Pre-Specialisation in Data Science and Machine Learning
2025/2026
Content, progress and pedagogy of the module
Disclaimer.
This is an English translation of the module. In case of
discrepancy between the translation and the Danish version, the
Danish version of the module is valid.
Learning objectives
Knowledge
After completing the project module, the student should be able to:
- document in-depth knowledge and overview of a current research problem in data science
Skills
- reason about and with the concepts and techniques concerned
- apply and create theory courses in the subject area in connection with the formulation and analysis of a problem in the subject area research
- communicate a current computer science problem and the related conceptual apparatus within the framework of the subject area
Competences
- be able to use the concepts and reasonings in the subject area to formulate and analyze a problem within a current research problem in the subject area
Type of instruction
The project report must contain:
- formulating and analyzing a problem in data science research, and
- reasoned considerations for resolving this issue
Extent and expected workload
The student is expected to spend 30 hours per ECTS, which means 450 hours for this activity.
Exam
Exams
| Name of exam | Pre-Specialisation in Data Science and Machine Learning |
| Type of exam | Oral exam based on a project |
| ECTS | 15 |
| Permitted aids | Aids are permitted during the preparation of the project, but not during the exam. Rules regarding AI are mentioned on the semester page in MOODLE |
| Assessment | 7-point grading scale |
| Type of grading | External examination |
| Criteria of assessment | The criteria of assessment are stated in the Examination Policies and Procedures |
Additional information
Contact: Study Board for Computer Science via cs-sn@cs.aau.dk or 9940 8854
Facts about the module
| Danish title | Forspecialisering i datavidenskab og machine learning |
| Module code | DSNDVMLK331 |
| Module type | Project |
| Duration | 1 semester |
| Semester | Autumn
|
| ECTS | 15 |
| Language of instruction | Danish and English |
| Empty-place Scheme | Yes |
| Location of the lecture | Campus Aalborg |
| Responsible for the module |
Organisation
| Education owner | Master of Science (MSc) in Data Science and Machine Learning |
| Study Board | Study Board of Computer Science |
| Department | Department of Computer Science |
| Faculty | The Technical Faculty of IT and Design |
