Practical Deep Learning for Coders
Top-down, code-first course teaching how to train, fine-tune, and deploy neural networks in Python.
✓ verified 2026-10-28 all links ok
Why it's here
Jeremy Howard flips traditional academic teaching on its head: you train and deploy a working model in lesson one, then peel back the math layer by layer.
Recommended by Ada Lovelace
What you'll learn
- Lessons 1–3: Training vision/tabular models, deployment, and stochastic gradient descent
- Lessons 4–6: Natural language processing, collaborative filtering, and random forests
- Lessons 7–9: Convolutions, ResNets, and stable diffusion from foundations
Who it's for and time commitment
verified 2026-10-28| Time commitment | 9 lessons, roughly 8 hours per lesson including notebooks |
|---|---|
| Prerequisites | 1 year of coding experience (preferably Python) |
| Compute | Runs on free Kaggle or Colab GPUs |
Study guide
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