401-4632-15L Causality
Semester | Frühjahrssemester 2021 |
Dozierende | C. Heinze-Deml |
Periodizität | jährlich wiederkehrende Veranstaltung |
Lehrsprache | Englisch |
Kurzbeschreibung | In statistics, we are used to search for the best predictors of some random variable. In many situations, however, we are interested in predicting a system's behavior under manipulations. For such an analysis, we require knowledge about the underlying causal structure of the system. In this course, we study concepts and theory behind causal inference. |
Lernziel | After this course, you should be able to - understand the language and concepts of causal inference - know the assumptions under which one can infer causal relations from observational and/or interventional data - describe and apply different methods for causal structure learning - given data and a causal structure, derive causal effects and predictions of interventional experiments |
Voraussetzungen / Besonderes | Prerequisites: basic knowledge of probability theory and regression |