FYS-3012 Pattern recognition - 10 ECTS
The course is available as a singular course. The course is also available to exchange students and Fulbright students.
The course will only be taught if there is a sufficient number of students. Are you interested in following the course, please contact the student advisor as soon as possible.
Knowledge - The student can
- describe the concepts of classification, clustering and dimensionality reduction in data analysis
- apply advanced methods from pattern recognition to diverse classification, dimensionality reduction and clustering problems
- compare different algorithms with respect to their strengths and applicability
- describe important pattern recognition applications in society
Skills - The student can
- analyse modern pattern recognition methods and apply them in independent practical and theoretical problem solving
- train and validate a pattern recognition algorithm for a defined task using available data
- analyse Bayes classifiers in terms of error probabilities
- design linear classifiers for minimization of squared errors and other criteria
- design and analyse nonlinear classifiers in the form of neural networks
- perform feature extraction and data transformation, e.g. using eigenvectors
- explain different clustering algorithms, and analyse their strengths
- implement in practice all methods discussed in the course for analysis of data
General competence - The student can
- report the comparison of several pattern recognition algorithms applied to a practical problem
- appreciate the importance of pattern recognition in society
- work with pattern recognition methods for analysis of real data
Do you have questions about this module? Please check the following website to contact the course coordinator for exchange students at the faculty: https://en.uit.no/education/art?p_document_id=510412
- A home exam, counting about 40%
- An oral exam, counting about 60%
Assessment scale: Letter grades A-F. A is the highest grade and F is failed.
There is no access to a re-sit examination in this course
For further information, see chapter 5 in Regulations forstudies and examinations at the UiT The arctic university of Norway.
- About the course
- Campus: Tromsø |
- ECTS: 10
- Course code: FYS-3012
- Responsible unit
- Institutt for fysikk og teknologi