On 30 and 31 May 2023, the School for Information and Knowledge Systems (SIKS) is organising the SIKS-course “Causal Inference”. The course will be given in English and is part of the Educational Program for SIKS PhD students. Although these courses are primarily intended for SIKS PhD students, other participants will not be excluded. However, their number of passes will be restricted and will depend on the number of SIKS PhD students taking the course.
Cause-effect relations are of central interest in many fields of science. How well does a new medicine cure a disease? Will a new government policy lead to a fairer distribution of wealth? We want to use data to answer these questions, but a straightforward application of standard methods from machine learning or statistics may give you misleading answers to questions such as these.
Causal inference provides the tools to answer these causal questions correctly, both qualitatively and quantitatively. It has originally been studied by statisticians, and has now also become a topic of great interest for machine learners. On the first day of this course, the focus is on the approach to causal inference initiated by Judea Pearl, which has become popular in machine learning. On the second day, you will learn about the potential outcomes framework, which is used by statisticians to answer a wide variety of questions. Both days will start with a more introductory lecture, followed by several more advanced topics.
LOCATION: Mitland Hotel , Utrecht
DATE: 30 and 31 May 2023
- Prof. dr. Joris Mooij (UvA)
- Dr. Thijs van Ommen (UU)
The full programme will be made available soon
Registration for this course is now open. Please note that option 1 includes an overnight stay at the hotel, whereas option 2 includes meals but no overnight stay. The number of rooms may be limited so please consider this, especially if you live in the Utrecht area.
Information for non-SIKS PhD students
SIKS needs a confirmation from your supervisor/office that they agree with the arrangement and paying conditions.