Scientific Visualisation

5 credits

Syllabus, Master's level, 1TD389

A revised version of the syllabus is available.
Code
1TD389
Education cycle
Second cycle
Main field(s) of study and in-depth level
Computational Science A1N, Computer Science A1N, Technology A1N
Grading system
Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
Finalised by
The Faculty Board of Science and Technology, 13 February 2018
Responsible department
Department of Information Technology

Entry requirements

120 credits including Computer Programming I and Scientific Computing II. Scientific Computing II may be replaced by Numerical Methods and Simulation, 5 credits, Scientific Computing, Bridging Course, 5 credits, or Scientific Computing and Calculus, 10 credits.

Learning outcomes

To pass, the student should be able to

  • describe the data flow in a visualisation system;
  • outline the methods that transform the data and information to visual representations;
  • use and program advanced software for various visualisation techniques.

Content

The visualisation pipeline. Data representations and scalar visualisation. Vector and tensor visualisation. Multidimensional visualisation. Stereo Rendering. Perceptual issues in visualisation. Information Visualisation. Rendering techniques for visualisation such as volume rendering, splatting and isosurface generation.

The course includes projects using software for advanced visualisations.

Instruction

Lectures, laboratory work and compulsory assignments.

Assessment

Written test (2 credits). Passed laboratory course and approved compulsory assignments are also required (3 credits).

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