The MBA in Data Science and Data Analytics course is designed to make students job-ready professionals. The syllabus is structured in a way to meet not only the current trends of the industry but also its future needs of the industry. Some of the syllabus topics are Artificial Intelligence, Machine-Learning, Python Programming, Design Thinking, etc.

Semester Wise MBA Data Science and Data Analytics Syllabus

MBA Data Science and Data Analytics syllabus give students a clear picture of the various concepts of data science and data analytics. Some of the syllabus subjects are business communication, business skills development, applied operations research, etc. Semester wise MBA Data Science and Data Analytics subjects are listed below:

MBA Data Science and Data Analytics First Year Syllabus
Semester I Semester II
Communication Skill Development Business Communication
Corporate Legal Environment Project Management
Accounting for Managers Macroeconomics in Global Economy
Applied Statistics for Decision Making Financial Analysis and Reporting
Business Skills Development Research Methodology
Management of Organizations Applied Operations Research
Business Policy and Strategic Management Applied Business Analytics
MBA Data Science and Data Analytics Second Year Syllabus
Semester III Semester IV
Econometrics Data Cleaning, Normalization, and Data Mining
Ethical and Legal Aspects of Analytics R Programming
Project - 1 Project - 2
SAP HCM SAP FICO
Spreadsheet Modelling Stochastic Modelling
Specialization Group A - Human Resource Management Specialization Group A - Human Resource Management
Specialization Group B – Foundations Specialization Group B – Foundations
Specialization Group C - Data Analytics Specialization Group C - Data Analytics

MBA Data Science and Data Analytics Subjects

MBA in Data Science and Data Analytics subjects is categorized as core, elective, and lab subjects. Students should select the elective subjects according to their area of interests, and career goals.

Core Subjects:

  • Management of Organizations
  • Research Methodology
  • Corporate Legal Environment
  • Project Management
  • Applied Operations Research
  • Accounting for Managers
  • Business Communication
  • Applied Statistics for Decision Making

Elective Subjects:

  • HR Industrial Psychology Performance Management
  • HR Analytics
  • HR Planning and Development Management of Industries
  • Stochastic Modelling
  • SAP FICO
  • SAP HCM

MBA Data Science and Data Analytics Course Structure

The MBA in Data Science and Data Analytics course consists of three major parts: core subjects, elective subjects, and lab subjects. The core subjects are the compulsory subjects; elective subject students can select the specialization according to their area of interest while the lab section is the practical class. The course structure is:

  • Core Subjects
  • Elective Subjects
  • Lab 
  • Seminars
  • Workshops
  • Research Paper Analysis
  • Internship
  • Project work

MBA Data Science and Data Analytics Teaching Methodology and Techniques

The MBA Data Science and Data Analytics Teaching Methodology and Techniques are such that each student can learn and grasp the various concepts and knowledge imparted. The mixture of theory and practical teaching gives the students a proper understanding of the program. Below are some of the teaching methodology and techniques:

  • Group projects
  • Practical sessions
  • Thesis writing
  • Research papers 
  • Workshops
  • Lab sessions
  • Data programming
  • Data analysis
  • Big data

MBA Data Science and Data Analytics Projects

MBA in Data Science and Data Analytics course is all about the study of managing information, data statistics, Data Visualisation, Fintech Concepts, Artificial Intelligence and Machine Learning, and much more.

Popular MBA Data Science and Data Analytics Projects are:

  • Big Data for Cybersecurity
  • Analysis of Sentiments
  • Market Survey for Segmentation
  • Text Mining
  • Analysis of Tourist Behaviour

MBA Data Science and Data Analytics Reference Books

Listed below are the best Data Science and Data Analytics reference books suggested by our experts:

MBA Data Science and Data Analytics Books
Books Authors
Practical Statistics for Data Scientists Peter Bruce and Andrew Bruce
Python for Data Analysis  Wes McKinney
R for Data Science Hadley Wickham and Garret Grolemund
Big Data MBA: Driving Business Strategies with Data Science Bill Schmarzo

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