Course Descriptions

16:642:550 - Linear Algebra and Applications

Fall 2021 - Tsai, Li-Cheng

Course Description:

This is a course aiming at graduate students in science, engineering, and statistics. The course covers Gauss elimination, vector spaces, linear transformations, determinants, eigenvalues and eigenvectors, with applications to least squares approximations, discrete Fourier transform, differential equations, Markov chain, and principal component analysis. The course will be accompanied by labs.

Text:

Linear Algebra with Applications, by W. Keith Nicholson (Open access under Creative Commons License)

Prerequisites:

Familiarity with matrices, vectors, complex numbers, and mathematical reasoning at the level of advanced undergraduate mathematics courses.

 

Schedule of Sections

Previous semesters: