2 Years
Post Graduate
Management
| Semester 1 | Semester 2 |
| Data Analytics Foundations | Machine Learning for Data Analytics |
| Statistical Methods for Business Analytics | Big Data Analytics and Management |
| Managerial Economics | Operations Research for Data Analytics |
| Financial Accounting for Analytics | Marketing Analytics |
| Organizational Behavior and Leadership | Data Visualization and Communication |
| Business Communication Skills | Database Management and SQL |
| Business Analytics Capstone Project (Part 1) | Business Analytics Capstone Project (Part 2) |
| Semester 3 | Semester 4 |
| Predictive Analytics and Modeling | Text Analytics and Natural Language Processing |
| Data Mining Techniques | Data Governance and Ethics |
| Supply Chain Analytics | Customer Analytics and Relationship Management |
| Financial Analytics | Social Media Analytics |
| Strategic Management for Analytics | Strategic Analytics and Decision Making |
| Business Analytics Capstone Project (Part 3) | Business Analytics Capstone Project (Part 4) |
Projects
Throughout the MBA in Data
Analytics program, students are required to work on various projects to
apply their skills and knowledge in real-world scenarios. These projects aim to
enhance their analytical abilities, problem-solving skills, and decision-making
capabilities.
The projects can involve tasks such as data analysis, data
visualization, predictive modeling, and business strategy formulation based on
data insights. Students typically work individually or in teams to complete
these projects, which may culminate in a final capstone project where they
showcase their skills and present their findings to faculty and industry
experts.
Reference Books
(1). "Data Science for Business" by Foster Provost and Tom
Fawcett
(2). "Python for Data Analysis" by Wes McKinney
(3). "R for Data Science" by Hadley Wickham and Garrett
Grolemund
(4). "Big Data: A Revolution That Will Transform How We Live, Work,
and Think" by Viktor Mayer-Schönberger and Kenneth Cukier
(5). "Predictive Analytics: The Power to Predict Who Will Click,
Buy, Lie, or Die" by Eric Siegel
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