Data analysis, clustering and classification
The goal of the course is to give knowledge of different methods for solving clustering and classification problems within data analysis. The course is intended to give both understanding of how the methods work as well as give training into how these methods can be used in different practical problems and applications. The course will present concrete examples of applications where clustering and classification appears and give examples of other aspects of data analysis, such as evaluation of results and common data transforms.
Occasions for this course
Autumn semester 2026
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Scope
7.5 credits
Time
2026-08-31 - 2026-11-08 (part time 50%)
Education level
Second cycle
Course type
Freestanding course
Application code
MDU-10367
Language
English
Study location
Västerås
Course syllabus & literature
See course syllabus and literature list (MAA512)Specific requirements
Linear algebra, 7.5 credits or Applied matrix analysis, 7.5 credits or the equivalent and Probability Theory and Statistical Inference, 7.5 credits or the equivalent and Fundamentals of programming, 7.5 credits or the equivalent. In addition, Swedish course 3 or Swedish level 3 and English course 6 or English level 2 are required. For courses given entirely in English exemption is made from the requirement in Swedish course 3 or Swedish level 3.
Selection
University credits