sc Big Data Analytics Course Structure

M.Sc Big Data Analytics course structure includes both core and elective subjects which are the aspects of the study. The course structure is made in such a way that both classroom training and practicals are included in the course curriculum. The course structure is given below:

  • IV Semesters
  • Core & Electives Subjects
  • Practicals
  • Projects
  • Internships

M.Sc Big Data Analytics Teaching Methodology and Techniques

The course curriculum takes into account different teaching methods. Classroom learning includes practical sessions for students. Students who are passionate about studying deep into computer programming with data analytics can be a boon for global technology development. Listed below are the teaching methodology and strategies in general:

  • Practical & Live sessions
  • Guest Lectures, Seminars, and Conferences
  • Group Assignment and Discussion
  • Project Submission
  • Internship

M.Sc Big Data Analytics Projects

Projects are given to students to understand the concepts and help students in getting hands-on experience. Research projects are to be completed by the end of the final year. Some popular M.Sc Big Data Analytics projects topics are:

  • Web Scraping
  • Data Cleaning
  • Sentiment Analysis
  • Exploratory Data Analysis (EDA)
  • 10 Free Public Datasets For EDA

M.Sc Big Data Analytics Reference Books

M.Sc Big Data Analytics books are available both online and offline by many authors and publications. Reference books are meant for gaining an in-depth understanding of big data analyst concepts. Books on M.Sc Big Data Analytics for academic purposes differ according to subjects. Some of the reference books for the course in M.Sc Big Data Analytics are:

M.Sc Big Data Analytics Books

Books

Authors

Big Data Analytics

Parag Kulkarni

Lean Analytics: Use Data to Build a Better Startup Faster

A.Croll and B.Yoskovitz

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die

E. Siegel

Data Analytics Made Accessibly

A. Maheshwari

M.Sc Big Data Analytics Fee Structure

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