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  1. Урок 1. 00:14:18
    Welcome Message
  2. Урок 2. 00:19:12
    Linear Algebra RoadMap 2024
  3. Урок 3. 00:09:03
    Pre-Requisites Introduction
  4. Урок 4. 00:10:31
    Refreshment - Norms & Euclidean Distance
  5. Урок 5. 00:04:14
    Refreshment - Real Numbers and Vector Space
  6. Урок 6. 00:04:45
    Refreshment - Cartesian Coordinate System & Unit Circle
  7. Урок 7. 00:13:24
    Refreshment - Angles, Unit Circle and Trigonometry
  8. Урок 8. 00:05:25
    Refreshment - Pythagorean Theorem & Orthogonality
  9. Урок 9. 00:02:28
    Why these Pre-Requisites Matter
  10. Урок 10. 00:30:55
    Module 2.1: Foundations of Vectors
  11. Урок 11. 00:56:53
    Module 2.2: Special Vectors and Operations
  12. Урок 12. 00:25:06
    Module 2.3: Part 1 - Scalar Multiplication
  13. Урок 13. 00:47:10
    Module 2.3 Part 2 - Linear Combination and Unit Vectors
  14. Урок 14. 00:40:06
    Module 2.3 Part 3 - Span of Vectors
  15. Урок 15. 00:31:53
    Module 2.3: Part 4 - Linear Independence
  16. Урок 16. 01:29:45
    Module 2.4: Dot Product, Cauchy-Schwarz Inequality and Its
  17. Урок 17. 00:16:50
    Module 1: Foundations of Linear Systems and Matrices
  18. Урок 18. 00:30:01
    Module 2: Introduction to Matrices
  19. Урок 19. 00:35:01
    Module 3: Core Matrix Operations
  20. Урок 20. 00:47:23
    Module 4: Part 1 Solving Linear Systems - Gaussian Reduction
  21. Урок 21. 01:07:47
    Module 4: Part 2 Solving Linear Systems - Gaussian Reduction
  22. Урок 22. 01:10:00
    Module 4: Part 3 Solving Linear Systems - Gaussian Reduction
  23. Урок 23. 00:53:47
    Module 4: Part 4 Solving Linear Systems - Gaussian Reduction
  24. Урок 24. 00:56:31
    Module 1: Algebraic Laws for Matrices
  25. Урок 25. 00:50:52
    Module 2: Determinants and Their Properties
  26. Урок 26. 01:03:32
    Module 3: Matrix Inverses and Identity Matrix
  27. Урок 27. 00:23:15
    Module 4: Transpose of Matrices: Properties and Applications
  28. Урок 28. 00:35:39
    Module 1: Part 1 Basis of Vector Space
  29. Урок 29. 00:41:12
    Module 1: Part 2 Vector Projection and Calculation
  30. Урок 30. 00:36:53
    Module 1: Part 3 Gram-Schmidt Process
  31. Урок 31. 00:14:39
    Module 2: Special Matrices and Their Properties
  32. Урок 32. 00:27:03
    Module 3: Matrix Factorization, Examples and Applications
  33. Урок 33. 00:42:52
    Module 4: QR Decomposition Overview
  34. Урок 34. 01:16:31
    Module 5: Eigenvalues, Eigenvectors, and Eigen Decomposition
  35. Урок 35. 00:58:23
    Module 6: Singular Value Decomposition (SVD)