Project course (ELE690)
Project in robotics, signal processing, health technology and/or artificial intelligence.
Course description for study year 2024-2025
Course code
ELE690
Version
1
Credits (ECTS)
5
Semester tution start
Autumn
Number of semesters
1
Exam semester
Autumn
Language of instruction
English
Content
NB! This is an elective course and may be cancelled if fewer than 10 students are enrolled by August 20th for the autumn semester.
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
Exam
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.
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. Physical presence is a requirement group and supervision meetings.
