IITM BS Business Analytics (BSMS2002): Syllabus and Tips

Business Analytics (BSMS2002) is a 4 credit diploma level course in the IITM BS Data Science programme. It teaches you to pick a statistical method for a business question and read the answer like a manager would. You must finish Business Data Management (BSMS2001) first, because the course page lists it as the prerequisite.

The instructor is Prof. Rahul R Marathe of the Department of Management Studies, IIT Madras.

How the course is built

Every week starts with a business situation. Then it shows one statistical technique that helps solve it. So the week titles read like questions, not chapter names. The course runs for 8 weeks.

What you learn

Weeks 1 to 3: Summaries, dashboards and comparing groups

You begin with dashboards and data summaries, and ask how far a good summary can guide a decision. Week 3 asks whether people in different cities prefer different brands. That is a question about comparing groups.

Weeks 4 to 6: Regression in three steps

Regression gets three full weeks. First the basics, using stock returns as the case. Next, checking whether a regression model can be trusted, using a case on how professors are paid. Then logistic regression and its link to classification, using a medical case.

Weeks 7 and 8: Repeated measurements and time

Week 7 uses repeated measures ANOVA to study what happens when people see the same advertisement again and again. Week 8 covers data with a time axis, through time series models.

By the end, you should be able to apply these methods to business problems and make careful forecasts. The course page also expects you to build business models based on data.

How it is assessed

The course page lists weekly online assignments, 2 in-person invigilated quizzes and 1 in-person invigilated end term exam. It does not give the weights. See how Quiz 1 and Quiz 2 work for the general rules.

Where it counts

Business Analytics is the theory half of Option 1 in the Diploma in Data Science. The other half is the BDM Project (BSMS2001P), worth 2 credits. You need both to complete Option 1.

Option 2 uses Introduction to Deep Learning and Generative AI instead. If you pick it, the handbook says you can still take Business Analytics later as a degree level elective. The reverse does not work: finishing Option 1 closes the Option 2 courses at the degree level.

Who finds it hard

• Students who memorised formulas in Statistics 1 and 2 but never asked what the result means. Here the meaning is the whole point.
• Students who get lost in regression output tables, since three of the eight weeks are about regression.
• Students who treat the cases as stories and skip the method, or learn the method and skip the story.

How to prepare

• Before the term, revise hypothesis testing, correlation and simple regression. Our Statistics 1 and 2 guide lists what to focus on.
• For each week, write three lines in your notes: the business question, the method, and what the answer tells the manager.
• Redo the lecture examples yourself in whatever tool the lectures use. The course page does not name a software tool.
• Keep one of the suggested books nearby. The page lists five, including Statistics for Business: Decision Making and Analysis, Managerial Statistics by Gerald Keller, and Statistics for Management by Levin and Rubin.

What to take before and after

Before: Business Data Management (BSMS2001). Alongside or after: the BDM Project. At the degree level, Market Research and Industry 4.0 continue the business side of data work. Prof. Marathe also teaches Industry 4.0.

Common questions

Can I take Business Analytics and BDM in the same term?

The course page lists BDM as a prerequisite, not a corequisite. So plan to finish BDM in an earlier term. If you are unsure, check the registration page before you pay.

Is there an OPPE in Business Analytics?

The course page lists no OPPE. It names only weekly assignments, two in-person quizzes and one in-person end term exam.

I finished Option 1. Can I still study deep learning later?

You cannot take the Option 2 courses at the degree level after finishing Option 1. The handbook says the degree level already has other deep learning courses, and those remain open to you.

Does the course need coding?

The course page does not mention any programming language or tool. It focuses on statistical methods and business decisions.