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 2021
2021-08-30 - 2021-11-07 (part time 50%)
Course syllabus & literatureSee course plan and literature list (MAA512)
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 B/Swedish 3 and English A/English 6 are required. In cases when the course is offered in English, the requirement for Swedish B/Swedish 3 is excluded.