Statistical Learning and AI

Course requirements


  • FIM720 Neural networks 
  • FIM750 Simulation of complex systems​
  • ​DIT742 Computational methods in bioinformatics
  • DIT602 Algorithms
  • DIT621 Databases
  • DIT405 Introduction to data science and AI (given for the first time 20/21)
  • DIT866 Applied machine learning
  • DIT728 Design of AI systems (given for the first time 20/21)
  • DIT245 Machine learning for natural language processing (give for the first time 20/21)
  • DIT381 Algorithms for machine learning and inference

You need to write a master's thesis in mathematical statistics (30 hec), with specialization Statistical learning and AI (MSA940). In order to start the thesis you should have finished the three compulsory courses and one of the courses from the second list above (starting with MM or MS).

Your study plan

The specialization is inter-disciplinary, and you will manly choose from the specialization courses above. You can find other courses to choose from in our lists of courses in mathematics and mathematical statistics.

Depending on your background you may need to include some courses at bachelor level (for instance, in mathematical statistics). At most 30 hec bachelor level courses may be included in your degree.

Together with the programme coordinator you will set up an individual study plan, which will be revised when needed.

Here is a schedule for some of the relevant courses.


Specialization courses
Other courses
Early fall
MSA101 Computational methods for Bayesian statistics
MMG621 Nonlinear optimization ​
FIM720 Neural networks
DIT602 Algorithms
MSA350 Stochastic analysis
MMA110 Integration theory
Late fall
MSA520 Project course in statistical modelling
MSA150 Foundations of probability​​
FIM750 Simulation of complex systems
DIT405 Introduction to data science and AI

DIT742 Comp. methods in bioinformatics
DIT245 Machine learning for NLP
DIT621 Databases


Early spring
MSF100 Statistical inference principles (1)
MSA251 Experimental design and sampling (2)
DIT866 Applied machine learning
DIT602 Algorithms
DIT405 Introduction to Data science and AIDIT621 Databases
DIT381 Algorithms för machine learning
DIT728 Design of AI systems

DIT181 Data structures and algorithms
Late spring
MSA410 Financial time series
MSA301 Spatial statistics and inage analysis
MSA220 Statistical learning for big data
MSF200 Stochastic processes (1)
MSF500 Weak convergence (2)
DIT961 Data structures

The master's thesis is normally written as a half-time course during the second year.

(1) The course is given academic years starting with an odd number, e.g. 2019-2020.
(2) The course is given academic years starting with an even number, e.g. 2020-2021.

Published: Wed 11 Mar 2020.