This course is designed for students with formal quantitative training to learn mathematical tools that are useful for data-driven analyses in the empirical sciences, in particular cognitive science and neuroscience. The focus is practical; while mathematical derivations will frequently be demonstrated, these will be curated to help give intuition behind the tools rather than to provide an entirely rigorous foundation for the material. Some lectures may provide an overview of many different techniques, while others will delve deep into a single fundamental concept.

Prerequisite: You must have a solid foundation in the following subjects: calculus, differential equations, linear algebra, and probability theory. You should also be proficient at Python. Unfortunately, R is not allowed for this course.

ECTS: 4