Statistical Learning and AI

Course requirements


  • FIM720 Neural networks ​
  • ​DIT741 Computational methods in bioinformatics
  • DIT602 Algorithms
  • DIT621 Databases
  • DIT411 Introduction to artificial intelligence
  • DIT866 Applied machine learning
  • DIT??? Design of AI systems (given for the first time 20/21)
  • DIT??? Natural language processing (give for the first time 20/21)
  • DIT381 Algorithms for machine learning and inference
  • DIT872 Techniques for large-scale data (not given 19/20)

You need to write a master's thesis in mathematical statistics (30 hec), with specialization Statistical learning and AI. 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.


Inriktningskurser Andra kurser
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​​
DIT741 Computational methods in bioinformatics
DIT??? "Natural language processing"
DIT621 Databases


Early spring
MSF100 Statistical inference principles (1)
MSA251 Experimental design and sampling (2)
​DIT411 Introduction to artificial intelligence

DIT866 Applied machine learning
DIT??? "Design of AI systems"

Late spring
MSA410 Financial time series
MSA301 Spatial statistics and inage analysis
MSA220 Statistical learning for big data
MSF200 Stochastic processes (1)
DIT381 Algorithms for machine learning and inference
MSF500 Weak convergence (2)
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: Sun 25 Aug 2019. Modified: Thu 19 Sep 2019