Learn AI Create the Future — with Pranay
Main site

All sections

The whole curriculum, grouped into 14 areas. Start at the top if you are new. If you came here for one thing, filter to its area or search — everything is on this page or one click from it.

Every lesson here is written by .

14 areas 117 sections 1,162 of 1,167 lessons published 10 new lessons every day

Showing Safety, Ethics and Law — 2 sections, 20 lessons. Show all 14 areas

Safety, Ethics and Law

Bias, privacy, safety and the rules — the part that decides whether a system should be built at all.

2 sections 20 of 20 lessons published

AI Safety and Ethics

How AI goes wrong, who it hurts, and what you can actually do about it as a developer.

13 published

  1. Why AI safety matters
  2. Bias in datasets
  3. Fairness metrics
  4. Explainability
  5. SHAP and LIME
  6. Privacy in machine learning
  7. Differential privacy
  8. Federated learning
  9. Adversarial attacks
  10. Prompt injection
  11. Model cards and documentation
  12. AI regulation
  13. Deploying responsibly

Other ways to use this site

Learning paths

An ordered route through the lessons for one job: ML developer, AI engineer, computer vision engineer.

Projects

Build real things with full code, a dataset and a deployment guide.

AI glossary

Every term you keep seeing, defined in one plain sentence first.

Error database

Paste the error you got. Find out what it means and how to fix it.