Stanford CS230: Deep Learning I Autumn 2025
Andrew Ng and Kian Katanforoosh
The lectures of Stanford’s Autumn 2025 deep learning course. They cover supervised and self-supervised learning, the full cycle of a deep learning project, adversarial robustness and generative models, deep reinforcement learning, agents and RAG, and interpretability, plus talks on AI project strategy and careers. On campus the lectures go with the online Deep Learning Specialization videos, which are not in this playlist.
What you'll learn
- Supervised, self-supervised and weakly supervised learning
- Running a deep learning project from data to deployment
- Adversarial attacks and generative models
- Deep reinforcement learning
- Agents, prompting and RAG
- Interpreting what a model has learned
