Project course (ELE690)

Project in robotics, signal processing, health technology and/or artificial intelligence.

Course description for study year 2023-2024. Please note that changes may occur.


Course code




Credits (ECTS)


Semester tution start


Number of semesters


Exam semester


Language of instruction



The purpose of this project topic is to build on knowledge acquired earlier in the study. The project will build on several topics, such as machine learning, deep neural networks, signal processing, image processing, control technology and robot technology.

Learning outcome

At the end of this course, the student should be able to solve a practical problem in robotics, signal processing, health technology and/or artificial intelligence. The problem must be solved within a certain time and the work must be documented in the form of a report and an oral presentation.

Required prerequisite knowledge



Project report and oral presentation

Form of assessment Weight Duration Marks Aid
Project report 1/2 Letter grades
Oral presentation 1/2 Letter grades

The assigned project is carried out in groups of two to three students. Exceptionally, it can be one or four students per group. The report describes and documents work in the project. The report is made in collaboration with all the participants in the group and all participants will get the same grade.The project is evaluated through a report and an oral hearing. Both parts must be done before final grade for the project is given.If a student fails the projectwork , she/he has to take this part again next time the subject is taught.

Course teacher(s)

Course coordinator:

Trygve Christian Eftestøl

Course teacher:

Øyvind Meinich-Bache

Study Program Director:

Tormod Drengstig

Head of Department:

Tom Ryen

Method of work

The project is implemented within 8-12 weeks and we expect that each student to spend about 3-4 hours per week on the project. Normally, two students work together on a project. Each group is given a brief tutorial meeting every week. If the course is taken in parallel with ELE680 Deep Neural Networks, and the project is aimed at deep learning, this can be adapted by placing the bulk of the work at the end of the semester. It is then expected that the number of hours spent per week is adjusted in relation to this.

Course assessment

There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.


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