1. Are there discounts available?

Yes. Other than the two baseline prices for regular and academic participants, we offer discounts for multiple participants from the same company and for participants from low-income countries. Contact in case you are in one of these categories.

2. Will I get access to the teaching materials?

Yes, we will share all teaching materials with our participants. You will be sent a link to download all lecture notes, teaching apps and Python notebooks.

3. Can I cancel my registration?

Please cancel your registration on eventbrite. The course fee will be refunded if the participation is cancelled no later than 30 days before the course. eventbrite fees are not refundable.

4. Why Causal Machine Learning?

Machine Learning has revolutionized the world. In most cases, ML methods have been used for prediction purposes. However, the most important questions are causal. Managers wonder if a certain service is profitable or not, whether certain production processes improve the quality of the final product and how to optimally allocate resources. Causal Machine Learning makes it possible to combine the predictive power of ML algorithms with causal modelling.

5. What is Double Machine Learning?

Double Machine Learning is a general approach to Causal Machine Learning. In short, all ML algorithms introduce some form of regularization in order to handle complex or high-dimensional data. Double Machine Learning explicitly addresses the consequences of such a regularization in the context of causal inference. It is based on three key ingredients:

  1. Neyman Orthogonality
  2. High-Quality ML Learners
  3. Sample Splitting (a.k.a. Cross-Fitting)

As a result, Double Machine Learning offers inference procedures like valid statistical tests based on estimation with ML.

Curious? Check out the upcoming classes and join our trainings to learn more!