[w23/24 ]Knowledge Discovery and Data Mining

[w23/24] System Development

[w23/24]Algorithm Design

[w23/24] Statistical Reasoning and Inference 1 (Kauermann)

[ws23/24] Seminar: Machine Learning Meets Causality (Bothmann, Dandl)

Login: Please contact Susanne Dandl 

Target group: Master Data Science

Course Description:

For decades, research in machine learning and causality progressed independently of each other. This seminar sheds light on the recent advances on the intersection between the two, which can be classified into two primary areas:

(1) How can machine learning algorithms contribute to causality? Examples are the estimation of heterogeneous treatment effects and causal structure learning.

(2) How can causal knowledge enhance machine learning models, for example, w.r.t. their generalizability, interpretability, and fairness?



[w23/24] Advanced Statistical Modeling (Buttazzo)

[ws 23/24] Data Ethics and Data Security

[ws 23/24] Multivariate Statistics (Casalicchio)

Schedule

  • Class: Tuesday, 12 - 14 c.t.

    Enrollment key

    • This class is only for students enrolled in the elite master program Data Science.  You should have received the enrollment key via e-mail.
    • If not, please let me know via e-mail giuseppe.casalicchio[at]stat.uni-muenchen.de to ask for the enrollment key.


    [ws 23/24] DS Practicals