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:

  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.

Exam

Exams

Name of examPre-Specialisation in Data Science
Type of exam
Oral exam based on a project
ECTS15
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 cs-sn@cs.aau.dk or 9940 8854

Facts about the module

Danish titleForspecialisering i datavidenskab
Module codeDSNDVK301
Module typeProject
Duration1 semester
SemesterAutumn
ECTS15
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

Study BoardStudy Board of Computer Science
DepartmentDepartment of Computer Science
FacultyTechnical Faculty of IT and Design