Fundamentals to Linear Algebra
20h 53m 19s
English
Paid
Course description
Unleash the power of linear algebra to conquer the world of data science, machine learning, and artificial intelligence. This intensive course will transform you into a master of mathematics, ready to tackle real-world challenges with practical skills and unwavering confidence.
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/ #1: Welcome Message
All Course Lessons (35)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | Welcome Message Demo | 14:18 | |
| 2 | Linear Algebra RoadMap 2024 | 19:12 | |
| 3 | Pre-Requisites Introduction | 09:03 | |
| 4 | Refreshment - Norms & Euclidean Distance | 10:31 | |
| 5 | Refreshment - Real Numbers and Vector Space | 04:14 | |
| 6 | Refreshment - Cartesian Coordinate System & Unit Circle | 04:45 | |
| 7 | Refreshment - Angles, Unit Circle and Trigonometry | 13:24 | |
| 8 | Refreshment - Pythagorean Theorem & Orthogonality | 05:25 | |
| 9 | Why these Pre-Requisites Matter | 02:28 | |
| 10 | Module 2.1: Foundations of Vectors | 30:55 | |
| 11 | Module 2.2: Special Vectors and Operations | 56:53 | |
| 12 | Module 2.3: Part 1 - Scalar Multiplication | 25:06 | |
| 13 | Module 2.3 Part 2 - Linear Combination and Unit Vectors | 47:10 | |
| 14 | Module 2.3 Part 3 - Span of Vectors | 40:06 | |
| 15 | Module 2.3: Part 4 - Linear Independence | 31:53 | |
| 16 | Module 2.4: Dot Product, Cauchy-Schwarz Inequality and Its | 01:29:45 | |
| 17 | Module 1: Foundations of Linear Systems and Matrices | 16:50 | |
| 18 | Module 2: Introduction to Matrices | 30:01 | |
| 19 | Module 3: Core Matrix Operations | 35:01 | |
| 20 | Module 4: Part 1 Solving Linear Systems - Gaussian Reduction | 47:23 | |
| 21 | Module 4: Part 2 Solving Linear Systems - Gaussian Reduction | 01:07:47 | |
| 22 | Module 4: Part 3 Solving Linear Systems - Gaussian Reduction | 01:10:00 | |
| 23 | Module 4: Part 4 Solving Linear Systems - Gaussian Reduction | 53:47 | |
| 24 | Module 1: Algebraic Laws for Matrices | 56:31 | |
| 25 | Module 2: Determinants and Their Properties | 50:52 | |
| 26 | Module 3: Matrix Inverses and Identity Matrix | 01:03:32 | |
| 27 | Module 4: Transpose of Matrices: Properties and Applications | 23:15 | |
| 28 | Module 1: Part 1 Basis of Vector Space | 35:39 | |
| 29 | Module 1: Part 2 Vector Projection and Calculation | 41:12 | |
| 30 | Module 1: Part 3 Gram-Schmidt Process | 36:53 | |
| 31 | Module 2: Special Matrices and Their Properties | 14:39 | |
| 32 | Module 3: Matrix Factorization, Examples and Applications | 27:03 | |
| 33 | Module 4: QR Decomposition Overview | 42:52 | |
| 34 | Module 5: Eigenvalues, Eigenvectors, and Eigen Decomposition | 01:16:31 | |
| 35 | Module 6: Singular Value Decomposition (SVD) | 58:23 |
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