Computational Methods
This course introduces computational algorithms solving problems from a variety of scientific disciplines. Mathematical models describing a phenomenon of interest are typically too complex to construct analytical solutions, leading us to numerical methods. Motivated by models from physics, biology, and medicine, students will develop numerical algorithms and mathematically analyze their accuracy, efficiency, and convergence properties. Students will be expected to implement computational algorithms to verify their understanding of the theoretical results, but developing programming skills is not the main focus of the course. Sample topics include matrix decompositions, inverse problems, optimization, data fitting, and differential equations.
Prerequisites & course information
Prerequisite MATH 23 and ( MATH 22 or MATH 24 ). Recommended Preparation: COSC 1 , ENGS 20 , or Experience with programming.
Sources
- Course catalogue ↗2026-2027