Ajay Shenoy

1. Sample space, conditional probability, Bayes theorem
2. Random variables, join distribution
3. Conditional expectation
4. KL Divergence, cross entropy, maximum likelihood and applications (Logistic Regression, Linear Regression, VAE, Diffusion, GANs)
5. Intro to Reinforcement Learning (Basic definitions, RL framework, Policy gradient, Deepseek)

July 8th to August 14th

Live session: Tuesdays and Thursdays, 9:00 PM to 11:00 PM (IST)

Office hours: Saturdays and Sundays, 2:30 PM to 4:00 PM (IST)

Recordings of live sessions will be available.

First few registrants can avail a few discount coupons:

FLAT20 - for 20%