Cancelled Visualisation (Vis)

Course content

The course introduces participants to visualisation: the use of interactive visual representations to help people understand and analyse data. Visualisation is central to data-intensive science, business and intelligence analysis, for exploratory data analysis, and for clearly communicating findings in data.

Participants will learn about the foundations of information visualisation and techniques for visually representing different types of data and for supporting different tasks. Students will learn through a practical problem-driven approach to analyse, design, and build visualisations. In particular, through weekly exercises, the course will provide hands-on experience with creating interactive visualisations for the web. The course also emphasises the theoretical foundations of visualisations and includes considerations about current challenges in information visualisation research. 


MSc Programme in Computer Science

MSc Programme in Computer Science with a minor subject 

Learning outcome

Knowledge of

  • Key principles of visualisation
  • Fundamental visualisation and interaction techniques for different data types
  • Tools for building visualisations
  • Methods and frameworks for analysing and designing visualisations
  • Challenges in information visualisation


Skills in

  • Systematically analysing and comparing visualisations
  • Designing a visualisation that effectively supports a particular task
  • Visualising data types such as graphs, trees, matrices, and maps 


Competences in

  • Reasoning about and justifying the application of visualisation to a problem in a particular domain
  • Implementing interactive visualisation prototypes

Mix of lectures and class discussions, tutorials and exercises, and group work on weekly assignments and the project.

See Absalon for a list of course literature.

Programming skills corresponding to an introductory programming course is expected; experience with computer graphics is an advantage, but is not required.

Academic qualifications equivalent to a BSc degree is recommended.

Feedback by final exam (In addition to the grade)
7,5 ECTS
Type of assessment
Oral examination, 20 min
Type of assessment details
The oral exam is without preparation and is based on a project report.

Weight oral examination: 100%
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assessment

See Learning Outcome.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 24
  • Preparation
  • 42
  • Exercises
  • 56
  • Project work
  • 83
  • Exam
  • 1
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 2
No limit
The number of seats may be reduced in the late registration period
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Computer Science
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Kasper Hornbæk   (4-7a7082774f73783d7a843d737a)
Saved on the 24-06-2022

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