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
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.
As
an exchange, guest and credit student - click here!
Continuing Education - click here!
PhD’s can register for MSc-course by following the same procedure as credit-students, see link above.
- ECTS
- 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% - Exam registration requirements
-
To qualify for the exam, the student must:
1. Submit a report based on their project and
2. get approved 4 assignments that are given during the course.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
-
Re-exam same as ordinary exam.
If the student is not qualified then qualification can be achieved by submitting and approval of equivalent assignments and a project report. The assignments and report must be submitted no later than 3 weeks before the re-exam.
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
Kursusinformation
- Language
- English
- Course number
- NDAK16009U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 2
- Schedulegroup
-
B
- Capacity
- No limit
The number of seats may be reduced in the late registration period - Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Computer Science
Contracting faculty
- Faculty of Science
Course Coordinator
- Kasper Hornbæk (4-6e64766b43676c316e7831676e)
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