For students attending the Master's Programme in Biostatistics and Data Science Elective courses

Students enrolled in the master’s programme in biostatistics and data science choose 30 credits (of the total 120 credits) from a selection of conditionally elective courses.

These courses take place in the second and third semesters and allow students to customise their education by studying elective courses that deepen or broaden their knowledge in their areas of interest within biostatistics and data science. No more than 15 credits (of the 30 credits of electives) can be at the undergraduate level. 

Students must choose one (and only one) of the following courses:

Exception: students who have completed the KTH course “DD1420 Foundations of Machine Learning” as part of an earlier degree may not select any of these three courses and must choose a more advanced course in machine/statistical learning from the list below.  

The remaining 22.5 credits are selected from a list of courses (see below). 

List of conditionally elective courses

The conditionally elective courses listed below are grouped according to the study period in which they start. Each course name is preceded by the corresponding course code and the name of the responsible university (KTH or SU). 

Note that DD2421 and DD2412 run throughout the spring semester at a lower rate of study. 

For guidance, we use the following abbreviations:

ML: focus on (possibly statistical) machine learning
BS: focus on biostatistics
MS: focus on mathematical statistics 
DS: general data science, not necessarily ML, BS, or MS. 
UG: undergraduate level

Conditionally elective courses offered academic year 2024/2025

Autumn 2024, first study period (there is no time allocated to elective courses in this period, but some students may have already passed a mandatory course)

SF2935 (KTH) Modern methods of statistical learning, 7.5 credits (ML)
MT7052 (SU) Inference and prediction for life and health processes, 7.5 credits (BS) 
MT7050 (SU) Unsupervised learning, 7.5 credits (ML)
SF2956 (KTH) Topological data analysis, 7.5 credits (DS) 
DD2412 (KTH) Deep learning, advanced course, 3 credits (ML; runs over two study periods)

Autumn 2024, second study period (there is no time allocated to elective courses in this period, but some students may have already taken a mandatory course)

MT7049 (SU) Statistical learning, 7.5 credits (ML)
SF2957 (KTH) Statistical machine learning, 7.5 credits (ML)
MT7042 (SU) Statistical aspects of deep learning, 7.5 credits (ML)

Spring 2025, first study period

DD2421 (KTH) Machine learning, 7.5 credits (ML; runs over two study periods)
SF2930 (KTH) Regression analysis, 7.5 credits (MS)
MT7051 (SU) Reinforcement learning, 7.5 credits (ML) 
SF2926 (KTH) Numerical algorithms for data intensive science, 7.5 credits (DS)

Spring 2025, second study period

MT5020 (SU) The mathematics and statistics of infectious disease outbreaks, 7.5 credits (BS, UG)
SF2943 (KTH) Time series analysis, 7.5 credits (MS)
DD2424 (KTH) Deep learning in data science, 7.5 credits (ML) 

Details of elective courses

Information will be provided here on, for example, elective courses that fit well together or elective courses that may not be taken together.   

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