Big Data Science in Astronomy - Einzelansicht

Due to the COVID-19 pandemic, this course will be taught online. All lectures will be recorded on video, and will be available together with the lecture slides on the course Moodle page. Lectures will be uploaded every Thursday, starting April 23.

After signing up for this course in PULS, I will send you an email with the Moodle course enrollment key. Once you have received the email with the enrollment key, please search for BigDataAstro20 in Moodle or enter https://moodle2.uni-potsdam.de/course/view.php?id=23644

Introduction to Astronomy and Astrophysics

3 CP with 50% of the total points in bi-weekly exercises

This course will give an overview on data mining and machine learning techniques and their applications in the analysis of current and upcoming large astronomical data sets (e.g. SDSS, Pan-STARRS, DESI, 4MOST, LSST). Addressed topics include (1) classical and Bayesian statistical inference, (2) supervised machine learning for object classification and regression problems, (3) unsupervised machine learning and dimensionality reduction techniques, (4) time series analyis of variable sources.

MSc Astrophysics, MSc Physics, MSc Computational Science, MSc Data Science, graduate students