Mathematical Methods for Artificial Intelligence

Catalog description

This course introduces the mathematical background necessary to understand, design, and effectively deploy AI systems. It focuses on four key areas of mathematics: (1) linear algebra, which enables describing, storing, analyzing and manipulating large-scale data; (2) optimization theory, which provides a framework for training AI systems; (3) probability and statistics, which underpin many machine learning algorithms and systems; and (4) numerical analysis, which illuminates the behavior of mathematical and statistical algorithms when implemented on computers.