KIUA2000 Machine learning
- Course codeKIUA2000
- Number of credits20
- Teaching semester2026 Autumn
- Language of instruction and examinationNorwegian/English
- CampusHamar
- Required prerequisite knowledge
Recommended: KIUA1013 Introduction to artificial intelligence
The course provides an introduction to basic methods and tools in machine learning in a comprehensive manner. This is based on the basic topics in machine learning. These topics will be supplemented with advanced methods and tools in programming to actualise the algorithms. In addition to this, current low code/no code approaches for implementing machine learning methods will also be introduced. Students will continue to develop general skills in project planning and knowledge sharing.
Learning outcome
Upon successfully passing the course, students will have achieved the following learning outcomes:
Students have:
- Knowledge about advanced programming methods and tools
- Knowledge about intermediate-level topics in methods and tools in machine learning based on the basic methods in machine learning
- Knowledge about linking programming tools and machine learning methods
Students can:
- Apply advanced programming methods and tools
- Apply intermediate-level topics in methods and tools in machine learning
- Implement machine learning methods through programming tools
- Implement machine learning methods through low code/no code tools
Students:
- Have a good understanding of intermediate-level topics in machine learning methods
- Have a good understanding of programming as a tool for implementing machine learning methods.
- Have a good understanding of the importance of teamwork, interdisciplinarity, flexible and multimodal approaches to realising project goals.
- Can work in collaborative projects through different activities
The course comprises a combination of lectures, practical exercises, independent study and academic supervision.
- 2 individual pieces of required coursework, compulsory physical attendance on campus.
- Attendance in classes/teaching sessions is mandatory, where physical attendance on campus is required. There is an 80% attendance requirement in teaching sessions and a 100% attendance requirement in specific learning activities. This is in accordance with the teaching plan for each course in the programme of study.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comments |
|---|---|---|---|---|---|---|
Written assignment | ECTS - A-F | Group | 100% |
- 1 project-based group assignment
Students may choose which language to use for their examination. The available options are Norwegian Bokmål, Norwegian Nynorsk and English.
Permitted examination support material:
- Literature
- All printed and written resources
- Any use of AI-generated text and content must be clarified with the lecturer, clearly labelled and academically justified in the submission