Courses for Biostatistics and Data Science
The two-year master's programme in Biostatistics and Data Science 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 2026.
Year 1
Mandatory courses
Conditionally elective courses
Year 2
Mandatory courses 60 credits (45 credits year 1, 45 credits year 2)
SF2940 Probability Theory 7,5 credits (KTH)
MT5017 Theory of Statistical Inference 7,5 credits (SU)
5BD000 Biostatistics 1 7,5 credits (KI)
MT5022 Classification and Analysis of Categorical Data 7,5 credits (SU)
5BD001 Survival analysis with applications in medicine 7,5 credits (KI)
SF2955 Computer Intensive Methods in Mathematical Statistics 7,5 credits (KTH)
5BD002 Biostatistics 2 7,5 credits (KI, year 2)
5BD003 Study design and analysis in medical research 7,5 credits (KI, year 2)
Degree project in biostatistics and data science 30 credits (KI, year 2)
Conditionally elective courses 30 credits (15 credits year 1, 15 credits year 2)
MT7050 Unsupervised learning 7,5 credits (SU)
MT7042 Statistical deep learning 7,5 credits (SU)
MT7032 Statistical information theory, 7,5 credits, SU
MT7051 Reinforcement Learning 7,5 credits (SU)
MT5020 Mathematics and Statistics of Infectious Disease Outbreaks 7,5 credits (SU)
MT7049 Statistical Learning 7,5 credits (SU)*
DD2421 Machine Learning 7,5 credits (KTH)*
SF2935 Modern Methods of Statistical Learning 7,5 credits (KTH)*
SF2526 Numerical algorithms for data-intensive science 7,5 credits (KTH)
SF2930 Regression Analysis 7,5 credits (KTH)
SF2943 Time Series Analysis 7,5 credits (KTH)
DD2424 Deep Learning in Data Science 7,5 credits (KTH)
SK2532 Biomedicine for Engineers 7,5 credits (KTH)
DD2420 Probabilistic Graphical Models 7.5 credits (KTH)
DD2610 Deep Learning, advanced course 7,5 credits (KTH)
SF2957 Statistical Machine Learning 7,5 credits (KTH)
5BD005 Mathematics of causal inference 7,5 credits (KI)
5BD006 Fundamentals of Statistical Modeling 7,5 credits (KI)
*Of the 30 credits conditionally elective courses students must choose one (and only one) of the following conditionally elective courses: SF2935 Modern Methods for Statistical Learning, DD2421 Machine Learning or MT7049 Statistical Learning.
Up to 15 credits of the conditionally elective courses can be at the undergraduate level.