- Intro to ML
- Probability
- Linear Algebra
- Neural Networks
- Sequence Models
- Deep Learning for vision
- Recommender Systems
- Generative Models
- Reinforcement Learning
- Graphs and ML
- Matching Networks
- Monte Carlo Methods
- Advanced ( stable diffusion, Flamingo, multimodal, joint learning)