Business Intelligence & Analytics Course | IIT Madras Postgraduate Program
Course Details
| Exam Registration | 7011 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Computer Science and Engineering, Data Science |
| Credit Points | 3 |
| Level | Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 17 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Unlock the Power of Data: A Comprehensive Guide to the Business Intelligence & Analytics Course from IIT Madras
In today's data-driven world, the ability to transform raw information into actionable insights is the ultimate competitive advantage. Whether you're aiming to pivot your career, enhance your skill set, or lead data-centric initiatives in your organization, a strong foundation in Business Intelligence & Analytics (BIA) is indispensable. We are excited to present a deep dive into a premier postgraduate course designed to equip you with exactly that: the Business Intelligence & Analytics program offered by the prestigious Indian Institute of Technology Madras (IIT Madras).
Course Overview: Your Gateway to Data Science
This intensive 12-week postgraduate course is meticulously structured to bridge the gap between theoretical knowledge and practical application. It is tailored for professionals and graduates seeking to master the thought processes, modeling approaches, and tools required to leverage enterprise data for strategic business decisions. The curriculum prepares participants for thriving careers in data science, business analytics, market research, and IT services.
Learn from an Esteemed Expert: Prof. Saji K Mathew
The course is led by Prof. Saji K Mathew, a distinguished professor at the Department of Management Studies, IIT Madras. A Fulbright Scholar who conducted post-doctoral research at Emory University's Goizueta Business School in the USA, Prof. Mathew brings a wealth of academic and research expertise. His current research focuses on cutting-edge areas like behavioral cybersecurity, information privacy, and digital nudging. As a founding member and Vice President of the Association for Information Systems India Chapter (INAIS), his guidance ensures the course content is both rigorous and relevant to industry needs.
Who Should Enroll?
- Postgraduate students in Computer Science, Data Science, Engineering, or Management.
- Working professionals in IT, analytics, marketing, or operations seeking to upskill.
- Aspiring data scientists and business analysts.
- Managers and decision-makers who want to harness data-driven strategies.
Prerequisite: A foundational knowledge of business statistics is desirable. Participants can refer to the NPTEL course "Introduction to Probability and Statistics" for preparation.
Detailed 12-Week Course Curriculum
The course progresses from foundational concepts to advanced analytical techniques, ensuring a holistic learning experience.
| Week | Topic | Key Learning Outcomes |
|---|---|---|
| 1 | Introduction to BIA | Understand drivers, types (descriptive, predictive, prescriptive), and core vocabulary. |
| 2 | Technical Architecture & Data Management | Learn BIA architecture, OLTP systems, and database design fundamentals. |
| 3 | Databases & Data Warehousing | Master relational databases, normalization, SQL queries, and OLAP concepts. |
| 4 | Descriptive Analytics & Visualization | Explore customer analytics, survival analysis, and Customer Lifetime Value (CLV). |
| 5 | Data Mining Process & Regression | Grasp the data mining process, statistical learning, and regression analysis. |
| 6 | Classification Techniques | Dive into classification models, scoring, and performance metrics (ROC curves). |
| 7 | Decision Trees & Ensemble Methods | Learn tree induction, pruning, and ensemble methods for robust models. |
| 8 | Python Implementation: Decision Trees | Apply decision trees to a real-world problem (targeted mailing) using Python. |
| 9 | Cluster Analysis | Understand distance measures, K-means, and other clustering algorithms. |
| 10 | Case Study: Clustering in Python | Implement store segmentation, profile clusters, and apply RFM analysis. |
| 11 | Machine Learning & Neural Networks | Explore ANN topology, backpropagation, and financial time series modeling. |
| 12 | Text Mining & Sentiment Analysis | Learn the text mining process, sentiment scoring, and implementation in R. |
Hands-On Learning with Industry-Standard Tools
This course emphasizes practical, hands-on learning. Participants will gain proficiency in essential tools and programming languages:
- SQL & Databases: Work with MySQL and real-life datasets like "Adventure Works Cycles" and "Retail Sense."
- Programming: Develop scripts in both Python and R. The course provides flexibility to choose one or learn both, with comprehensive installation guides and learning resources provided.
- Libraries & Packages: Use powerful libraries like scikit-learn, tidytext, caret, and neuralnet for implementing algorithms.
- Data Sources: Engage with diverse data from UCI Machine Learning Repository, Yahoo! Finance, Twitter, and Kaggle.
Key Textbooks and Resources
The course is supported by authoritative texts and a wealth of online resources:
- Primary Text 1: Han, J., Pei, J. & Tong H. (2023). Data Mining Concepts and Techniques (4th ed.).
- Primary Text 2: James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning with Applications in R.
- Detailed appendices include curated links for mastering Python, R, and MySQL, from official documentation to video tutorials and online courses.
Conclusion: Transform Your Career with Data
The Business Intelligence & Analytics course from IIT Madras is more than just an academic program; it's a career accelerator. By combining the stellar reputation of IIT Madras, the expertise of Prof. Saji K Mathew, and a curriculum built on industry demands, this course offers an unparalleled opportunity to become a leader in the field of data science and analytics. Whether you are analyzing customer behavior, optimizing operations, or building predictive models, the skills acquired here will be your most valuable asset.
Take the first step towards mastering the language of data. Enroll today and unlock new dimensions in your professional journey.
Enroll Now →