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Quick Summary: Mathematics for Data Science I (course code BSMA1001) is a 4-credit foundation course and one of the four qualifier subjects in the IIT Madras BS in Management & Data Science. It is pre-calculus done properly — sets, functions, coordinate geometry, quadratics, logs and an introduction to limits. No prior maths degree needed. This guide covers the syllabus, focus areas and a study plan.

📋 Table of Contents

Where this course fits
Syllabus — topic by topic
What to focus on
Study plan
Common mistakes
FAQs

Where this course fits

Maths I appears twice in your journey: it is one of the four courses you are tested on in the Qualifier, and it is a full 12-week course once you enrol in the Foundation level. Getting strong at it early therefore pays off twice. It is designed for learners from any stream, so it starts from the basics and builds up.

Syllabus — topic by topic

Sets, relations & functions — the language everything else is written in
Coordinate geometry — points, distance, and straight lines (slope, intercepts)
Quadratic functions & polynomials — roots, factorisation, graphs
Exponential & logarithmic functions — properties and graphs
Sequences & series — arithmetic and geometric progressions
Introduction to limits & derivatives — the first taste of calculus

Exact week-wise content is on the official student portal; treat the above as the reliable topic map.

💡 Pro Tip: Functions and graphs are the backbone. If you can sketch and interpret a function confidently, most of the rest becomes visual and intuitive.

What to focus on

The highest-return topics are functions (including exponential and log), straight lines, and quadratics — they recur throughout the course and the assignments. Limits are introduced gently; understand the idea rather than memorising rules. Since your qualifier eligibility depends on assignment scores, practise the assignment-style problems until they are automatic.

Study plan

Weeks 1–2: Sets, relations, functions + coordinate geometry.
Weeks 3–4: Quadratics, polynomials, exponentials and logarithms.
Weeks 5–6: Sequences & series, then limits and basic derivatives.
Throughout: Do every graded assignment on time — that is your qualifier eligibility score.

Common mistakes

❌ Memorising formulas without understanding function graphs.
❌ Rushing log and exponential rules — they trip up many learners.
❌ Leaving assignments to the last day.
❌ Skipping practice because a topic “looks familiar” from school.

Frequently Asked Questions (FAQs)

Is Maths I hard for non-maths students?

No — it is built for mixed backgrounds and starts from fundamentals. Regular practice matters more than your Class 12 stream.

How many credits is it?

Mathematics for Data Science I is a 4-credit foundation course delivered over 12 weeks of video lectures and assignments.

Want guided classes & practice for Maths I and the qualifier?

Explore Qualifier Prep →

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