AAI601O Mathematics for Applied AI

[3–0, 3 cr.]

This course covers the mathematical principals required for the various concepts in the area of applied artificial intelligence. This course aims at delivering the mathematical topics in a balance manner based on solid theoretical foundation while focusing on the computational aspects and application to data problem. Topics covered include linear algebra, multivariate calculus, optimization, regression, statistics of datasets, orthogonal projections, principal component analysis, and probability. The course provides computational and practical examples of the covered topics.