connect with us
For further information please fill the details below:
Skip to main content
Business Analytics Banner 2
NMIMS-Business Analytics-Banner 3
NMIMS-Business Analytics-Banner 4

Post Graduate Certificate Program (PGP) in Business Analytics

Program Overview

  • The Program is intended for participants who want to build their careers in Business Analytics.
  • The CBA Program is a blend of classroom training (to be conducted in Mumbai) and technology-enabled learning platform.
  • The Program provides 380 contact hours for classroom training, one of the highest in the industry for a one-year program.
  • The classroom lectures would be held only during weekends (Saturdays and Sundays). The Program structure has been designed to enable working professionals to attend classes during weekends without any work disruptions.
  • The CBA Program is carefully crafted by academic and industry professionals to cover the essentials of Analytics, provides practical training on analytical tools, methodologies and technologies to facilitate solving real-world business problems.

Program Objectives 

  • The Program is intended for participants who want to build their careers in Business Analytics.
  • The Program is carefully crafted by distinguished academic and industry professionals to help participants develop a though conceptual understanding of the essentials and advanced topics in Business Analytics.
  • The Program aims to provide practical training on contemporary Business Analytical tools, methodologies and technologies.
  • The Program intends for participants to apply the above analytics skills-sets to solve real-world business problems.
  • Through the industry research project (Capstone), the program intends participants to handle a real-world business problem through various tools and methodologies discussed in the curriculum.


The teaching-learning cycle of this highly interactive Certificate Program in Business Analytics involves a judicious mix of a wide range of pedagogical approaches:

  • Classroom lectures by leading industry professionals in Business Analytics and distinguished faculty from NMIMS
  • Analytics tools
  • Case studies
  • Industry research project
  • Domestic and international exposure to practical Business Analytics
  • Developing and implementing business models for decision-making in Business Analytics
  • Frequent interaction with leading industry practitioners and academicians in Business Analytics

Program Structure

Saturdays and Sundays

9:00 am to 11:00 am,  
11:30 am to 1:30 pm, 
3:00 pm to 5:00 pm,  
5:30pm to 7:30 pm,


To be announced in the class

Industry Engagement

The Program is designed with meticulous inputs and insights from leading industry practitioners regarding program curriculum, case studies, analytical methodologies, data sets, business problems and analytics projects to align the Program to the industry requirements.

A key highlight of the Program is the "Capstone Analytics Project", fostering solid industry-academia partnership. Through the Project, students would need to identify a dataset, business problem and do a comprehensive analysis that results in a detailed report and presentation made that highlights the findings, methodology and implications for business.

Course Structure

Module 1 - Introduction to Statistics

  • Basic concepts of probability and statistics
  • Correlations, Analysis of Variance, Hypothesis Testing
  • Maximum likelihood methods and fit statistics
  • Statistical Inference
  • Introduction to linear models

Module 2 - Database Management

  • Relational Models and Database Design
  • Transaction Processing
  • SQL and extensions
  • Database optimization and query processing
  • Parallel and Distributed Databases

Module 3 - Business Intelligence* & Visualization

  • Basics of Reporting and BI dashboards
  • Basics of ETL frameworks
  • Data warehousing
  • Data Visualization using Spotfire and Tableau

Module 4 Statistical Programming

  • Installation and Basics of R
  • Vectors and Data Structures in R
  • Matrices, Arrays, Lists and Data Frames in R
  • Statistical Functions in R
  • Data Analytics and Visualization Examples in R

Module 5 - Machine Learning and Analytics*

  • Machine Learning Methods for Predictive Analytics
  • Decision Tree Induction and Analysis
  • Neural Networks
  • Nearest Neighbor Algorithms and Clustering

Module 6 - Big Data Analytics*

  • Introduction to Big Data
  • Big Data Platforms – Hadoop, Spark
  • Data Storage and Processing – HDFS, HBase and NoSQL
  • Text and stream analytics in Big Data
  • Hive, Pig and Hadoop extensions and tools

Module 7 - Marketing & Media Analytics*

  • Overview of marketing analytics
  • Customer Targeting and Lifetime Value Modeling
  • Attribution, Data and Marketing Models
  • Social Media Analytics

Module 8 - Statistical Data Mining

  • Data Exploration and Data Visualization
  • Linear Models
  • Non-Linear Models
  • Statistical Inference and Predictive Modeling

Module 9 - Analytics for Finance and Accounting

  • Overview of Financial & Accounting Data
  • Financial Data Analytics
  • Forensic Accounting and Fraud Detection
  • Analyzing Financial Statements and Quarterly Filings

Module 10 - Optimization*

  • Overview of combinatorial optimization
  • Linear Programming and Sensitivity Analyses
  • Integer Programming
  • Business Operations and Optimization Examples

Module 11 - Capstone Analytics Project

  • Students will need to identify a dataset, business problem and do a comprehensive analysis that results in a detailed report and presentation made that highlights the findings, methodology and implications for business.

Module 12 - Analytics in Business*

  • Business Cases in Analytics covering the use of analytics and data in a variety of industries worldwide

** These could change under extra-ordinary situations

Selection Process

The Admissions Committee would evaluate each applicant on several criteria to ensure that the participants selected for the programme are well-rounded individuals with sufficient analytical/programming/statistical backgrounds.

Each applicant would have to undergo an interview process to determine the fit, interest and inclination. Besides, an assessment test would have to be administered for freshers. Each component of the application including the application form, assessment test and the interview would be adequately reviewed, and the subsequent selection of the participants for the program will be made.

Connect With Us x