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18.06SC Linear Algebra (Fall 2011, MIT OCW). Taught by Prof. Gilbert Strang, this course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics and social sciences, natural sciences, and engineering.

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Description

This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include: a complete set of lecture videos, summary notes, problem solving videos, and a full set of exams and solutions. (from ocw.mit.edu)

https://www.youtube.com/watch?v=hNDFwVVKVk0&ab_channel=MITOpenCourseWare

Course content

    • Lecture 01 – The Geometry of Linear Equations Unlimited
    • Lecture 02 – An Overview of Key Ideas Unlimited
    • Lecture 03 – Elimination with Matrices Unlimited
    • Lecture 04 – Multiplication and Inverse Matrices Unlimited
    • Lecture 05 – Factorization into A = LU Unlimited
    • Lecture 06 – Transposes, Permutations, Vector Spaces Unlimited
    • Lecture 07 – Column Space and Nullspace Unlimited
    • Lecture 08 – Solving Ax = 0: Pivot Variables, Special Solutions Unlimited
    • Lecture 09 – Solving Ax = b: Row Reduced form R Unlimited
    • Lecture 10 – Independence, Basis and Dimension Unlimited
    • Lecture 11 – The Four Fundamental Subspaces Unlimited
    • Lecture 12 – Matrix Spaces; Rank 1; Small World Graphs Unlimited
    • Lecture 13 – Graphs, Networks, Incidence Matrices Unlimited
    • Lecture 14 – Exam 1 Review Unlimited
    • Lecture 15 – Orthogonal Vectors and Subspaces Unlimited
    • Lecture 16 – Projections onto Subspaces Unlimited
    • Lecture 17 – Projection Matrices and Least Squares Unlimited
    • Lecture 18 – Orthogonal Matrices and Gram-Schmidt Unlimited
    • Lecture 19 – Properties of Determinants Unlimited
    • Lecture 19 – Properties of Determinants Unlimited
    • Lecture 20 – Determinant Formulas and Cofactors Unlimited
    • Lecture 21 – Cramer’s Rule, Inverse Matrix and Volume Unlimited
    • Lecture 22 – Eigenvalues and Eigenvectors Unlimited
    • Lecture 23 – Diagonalization and Powers of A Unlimited
    • Lecture 24 – Differential Equations and exp(At) Unlimited
    • Lecture 25 – Markov Matrices; Fourier series Unlimited
    • Lecture 26 – Exam 2 Review Unlimited
    • Lecture 27 – Symmetric Matrices and Positive Definiteness Unlimited
    • Lecture 28 – Complex Matrices; Fast Fourier Transform Unlimited
    • Lecture 29 – Positive Definite Matrices and Minima Unlimited
    • Lecture 30 – Similar Matrices and Jordan Form Unlimited
    • Lecture 31 – Singular Value Decomposition Unlimited
    • Lecture 32 – Linear Transformations and their Matrices Unlimited
    • Lecture 33 – Change of Basis; Image Compression Unlimited
    • Lecture 34 – Left and Right Inverses; Pseudoinverse Unlimited
    • Lecture 35 – Exam 3 Review Unlimited
    • Lecture 36 – Final Course Review Unlimited

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