Mathematical Methods in Data Science.

Catalog description

Many students entering quantitative graduate programs have encountered key mathematical tools in a mechanical way but without conceptual depth. This course deepens understanding of vector spaces, linear maps, spectral methods, probability, and optimization, all framed through data-relevant examples. The emphasis is on a rigorous treatment, assuming a few standard prerequisites.