Phase 01

Math Foundations

Phase 1: Math Foundations. 22 hands-on lessons building AI from first principles in the browser. Free reading; graded exercises and certificate with lifetime access.

  1. Linear Algebra Intuition (graded)
  2. Vectors, Matrices & Operations (graded)
  3. Matrix Transformations (graded)
  4. Calculus for Machine Learning (graded)
  5. Chain Rule & Automatic Differentiation (graded)
  6. Probability and Distributions (graded)
  7. Bayes' Theorem (graded)
  8. Optimization (graded)
  9. Information Theory (graded)
  10. Dimensionality Reduction (graded)
  11. Singular Value Decomposition (graded)
  12. Tensor Operations (graded)
  13. Numerical Stability (graded)
  14. Norms and Distances (graded)
  15. Statistics for Machine Learning (graded)
  16. Sampling Methods (graded)
  17. Linear Systems (graded)
  18. Convex Optimization (graded)
  19. Complex Numbers for AI (graded)
  20. The Fourier Transform (graded)
  21. Graph Theory for Machine Learning (graded)
  22. Stochastic Processes (graded)
0 lifetime access. Curriculum based on AI Engineering from Scratch by Rohit Ghumare (MIT, used under attribution).