Introduction to Causal Inference

3 credits

The courses is for professionals and part of the programme MAISTR ( where participants can study the entire programme or individual courses. The course is part of the course track machine learning and is held online in English.
This course contain the definition of cause and effect, Randomized Experiments, do-calculus and graphical models. The primary content of the course answers the following questions:
Why causal inference? How causal inference can improve decision making?
What would be the potential outcome given a certain decision?
How to represent different causal relations in terms of what causes what?
How can machine learning methods take advantage of causal inference concepts?

Spring 2025 (Distance (Internet), Varied, 12%)


Advanced level

Application code:


Entry requirements:

Degree of Bachelor of Science inkluding an independent project 15 credits or Degree of Bachelor of Science in Engineering inkluding an independent project 15 credits, or the equivalent of 180 Swedish credit points or 180 ECTS credits at an accredited university. 5 credits machine learning and 3 credits statistics. Applicants must have written and verbal command of the English language equivalent to English course 6 in Swedish UpperSecondary School. Exemption of the requirement in Swedish is granted.

Selection rules:

Credits: 100%

Start week:

week: 04

Number of gatherings:


Instructional time:

Various times

Language of instruction:

Teaching is in English.

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