Syllabus, Master's level, 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
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.
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.
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.
Lectures, laboratory work and compulsory assignments.
Written test (2 credits). Passed laboratory course and approved compulsory assignments are also required (3 credits).