ML 101: Introduction to Machine Learning

ML 101 is a student-run introduction to machine learning, organised by the Society for Artificial Intelligence and Deep Learning in collaboration with the Center for Technical Education (CTE). It runs in the First Semester of 2026-27, and every lecture is designed and delivered by current members of SAiDL.

The course starts from regression and the fundamentals of how models learn, then moves into deep learning: neural networks, computer vision, attention, transformers, generative AI, and reinforcement learning. By the end you understand not just how modern AI systems are used, but how they are built and why they work.

SAiDL is a student-run, non-profit group of undergraduates at BITS Pilani, Goa working on research and applications of artificial intelligence and deep learning. Its members have collaborated with research groups and companies including Harvard, Brown, MIT, Mila, CMU, INRIA, Google, Microsoft Research, Adobe, and Amazon, among many others.

Prerequisites

None. Some familiarity with Python helps, but it is not a requirement, and we will point you to resources for picking it up alongside the lectures. No prior machine learning or deep learning experience is expected, as everything is built up from scratch during the course.

Lectures

Twelve lectures organised into five units: Foundations (L1 to L4), Vision and Sequences (L5 to L6), Attention and Transformers (L7 to L8), Generative and Modern AI (L9 to L11), and Reinforcement Learning (L12).

The full lecture-by-lecture breakdown is on the lectures page. Days, timings, and venue are on the schedule page.

Resources

Slides for each lecture are linked from the lectures page as the course progresses. Additional reading will be posted alongside them.

Contact

Reach out to any of the instructors, or write to todo@todo.com with questions about the course. Course updates are posted on the announcements page.