Course Description
Learn the mathematics behind machine learning, statistics, optimization, probability, neural networks, data analysis, and modern intelligent systems.
What You'll Learn
- Build mathematical intuition from fundamentals to advanced applications.
- Solve structured practice problems and exam-grade challenges.
- Apply mathematics to engineering, AI, and research scenarios.
- Gain confidence with concept-first visual instruction.
Curriculum
1. Bayes Theorem Tutorial
Presentation Presentation lesson: Bayes Theorem Tutorial
2. Chain Rule In Neural Networks
Presentation Presentation lesson: Chain Rule In Neural Networks
3. Convex Optimization Tutorial
Presentation Presentation lesson: Convex Optimization Tutorial
4. Descriptive Statistics Tutorial
Presentation Presentation lesson: Descriptive Statistics Tutorial
5. Determinants Tutorial Corrected
Presentation Presentation lesson: Determinants Tutorial Corrected
6. Determinants Tutorial With Brackets Corrected
Presentation Presentation lesson: Determinants Tutorial With Brackets Corrected
7. Determinants Tutorial With Solutions
Presentation Presentation lesson: Determinants Tutorial With Solutions
8. Eigenvalues And Eigenvectors Tutorial
Presentation Presentation lesson: Eigenvalues And Eigenvectors Tutorial
9. Expect Variance Covariance Tutorial
Presentation Presentation lesson: Expect Variance Covariance Tutorial
10. Expectation Variance Covariance Tutorial
Presentation Presentation lesson: Expectation Variance Covariance Tutorial
11. Hypothesis Testing And Confidence Intervals Tutorial
Presentation Presentation lesson: Hypothesis Testing And Confidence Intervals Tutorial
12. Inferential Statistics Tutorial With Math
Presentation Presentation lesson: Inferential Statistics Tutorial With Math
13. Integer Programming Tutorial
Presentation Presentation lesson: Integer Programming Tutorial
14. Linear Algebra Tutorial Unicode
Presentation Presentation lesson: Linear Algebra Tutorial Unicode
15. Linear Algebra Tutorial Practice Solutions
Presentation Presentation lesson: Linear Algebra Tutorial Practice Solutions
16. Linear Programming Tutorial
Presentation Presentation lesson: Linear Programming Tutorial
17. Markov Chains Tutorial With Notes
Presentation Presentation lesson: Markov Chains Tutorial With Notes
18. Mathematics For AI
Presentation Presentation lesson: Mathematics For AI
19. Mathematics For Computers
Presentation Presentation lesson: Mathematics For Computers
20. Matrix Operations Tutorial Enhanced
Presentation Presentation lesson: Matrix Operations Tutorial Enhanced
21. Maximum Likelihood Estimation Tutorial
Presentation Presentation lesson: Maximum Likelihood Estimation Tutorial
22. Monte Carlo Methods Tutorial
Presentation Presentation lesson: Monte Carlo Methods Tutorial
23. Monte Carlo Methods Tutorial With Voice Over
Presentation Presentation lesson: Monte Carlo Methods Tutorial With Voice Over
24. Neural Networks Tutorial
Presentation Presentation lesson: Neural Networks Tutorial
25. Nonlinear Programming Tutorial
Presentation Presentation lesson: Nonlinear Programming Tutorial
26. Optimization Tutorial
Presentation Presentation lesson: Optimization Tutorial
27. Probability And Statistics Tutorial
Presentation Presentation lesson: Probability And Statistics Tutorial
28. Probability Distributions And Statistical Inference Tutorial
Presentation Presentation lesson: Probability Distributions And Statistical Inference Tutorial
29. Random Variables And Distributions Tutorial
Presentation Presentation lesson: Random Variables And Distributions Tutorial
30. Regression Analysis Tutorial
Presentation Presentation lesson: Regression Analysis Tutorial
31. Stochastic Processes Tutorial
Presentation Presentation lesson: Stochastic Processes Tutorial
32. Updated Monte Carlo Methods Tutorial
Presentation Presentation lesson: Updated Monte Carlo Methods Tutorial
33. Vectors And Matrices Tutorial
Presentation Presentation lesson: Vectors And Matrices Tutorial