Pre-Specialisation in Data Science


Content, progress and pedagogy of the module

Learning objectives


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


  • 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


  • 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:

  1. formulating and analyzing a problem in data science research, and
  2. 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.



Name of examPre-Specialisation in Data Science
Type of exam
Oral exam based on a project
Assessment7-point grading scale
Type of gradingExternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Additional information

Contact: Study Board for Computer Science via or 9940 8854

Facts about the module

Danish titleForspecialisering i datavidenskab
Module codeDSNDVK301
Module typeProject
Duration1 semester
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Education ownerMaster of Science (MSc) in Data Science and Machine Learning
Study BoardStudy Board of Computer Science
DepartmentDepartment of Computer Science
FacultyThe Technical Faculty of IT and Design