Duration : 24 months
Structure : Six terms with an internship project after three terms

This first of its kind PGDM Programme in Business Analytics. Artificial intelligence. Machine Learning. and has been designed to equip students with knowledge and skills in extensively using business sciences such as programming platforms - R, Python, Tableau as well as the use of analytical tools - SPSS, Data Mining and Social Media Analytics.

The Programming Language R provides a wide variety of statistical modelling and analysis, classification of data and time series analysis. Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems. Python is a programming language that lets you work more quickly and integrate your systems more effectively.

SPSS is a widely used programme used by market researchers, survey researchers, and students as well and data miners for analyzing raw data. Tableau is the analytical tool which permits live visual analytics aiding data exploration visually. Interactive dashboards help users uncover hidden insights on the fly. Tableau harnesses people’s natural ability to spot visual patterns quickly, revealing everyday opportunities and eureka moments alike.

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programme that can access data use it and learn for themselves.

These powerful Analytical Tools and applications like Artificial Intelligence and Machine Learning dramatically enhance a manager’s ability to make informed decisions of high quality, thereby making the most optimal use of the organisation’s resources.

A corporate manager empowered with these decision making tools is able to take advantage of the massive amounts of data capturing the preferences and habits of millions of customers and make decisions which would radically improve effectiveness of managerial actions.

Programme Structure
The structure is conceived in such a way that participants would gain knowledge of Data Analytics, Artificial Intelligence and Machine Learning tools extensively and at the same time acquire a wide range of managerial capabilities while specializing in main stream areas like Marketing and Finance. The programme is conceived as a full-scale Business Master’s Programme combined with Master’s level exposure to Business Sciences. It is this combination which makes this programme unique.

The first three trimesters have eight courses in the Business Analytics domain which empowers participants with statistical, research, analytical as well as relevant mathematical capabilities. At the same time students are fully exposed to general management courses in the domains of Marketing, Finance, Accounting, Organisational Behaviour, Economics and Communications.

In the terms 4 to 6, participants are exposed to several more courses in Data Analytics. Additionally students may choose an area of specialization such as Marketing and Finance. In these specialization areas students can choose seven courses within their chosen second sepcialisation. This combination creates a powerful blend of functional capabilities backed by competencies in Business Sciences.

Global Immersion Programme at NTU, Singapore
Towards the end of the second year students undergo a Global Immersion Programme at Nanyang Technological University at Singapore. The NTU, Singapore is ranked top 27th University by Global Financial Times with exceptional capabilities in Artificial Intelligence, Business Analytics and Business Sciences. The Global Immersion programme is the Capstone of the content rich PGDM – BA, ML & AI programme and adds enormous value to the participant’s learning by witnessing at first hand the application of business sciences in a world class environment.


Term 1

All courses are compulsory

Academic Area

Course Title

General Management

Computer Applications for Business (XL Miner)

General Management

Business Communication

Business Science

Linear Algebra & Discrete Mathematics and Coding the Matrix

Business Science

Business Statistics (Descriptive) (Data Science 1)

Business Science

Introduction to R Programming

Economics

Managerial (Micro) Economics

Marketing Management

Marketing Management I

Financial Management

Accounting and FSA



Term 2

All courses are compulsory

Academic Area

Course Title

Business Science

Calculus

Business Science

Introduction to Python Programming

General Management

Business Research Methods

Economics

Macro Economics

Marketing Management

Marketing Management II

Financial Management

Corporate Finance

HRBS

Organizational Behavior

Operations Management/Business Analytics

Operations Management



Term 3

All courses are compulsory

Academic Area

Course Title

Business Science

Machine Learning ( Pattern Classification, SVM, Bayesian Decision Theory, Clustering)

Marketing Management

Marketing Research and Multivariate Data Analysis (With SPSS)

Business Science

SQL & Data Mining

Business Science

Artificial Intelligence ( Neural Networks, Deep Learning & Speech Recognition)

HRBS

Human Resources Management

Operations Management/Business Analytics

Operations Research

Business Science

Advanced Statistics (Inference) (Data Science 2)



Term 4

Core Courses are compulsory. Students may choose any of the four specialisations, Marketing, Operations, Finance or HR. Within a specialization, all courses are compulsory. Students opting for Operations specialization may choose any two electives from other areas in Trimester 4.

Academic Area

Course Title

Business Science (Core)

Data Visualization (Tableau)

Business Science (Core)

Predictive Analytics (Using R & Python)

Operations Management (Core)

Supply Chain Management

Operations management (Core)

Total Quality Management

Financial Management (Elective)

Security Analysis and Portfolio Management

Financial Management (Elective)

Management of Financial Institutions

Marketing Management (Core)

Services Marketing

Marketing Management (Core)

Brand Management

Human Resource Management (Elective)

Talent Acquisition and Retention

Human Resource Management (Elective)

Compensation & Benefits Management



Term 5

Core courses are compulsory. All three courses from the area of specialization chosen need to be taken.

Academic Area

Course Title

Business Science (Core)

Big Data ( Hadoop/ Spark)

Business Science (Core)

Business Forecasting

Business Science (Core)

Text, Web & Social Media Analytics

Marketing Management (Elective)

Retail Management

Marketing Management (Elective)

Sales and Distribution Management

Marketing Management (Elective)

B2B Marketing

Financial Management (Elective)

Financial Econometrics & Time Series Analysis

Financial Management (Elective)

Financial Derivatives and Risk Management

Financial Management (Elective)

Financial Modelling and Analytics

Operations Management (Elective)

Services Operations Management

Operations Management (Elective)

Project Management

Operations Management (Elective)

Pricing & Revenue Management

Human Resource Management (Elective)

Leadership

Human Resource Management (Elective)

Learning & Development

Human Resource Management (Elective)

Performance Management




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