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Blekinge Institute of Technology
Department of Computer Science
Revision: 2
Reg.no:
Course syllabus
Machine Learning
Machine Learning
6 credits (6 högskolepoäng)
Course code: DV2638
Main field of study: Computer Science, Software Engineering
Disciplinary domain: Technology
Education level: Second-cycle
Specialization: A1N - Second cycle, has only first-cycle course/s as entry requirements
Language of instruction: English
Applies from: 2025-03-13
Approved: 2025-03-13
1. Descision
This course is established by Dean 2023-05-03. The course syllabus is approved by Head of Department of Computer Science 2025-03-13 and applies from 2025-03-13.
2. Entry requirements
Admission to the course require completed credits in Programming, 5 credits, Data Structurse and Algorithms, 5 credits and Mathematical Statistics or Probability Theory, 5 credits. English 6.
3. Objective and content
3.1 Objective
The main aim of the course is to introduce theory and methods from machine learning (ML) as well as practical applications in data mining. Technological developments have contributed to our becoming more dependent on databases for storage and data processing. The number and amount of content in databases is growing rapidly. With this growth, it becomes more difficult to manually find useful information from the large amount of data. We therefore need semi-automatic and automated methods to use, aggregate, analyze and extract such information. Methods and techniques from machine learning, information mining, and artificial intelligence have proven useful for this purpose.
3.2 Content
4. Learning outcomes
The following learning outcomes are examined in the course:
5. Learning activities
6. Assessment and grading
Modes of examinations of the course
| Code | Module | Credit | Grade |
| 2510 | Written assignment 1 | 1 credits | GU |
| 2520 | Written assignment 2 | 1 credits | GU |
| 2530 | Project | 4 credits | AF |
The course will be graded A Excellent, B Very good, C Good, D Satisfactory, E Sufficient, FX Failed result, a little more work required, F Fail.
The examiner may carry out oral follow-up of written examinations.
The information before the start of the course states the assessment criteria and make explicit in which modes of examination that the learning outcomes are assessed.
An examiner can, after consulting the Disability Advisor at BTH, decide on a customized examination form for a student with a long-term disability to be provided with an examination equivalent to one given to a student who is not disabled.
7. Course evaluation
The course evaluation should be carried out in line with BTH:s course evaluation template and process.
8. Restrictions regarding degree
The course can form part of a degree but not together with another course the content of which completely or partly corresponds with the contents of this course.
9. Course literature and other materials of instruction
10. Additional information
This course replaces DV2599