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Courses for Machine Learning

The two-year master's programme in Machine Learning consists of three terms of courses and one final term dedicated to the master's degree project. Each term consist of approximately 30 ECTS credits. The courses presented on this page apply to studies starting in autumn 2022.

Year 1

Courses that run in periods 1 and 2 of Year 2 can potentially be taken in period 1 and period 2 of Year 1 if its leads to a manageable workload for the student.

Apart from the mandatory and conditionally elective course requirements the student is free to choose from all the second cycle and language courses given at KTH to take his/her number of completed course credits to 90 ECTS. First cycle courses may be taken (though we prefer if students take second-cycle courses) but no more than 30 ECTS points can be counted towards graduation. Recommended courses is for those who would like to extend their competency and knowledge in Computer Science and Software Engineering. A final degree project must also be completed.

Choose among the conditionally elective courses so that the following conditions are fulfilled:

- at least 6 courses from Application Domains + Theory, and
- at least 2 courses from Application Domains, and also
- at least 2 courses from Theory.

Examples of possible combinations of courses:
- at least 2 courses from Application Domains, and at least 4 courses from Theory,
- at least 3 courses from Application Domains, and at least 3 courses from Theory,
- at least 4 courses from Application Domains, and at least 2 courses from Theory.

Mandatory courses

Conditionally elective courses

Year 2

Conditionally elective courses