Additional learning outcomes
- has a thorough understanding of how computing is used to solve scientific problems
- knows some central algorithms used in science
- has knowledge of high-performance computing elements: memory usage, vectorization and parallel algorithms
- understands approximation errors and what can go wrong with algorithms
- has experience with programming in a compiled language (Fortran, C, C++)
- has experience with debugging software
- has experience with test frameworks and procedures
- can critically evaluate results and errors
- understands how to increase the efficiency of numerical algorithms and pertinent software
- understands tools to make science reproducible and has a sound ethical approach to scientific problems
- Is able to write a scientific report with software like Latex