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MIT OpenCourseWare

Linear Algebra

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. 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 )

Instructor

Prof. Gilbert Strang,

Mathematics

2009

Lecture 21 - Cramer's Rule, Inverse Matrix and Volume

Lecture 22 - Eigenvalues and Eigenvectors

Lecture 23 - Diagonalization and Powers of A

Lecture 24 - Differential Equations and exp(At)

Lecture 25 - Markov Matrices; Fourier series

Lecture 26 - Exam 2 Review

Lecture 27 - Symmetric Matrices and Positive Definiteness

Lecture 28 - Complex Matrices; Fast Fourier Transform

Lecture 29 - Positive Definite Matrices and Minima

Lecture 30 - Similar Matrices and Jordan Form

Lecture 31 - Singular Value Decomposition

Lecture 32 - Linear Transformations and their Matrices

Lecture 33 - Change of Basis; Image Compression

Lecture 34 - Left and Right Inverses; Pseudoinverse

Lecture 35 - Exam 3 Review

Lecture 36 - Final Course Review