Startsida
Bayesian Learning, 6 credits
The course aims to give a solid introduction to the Bayesian approach to statistical inference, with a view towards applications in data mining and machine learning. The course contents is a mix of theoretical concepts, computer exercises and exercise sessions. Such concepts as prior-to-posterior updating, Markov Chain Monte Carlo, Bayesian prediction, marginalization of nuisance 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, 011-36 35 90, 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. The student should also have passed:
- an intermediate course in probability and statistical inference,
- a basic course in programming,
- a course including multiple linear regression.
| Course information | ||
|---|---|---|
| Semester: Autumn 2013 | ||
| Enrolment code: LIU- | ||
| Rate of study: Part-time | ||
| Campus: Linköping | ||
| Study Period: 201344 - 201403, 28 October 2013-17 January 2014 | ||
| Course code: 732A46 | ||
| Tuition fee: 9 498 SEK | ||
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See the contact person above
Last updated: Fri Jun 07 04:02:24 CEST 2013
