Math for AI
The mathematical foundations every AI/ML engineer needs - from linear algebra and calculus to Bayesian statistics and statistical learning theory.
10 Modules
| # | Module | Level | Lessons |
|---|---|---|---|
| 01 | Linear Algebra | Beginner | 10 |
| 02 | Calculus & Optimization | Beginner | 8 |
| 03 | Probability Theory | Beginner | 8 |
| 04 | Statistics for ML | Intermediate | 8 |
| 05 | Information Theory | Intermediate | 7 |
| 06 | Bayesian Statistics | Intermediate | 8 |
| 07 | Statistical Learning Theory | Advanced | 7 |
| 08 | Numerical Methods | Intermediate | 7 |
| 09 | Graph Theory | Intermediate | 6 |
| 10 | Time Series Mathematics | Advanced | 7 |
Start with Linear Algebra - it underpins every other module.
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