| Kursusnavn (dansk): | Datamining |
| Kursusnavn (engelsk): | Data Mining |
| Semester: | Forår 2013 |
| Udbydes under: | cand.it., spil (games) |
| Omfang i ECTS: | 7,50 |
| Kursussprog: | Engelsk |
| Kursushjemmeside: | https://learnit.itu.dk |
| Min. antal deltagere: | 12 |
| Forventet antal deltagere: | 30 |
| Maks. antal deltagere: | 55 |
| Formelle forudsætninger: | Students must have experience with and be comfortable with programming, and be capable of independently implementing algorithms from descriptions in pseudocode. This corresponds to at least having passed an introductory programming course, and preferably also an intermediate-level programming course. The course will contain compulsory programming assignments.
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Information about study structure
This course is an elective on the Games study programme, as well as for other study programmes. |
| Læringsmål: | After the course the students should be able to:
- Analyze data mining problems and reason about the most appropriate methods to apply to a given dataset and knowledge extraction need.
- Implement basic pre-processing, association mining, classification and clustering algorithms.
- Apply and reflect advanced pre-processing, association mining, classification and clustering algorithms.
- Work efficiently in groups and evaluate the algorithms on real-world problems. |
| Fagligt indhold: | This course gives an introduction to the field of data mining. The course is relatively practically oriented, focusing on applicable algorithms. Practical exercises will involve both use of a freely available data mining package and individual implementation of algorithms.
The course will cover the following main topics:
- The data mining process
- Data pre-processing
- Pattern and association mining
- Classification and prediction
- Cluster analysis
Additionally the course will touch on topics including data warehousing, validation and recommender systems. Application examples will be given from domains including e-commerce, computer games and finance. |
| Læringsaktiviteter: | 12 forelæsninger + frivillige øvelsestimer 7 weeks of lectures, followed by 7 weeks of supervised group projects.
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See the schedule here:
link to the time table
The schedule will be available shortly before the beginning of the term. |
| Obligatoriske aktivititer: | There will be a mandatory handin Friday the 22nd of March. |
| Eksamensform og -beskrivelse: | X. experimental examination form (7-scale; external exam), 7-trins-skala, Ekstern censur The duration of this oral exam is 30 minutes.
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| Litteratur udover forskningsartikler: | Jiawei Han, Micheline Kamber & Jian Pei: Data Mining: Concepts and
Techniques, 3rd Edition. Elsevier 2012 |
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Kursusoversigt