Numerical Linear Algebra

Catalog description

This course focuses on computational algebra methods and their applications, using basic programming with Matlab or Python. Topics should include: Direct methods (gauss elimination), Iterative methods (CG and GMRES), QR/ Gram Schmidt, Eigen decomposition, SYD and applications (matrix norms, condition number, low rank approximation, principal component analysis, linear regression). Extra time can be used for applications and projects, or discussion of sparse and structured matrix methods. Prerequisite Course(s): Prerequisites: MATH 310 Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3