MBA in Data Science and Artificial Intelligence

The managerial landscape is rapidly changing due to the advancement in ICT and web enabled business platforms...

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Learning Outcomes

Exposure to fundamentals of business management with special emphasis on contemporary and emerging topics.

Personality development by adequate exposure to soft skills like communication, creativity, and emotional intelligence etc.

In-depth exposure to tools and techniques like of DS, AI, ML etc. with a strong emphasis on problem solving approach.

Evolve as leaders of an organisation who can combine rational and subjective skills in the context of an organisation to make appropriate decisions.

Program Highlights

2-year long full-time Masters programme, distributed in 4 semesters.

 
                      A blend of contemporary management concepts, soft skills towards developing individuals, and relevant applications of data science tools.

The total credit requirement is 80.

 
                      The program aims to provide an in-depth exposure on data science tools and techniques like analytics, artificial intelligence machine learning, deep learning, natural language processing, and neural networks with a strong emphasis on problem solving approach.

Program Curriculum

The courses covered during the program will include basic to advanced topics from the following broad areas:

Semester I

Introduction to Bhagavad Gita

Probability and Statistics for Data Science & AI

Python Programming

Mathematical Foundation of Data Science and AI

Communication Skills for Managers

Financial Statement Analysis

Managerial Economics

Marketing Management I

Creative Thinking

Problem Solving and Decision Making

Operations Management

Semester II

Fundamentals of Data and Analytics

Disruptive Technology in Data Science

Strategic Management

Machine Learning for Business

Introduction to AI and Automation

Organizational Behaviour

Decision Analysis

Project Management

Marketing Management II

Ethical and Legal Aspects of Business

Financial Management

Semester III

Neural Network Fundamentals for Business

Digital Business Strateg and Models and Transformations

Entrepreneurship

Business and Data Leadership

Management Insights from Indian Knowledge System

Human Resource Management

Qualitative Research Methods

Free Elective 1

Project I

Semester IV

Discipline Elective 1

Discipline Elective 2

Discipline Elective 3

Discipline Elective 4

Discipline Elective 5

Free Elective 2

Project II

Discipline Electives (DE)

AI for Marketing

Causal Analytics for Business Decisions

Financial Analytics

Fintech

Blockchain for Business

Deep Learning for Business Applications

Natural Language Processing for Business

DevOps in ML and AI

Intelligent Automation

Fuzzy Logic for Business Decision Making

Evolutionary Computation for Business Solutions

DevOps

Operations Management

Design Thinking

Marketing Analytics

AI in Finance

Supply Chain Analytics

Management Science in Practice - A Modelling and Case Studies Approach with MS-Excel

Free Electives (FE)

Product Management

Social Analytics

Cloud Computing for Business

Cyber Security

Ethics and Privacy

Negotiation Analysis

Data Strategy

AI Strategy and Implementation

Leadership

Leadership Lessons from Indian Knowledge Systems

Consumer Behavior

Digital Marketing

Supply Chain Management

Advertising and Brand Management

In the third and fourth semester, participants will be offered a pool of electives to choose from the advanced courses offered by the institute as well as a project under the guidance of a faculty or industry expert.

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