MATH 5110 - Computational Linear Algebra with Python

This course covers basic concepts of algorithms for solving problems in linear algebra. Theoretical and experimental results will be studied with an emphasis on cost, stability, and convergence. Students will implement and analyze direct and iterative algorithms for solving linear systems, calculate eigenvalues and eigenvectors, and perform matrix decompositions. Applications to a variety of areas will be explored. Learning and using Python and the NumPy library form an essential component of the course. Details of the language will be developed concurrently with necessary algorithms, so knowledge of Python is not required. Some prior programming experience is helpful but not required.

Note: Distance Learning Approved

Credits: 3

Prereq: Acceptance into the Masters in Mathematical Sciences
Lecture hours: 3