Startsida
Data Mining and Statistical Learning, 15 credits
The course is about methods that allow for exploring large data to extract and analyse important information hidden in this data. The course contents is a mix of theoretical concepts, computer exercises using software for Data Mining and discussion seminars. Such concepts as linear discriminant analysis, ridge regression, neural networks, splines, support vector machines and many other concepts are studied in the course.
Language of instruction: English
Level: Master's level
Department offering the course: Department of Computer and Information Science
Contact: Lilian Alarik, 011-363590, studievagledare-statistik@liu.se
Lotta Hallberg, 0734-618988, ann-charlotte.hallberg@liu.se
Specific admission requirements: For acceptance to the course, the student must have a bachelor’s degree with a total of at least 90 ECTS credits (1.5 years of full-time studies) in mathematics, applied mathematics, statistics, and computer science. The undergraduate courses in mathematics should include both calculus and linear algebra. Basic undergraduate courses in statistics and computer science are also required.
| Course information | ||
|---|---|---|
| Semester: Autumn 2013 | ||
| Enrolment code: LIU- | ||
| Rate of study: Part-time | ||
| Campus: Linköping | ||
| Study Period: 201336 - 201403, 2 September 2013-17 January 2014 | ||
| Course code: 732A33 | ||
| Tuition fee: 23 745 SEK | ||
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Last updated: Fri Jun 07 04:02:23 CEST 2013
