Topological Data Analysis

Topological Data Analysis

Course contents: Methods from computational topology have in recent years become an important tool in data analysis. This course offers an introduction to persistent homology, which is one of the main techniques in topological data analysis. We will cover the underlying mathematical theory, study concrete examples from applications in the natural sciences (like for example critical mutations in the evolution of viruses), and do some computer programming in order to see how the theory works in practice. For more information, and to access the course material, please sign up for this course through ILIAS.

Intended audience: everyone with a background in mathematics/computer science/natural sciences

Prerequisites: basic linear algebra and calculus

Credit points: 6 (Modul M-MATH-105487)

Course format: 3+1 SWS; online; asynchronous (lectures) / synchronous (exercise classes)