Visualization (Vis)

Course content

The course introduces participants to visualization: use of interactive visual representations to help people understand and analyze data. Visualization 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 visualization and gain an overview of techniques for visualizing different types of data and supporting different tasks. Participants will learn to design and build visualizations using software toolkits, and to evaluate them. The course takes a practical problem-driven approach where students work with visualizations for solving a specific problem. However, participants will also learn about current challenges in information visualization research that may form the basis for projects and theses. The course will involve the following topics:

  • Principles of visualization (e.g., human visual perception) and models of interaction with visualization.
  • Overview of the variety of techniques, applications, and tasks in visualization.
  • Methods for analyzing, designing, and evaluating visualizations for particular tasks.
  • Software tools for developing information visualizations.
  • Current challenges in information visualization research. 

Msc Programme in Computer Science

Learning outcome


  • key principles of visualization,
  • challenges in information visualization.



  • analyze and design visualizations to address particular tasks,
  • implement interactive visualizations using a software toolkit.



  • reason about and justify the design and use of information visualization tools in a particular scenario.

Short lectures, classroom discussions of key papers on information visualization, and project work. The project work involves design, implementation, and evaluation of a visualization; this is supported through tutorials, exercise classes and workshops.

Programming skills corresponding to an introductory programming course is expected; Experience with several different types of programming languages is beneficial.

7,5 ECTS
Type of assessment
Oral examination, 20 min
The oral exam is based on a group project report.
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assessment

In order to earn the grade 12, students must demonstrate the knowledge, skills and competences described in the intended learning outcomes.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 24
  • Class Instruction
  • 24
  • Preparation
  • 32
  • Project work
  • 125
  • Exam
  • 1
  • English
  • 206