- Lectures 2 & 3: Exploring Gradient Descent and Introduction to Backpropagation
- Lecture 4: Understanding Stochastic Gradient Descent
- Lectures 5 & 6: Navigating Numpy and PyTorch: Broadcasting and Acceleration and Supervised Learning
- Lectures 7 & 8: Constructing an Autograd Engine from Scratch
- Lecture 9: Exploring (Computational) Graph Traversal Algorithms