Core Tracks and General Track

The master's program is organized in methodological track. Research groups of Heidelberg University who actively teach in the master's program designed three core tracks to structure the program and specialize the  learning pathway.

  1. Machine Learning and Data Analysis
  2. Numerical Modelling, Simulation and Optimization
  3. Visual Data Analysis and Computer Graphics

The tracks are meant as guidelines for students to select courses and module combinations leading to interesting and rewarding master thesis research topics.The description of each core track lists modules that are essential for understanding the theory as well as the practical applications of the track. It also mentions associated research areas as well as possible topics for master projects.

General Track Note that students can decide not to follow core tracks but to compose a selection of modules based on the study regulations and the general study plan. We recommend this approach only to students with a more detailled overview of the area of scientific computing who want to specifically find complementary special moduels to enhance their prior education in scientific computing.