Neural networks, architectures (CNNs, RNNs, Transformers), and techniques powering modern AI breakthroughs.
- MIT: Introduction to Deep Learning (6.S191) - MIT's official intro course with lectures, labs, and projects updated annually.
Beginner - fast.ai: Deep Learning for Coders - Practical, top-down deep learning course — build models from day one.
Beginner - Coursera: Deep Learning Specialization - Andrew Ng's 5-course specialization covering CNNs, RNNs, optimization, and structuring ML projects.
Beginner - Stanford CS231n: Deep Learning for Computer Vision - World-class course on CNNs with lecture notes, assignments, and videos.
Intermediate - Stanford CS224n: NLP with Deep Learning - Deep learning applied to natural language with lecture videos and assignments.
Intermediate - NYU: Deep Learning (Yann LeCun) - Full course by Yann LeCun and Alfredo Canziani with notebooks and video lectures.
Intermediate - UC Berkeley: Full Stack Deep Learning - From training models to deploying them in production.
Intermediate - DeepMind x UCL: Deep Learning Lecture Series - Advanced deep learning topics from DeepMind researchers.
Advanced
- Dive into Deep Learning (d2l.ai) - Interactive deep learning book with code in PyTorch, TensorFlow, and JAX.
Beginner - Neural Networks and Deep Learning (Michael Nielsen) - Free online book explaining neural network concepts with clear intuition.
Beginner - Deep Learning Book (Goodfellow, Bengio, Courville) - The definitive deep learning textbook, freely available online.
Advanced - Distill.pub - Clear, interactive, beautifully visualized articles on deep learning research.
All Levels
- PyTorch: Official Tutorials - Step-by-step tutorials from basics to advanced model building.
All Levels - TensorFlow Playground - Interactive browser visualization of neural networks — great for building intuition.
Beginner - Papers With Code: Methods - Browse and understand deep learning architectures with linked implementations.
Intermediate