ITF31519 Practical Machine Learning (Autumn 2026)
Facts about the course
- ECTS Credits:
- 10
- Responsible faculty:
- Faculty of Computer Sciences, Engineering and Economics
- Campus:
- Halden
- Course Leader:
- Lars Vidar Magnusson
- Teaching language:
- Norwegian or English
- Duration:
- ½ year
Table of contents
The course is affiliated to the following study programme
Mandatory course for
- Bachelor in Computer Sciences (year 2026)
- Bachelor in Computer Sciences - Specialisation in Machine Learning (year 2024 and 2025)
Elective course for
- Bachelor in Computer Engineering
- Bachelor in Computer Engineering, TRESS
Required prerequisite knowledge
Recommended previous knowledge
Teaching semester
Content
Application of
- different techniques for machine learning
- methods for evaluating models for machine learning
The student's learning outcomes on passing the course
KnowledgeThe student
- understands what a machine learning problem is, how to solve it and ethical challenges related to it
- knows the workflow used in machine learning
Skills
- The student can use platforms and packages for machine learning
General competence
- The student can program machines so that they can learn to solve problems on their own
Teaching and learning methods
Workload
Coursework requirements - conditions for taking the exam
Exam
Individual or group portfolio assignment and individual written exam
The final grade is based on two exam parts. Each part must be passed to pass the course.
Part 1: Portfolio – individual or in groups of 2-3 persons. The portfolio counts 40% of the course grade. An individual grade is awarded using grading scale A-F.
Part 2: Individual written exam. The individual written exam is based on regular topics in the course. Duration: 3 hours. The written exam counts 60% of the course grade. No supporting materials allowed. Grading A-F.
Examiners
Conditions for resit/rescheduled exams
In the case of new or rescheduled examinations, both exam components can be retaken.
A new and rescheduled exam is conducted simultaneously with the next regular exam. However, the department management may decide to arrange a postponed exam in the following semester for students with valid absence from the regular exam.
Course evaluation
This course is evaluated by a:
- End-of-term evaluation (compulsory)
The responsible for the course compiles a report based on the feedback from the students and his/her own experience with the course. The report is discussed by the study quality committee of the faculty of Computer Sciences.