In addition to the course MVA200 Perspectives on mathematics, which is compulsory for the whole programme, you need eight specialization courses. The following three courses are compulsory:
In addition, you need at least two of the courses:
and at least three of the courses:
- 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.
(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.