The specialization in Research and Business Analytics offers electives such as machine learning, artificial intelligence, big data, and domain specific analytics courses such as medical analytics and financial analytics, in order to cater to industry demandin such fast growing areas.

RESEARCH & BUSINESS ANALYTICS
FINANCE/FINANCIAL ENGINEERING
The specialization in Finance includes in-depth theoretical and empirical coursework in asset pricing and corporate finance. Electives offered include stochastic calculus, derivatives pricing, computational techniques in finance and market microstructures.
RESEARCH & BUSINESS ANALYTICS
Domain-specific courses
Financial Risk Analytics
Medical Analytics
Machine Learning
Visualization
Deep and Reinforcement
Learning
Analytics in Business
Algorithms and Data Structures
Select Courses – FINANCE
Domain-specific courses
Asset Pricing Corporate
Finance
Financial Market
Microstructure
Stochastic Calculus
Financial Time Series
Derivatives and Options
Careers for RESEARCH & BUSINESS ANALYTICS
Students with the RESEARCH & BUSINESS ANALYTICS specialisation are ready for careers as data scientists, business analysis and intelligence, management reporting and control, datadriven consulting and policy formulation
Careers for FINANCE
Students with the FINANCE specialization are ready for careers in quantitative finance roles like structuring, trading, and risk management
Curriculum
The MSE PGDM is designed to train students for technically challenging jobs with financial institutions, consulting services and analytical companies. They also provide a unique combination of knowledge of complex theories with rigorous exposure to the underlying mathematical-statistical theories and practical financial modeling to enhance the ability of the students to meet the demands of today’s industry and companies committed to data-driven decision-making. Experts from industry further enrich the student ability. The two-year program is divided into six terms with class room instruction, and one term in the summer which consists of an internship in the industry. Both Research & Business Analytics (RBA) as well as Financial Engineering (FIN) undergo a similar first year, with a common syllabus in the first three terms. The focus is on learning foundational Mathematics, Microeconomics, Macroeconomics, Stochastic Calculus, Accounting, Finance with an introduction to Programming, Algorithms and Marketing

Objectives of the Programme
Develop a strong foundation for interdisciplinary work
Combine course work from the areas of Finance, Economics, Management, Business Analytics and Data Science
Exposure to latest trends in academics and industry through projects and internship
First Year Courses – Common for RBA & FIN
- 111 Quantitative Methods
- 112 Financial Management
- 113 Microeconomics
- 114 Calculus and Differential Equations
- 115 Probability
- 116 Analytics in Business
- 121 Programming in Python
- 122 Finance I
- 123 Macroeconomics
- 124 Optimization
- 125 Statistical Inference and Modeling
- 126 Machine Learning I
- 131 Financial Econometrics
- 132 Corporate Finance
- 133 Big Data
- 134 Supply Chain Management
- 135 Advanced Macroeconomics
- 136 Stochastic Process
Second year Courses
- 241 Deep and Reinforcement Learning
- 242 Financial Time Series Analysis
- 243 Asset Pricing I
- 244 Derivatives and Options
- 245 Financial Risk Analytics in Banking and Financial Services
- 246 Stochastic Calculus
- 247 Programming in SQL
- 251 AI Applications in Business
- 252 Advanced Analytical Models for Decision Making
- 253 Fixed Income Models
- 254 Credit Risk Models
- 255 Visualization
- 256 Financial Market Microstructure
- 257 Algorithms and Data Structures
List of Electives:
258 Applied Multivariate Statistics
- 261 Information Theory and Cryptography
- 262 Topics in Data Science
- 263 Topics in Financial Engineering
- 264 Computational Finance
List of Special Electives
- 260 Advanced Visualization
- 265 Asset Pricing II
- 266 Medical Analytics
- 267 Robotics
- 268 Quantum Computing
- 269 Projects in R / Python
- 270 Algorithmic and High Frequency Trading
- 271 Marketing Concepts
- 272 Organization Behavior
- 273 Human Resources
- 274 Natural Language Processing and Text Analytics
- 275 Dissertation