2026-10-05 - 2026-10-09
Hier geht es zur AnmeldungIvelina Momcheva
Max Planck Institute for Astronomy
Modern astronomy is intricately tied to data science by necessity: surveys like the Sloan Digital Sky Survey, Euclid and the Rubin Large Survey of Space and Time are producing catalogs of billions of objects, far beyond what traditional analysis can handle by hand.This block course offers an introduction to contemporary astronomical research topics, each paired with a subject in machine learning such as regression, unsupervised clustering, and convolutional neural networks, among others. The course includes hands-on sessions using data provided by the instructor, in which students work through and produce a functioning implementation over the course of each class. Students will walk away with solid, practical insight into modern astronomical techniques, as well as a set of worked, implemented examples they can adapt and build on in their own research.
