CFD 4: Uncertainty Quantification

This course is a general introduction to the numerical-statistical field of Uncertainty Quantification (UQ), with a particular focus on methods relevant for fluid dynamics (both CFD and to a lesser extent experimental methods), and machine learning.

Prerequisites:

- Probability and statistics (fundamentals)

- Numerical analysis (fundamentals)

- CFD (familiarity and interest)

- Scientific programming in Python (basics)

The latter is for completing the programming homework assignments. Python is recommended and supported, but other languages may be used if preferred.

Final grade consists of a combination of:

4 Python projects (code only, no student-written report)

An oral exam OR a written exam (to be decided)

All projects may be done alone or in pairs - orals are individual.