The course aims towards a good understanding of visualization principles and algorithms. The course gives insight into visualization techniques and tools as support to end users in their analytical reasoning. Increasingly complex data types including scalars, vectors, images, volumes and non-spatial datasets are explored with respect to their proper visualization techniques and algorithms. Issues such as data representation, presentation and interaction are discussed. Visualization software systems and libraries are central to creating successful visualizations and are also introduced.
Bachelors Degree in Computer Science or Computer Engineering, including courses in programming in C++, 15 Credits. Mathematics, Linear Algebra, 7.5 Credits; Probability Theory, 7.5 Credits.