Course ID: BSMA1003
Course Credits: 4
Course Type: Foundational
Pre-requisites: BSMA1001 - Mathematics for Data Science I
Faculty:
Dr. Sarang S Sane
Assistant Professor, Department of Mathematics, IIT Madras
Course instructors:
Lavanya S
Prerak Deep
Prescribed Books:
The primary study material will be the videos and the assignments posted on the course portal.
One may also refer to:
Title: Mathematics for Machine Learning Author: Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. Publisher: Cambridge University Press ISBN: 9781108455145
(The PDF of this book is currently available freely at https://mml-book.github.io/book/mml-book.pdf)
Title: Vector Calculus (By Michael Corral) (Available freely online)
The learners are advised to make best use of the interaction sessions with the course support members to clarify their doubts.
Suggested way to attempt the assignments: 1. Watch the lectures. 2. Attempt solve with us assignment. 3. Attempt Activity questions of each lecture. 4. Attempt practice assignments. 5. Attempt graded assignment.
Course Website Link: Click here
📐 Mathematics for Data Science II — Complete Course Playlist
Dive into Mathematics for Data Science II, an in-depth YouTube playlist that builds your mathematical foundation for advanced data science concepts. This series is tailored for learners who want to strengthen their understanding of essential mathematical tools used in data analysis, machine learning, and computational modeling. Covering topics such as vectors, matrices, determinants, systems of linear equations, and more, each video is structured to help you grasp both theory and real-world applications with clarity and confidence. Whether you’re preparing for academic courses, competitive exams, or a career in data science, this playlist equips you with the mathematical insights needed to excel in the field.