Honors Numerical Analysis
This course will cover the analysis of numerical algorithms which are ubiquitously used to solve problems throughout mathematics, physics, engineering, finance, and the life sciences. Topics include: algorithms for solving nonlinear equations; optimization; finding eigenvalues/eigenvectors of matrices; computing matrix factorizations and performing linear regressions; function interpolation, approximation, and integration; basic signal processing using the Fast Fourier Transform; Monte Carlo simulation. An introduction to programming will be provided as it is an integral part of numerical analysis, but students should feel quite comfortable programming on their own (or be exceptionally willing to learn along the way). | Prerequisites: (Grade of A- or above in MA-UY 2114 OR grade of B+ or above in MA-UY 2514 ) AND ((grade of A- or above in MA-UY 1044 OR MA-UY 3113) OR grade of B+ or above in MA-UY 3054 ) AND programming experience strongly recommended (e.g. julia, Matlab, or numpy) but not required (there is a programming component to this course). Anti-Requisites: MA-UY 4424
Topics
- algorithms for solving nonlinear equations
- optimization
- finding eigenvalues/eigenvectors of matrices
- computing matrix factorizations and performing linear regressions
- function interpolation
- approximation
- and integration
- basic signal processing using the Fast Fourier Transform
- Monte Carlo simulation
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027