After successful completion of the course, students are able to select and apply fundamental methods of scientific computing and to judge the challenges regarding computing time and implementation effort. Furthermore, the students have solution skills for inter-disciplinery problems, are able to evaluate and analyze computational approaches, and are able to scientifically formulate and extensively analyze compute-intensive problems as well as to develop appropriate approaches. 

• Distributed Parallel Computing
• Molecular Dynamics
• Methods for Ordinary Differential Equations
• Classification and Analyses of Partial Differential Equations
• Time Discretization
• Finite Volume Method
• Finite Element Method

Lectures, exercises and discussion of case studies

Exercises hand-in, a minimum threshold is required to be eligible for the final examination at the end of the term

advanced knowledge in C++ and Python required!