The IIT Madras BS in Management and Data Science pairs a management curriculum with the quantitative training of the Data Science programme. The Foundation level shares Mathematics for Data Science I, Statistics for Data Science I, Computational Thinking and English I with the DS programme, then adds economics, accounting and management theory. From the Diploma level onward every management function — marketing, HR, finance, operations, supply chain — is taught as an analytics course, and learners can exit with a Diploma in Data Analytics for Business.
Total credits
142
Levels
3
Courses listed
52
Eight courses totalling 32 credits. Four are shared with the Data Science Foundation — Mathematics for Data Science I, Statistics for Data Science I, Computational Thinking and English I — so learners who start in DS and move across carry credit with them. The other four introduce economics, financial accounting, business statistics and management theory.
Fourteen courses and two projects totalling 60 credits. Eight courses plus both projects form the Data Analytics for Business track, which is the exit route for the standalone diploma; the remaining six broaden into corporate finance, organisational behaviour, marketing management and macroeconomics. Every analytics course is tied to a business function rather than taught abstractly.
Six core courses worth 24 credits plus 26 credits of electives. The core is deliberately current — GenAI for Business, Digital Business and Market Intelligence sit alongside supply chain management and time series analysis — and the elective basket is the widest of any IITM BS programme, spanning finance, marketing, economics and responsible AI.
Learners do not have to complete the full degree. Depending on the credits earned, the programme can be exited with any of the following:
EduVerse does not host notes, previous year papers or graded assignment solutions for this programme yet — our resource library currently covers the Data Science programme. This page documents the official course structure so you can plan terms and credits. If you have Management & Data Science material to contribute, we would like to hear from you.