19 August – 22 August, 2024, at 10:00 – 15:00 at LUSEM. 

Instructor: Anthony Strittmatter, Ph.D. (UniDistance Switzerland and Amazon)

Introductory, Ph.D.-level course in causal machine learning.

• No prior knowledge of machine learning is needed.
• Open for Ph.D. students, postdocs, and faculty.
• Content: predictive versus causal methods; dealing with high-dimensional confounders; impact evaluation using machine learning.
• Hands-on exercise sessions in R. 
• 3 ECTS credits for completing a homework assignment (optional). 

Contact Petra Thiemann at petra [dot] thiemann [at] nek [dot] lu [dot] se (petra[dot]thiemann[at]nek[dot]lu[dot]se)  if you have any questions!

Course participation is free, thanks to generous support by the Arne Ryde Foundation.

Sign up until March 15, 2024!

To sign up, use the QR code or email petra [dot] thiemann [at] nek [dot] lu [dot] se.