Video Series
Introduction to Deep Learning
A lecture series covering the foundations of deep learning, from neural networks to generative models. Designed for students and practitioners who want to understand the mathematics and intuition behind modern AI systems.
Introduction and Overview
Course structure, prerequisites, and the landscape of deep learning in 2026
Neural Networks and Backpropagation
From perceptrons to multilayer networks, gradient computation, and training dynamics
Convolutional Neural Networks
Image recognition, feature hierarchies, and the architectures that transformed computer vision
Recurrent Neural Networks and Attention
Transformers and Large Language Models
Generative Adversarial Networks
Diffusion Models
Reinforcement Learning Foundations
Deep Reinforcement Learning
Graph Neural Networks
AI Safety and Alignment
The Future of Deep Learning