Pre-Specialisation in Data Science
2022/2023
Content, progress and pedagogy of the module
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 |
| Type of exam | Oral exam based on a project |
| ECTS | 15 |
| 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 |
| Module code | DSNDVK301 |
| 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
| Study Board | Study Board of Computer Science |
| Department | Department of Computer Science |
| Faculty | The Technical Faculty of IT and Design |
