ISC 4302. Scientific Visualization (3). Prerequisites: MAC 1105 and MAC 2312. This course is an introduction to scientific visualization for large-scale computation and experimental data that covers the visualization methods and techniques, visualization results analysis and evaluation, and visualization practice. It teaches students the techniques for creating compelling visual representations of 2D and 3D scientific data sets. The basic concepts, data structures, and algorithms in scientific visualization are presented and applied using datasets from different disciplines. Classic visualization techniques for scalar, vector, and tensor data such as marching cubes, ray casting, splatting, streamline, and line integral convolution and more, are introduced along with popular visualization software. [source]

Graduate Level (ISC 5307)