Machine Learning for Physicists and Astronomers

Utbildningsfakta

Kod: FK7068

Machine learning is one of the fastest growing and most dynamic areas of modern physics research and data application. This course gives an introduction to the core concepts, theory and tools of machine learning as required by physicists addressing practical data analysis tasks. Use cases and limitations of machine learning algorithms will be discussed. The implementation and use of machine learning in practical applications will be exemplified, and realistic scenarios will be studied in applications relevant to physics research and astronomy.

Behörighet

Admission to the course requires knowledge equivalent to passed courses (excluding introductory courses) of 45 credits in mathematics and 60 credits in physics, where the courses Programming, Numerical Methods and Statistics for Physicists, 15 credits (FK4026), and Mathematics II - Linear Algebra, 7.5 credits (MM5012) should be included. Additionally, requires knowledge equivalent to upper secondary school English B/English 6.

Utbildningstillfällen

Varje tillfälle har egna datum och villkor. Avslutade tillfällen behålls som historik och innebär inte att en ny ansökan är öppen.

• Machine Learning for Physicists and Astronomers

  Stockholm University

  Startdatum: 19 januari 2026

  Slutdatum: 22 mars 2026

  Studietakt: 50 %