Course — Data-Driven Fluid Mechanics: Combining First Principles and Machine Learning

The integration of machine learning methods in fluid mechanics continues to grow and open new frontiers. Combining first principles and machine learning offers new avenues to improve predictions and control design, identify patterns, reduce computational costs, enhance measurement techniques, and more generally, get deeper insights into complex fluid phenomena. This lecture series provides an overview of the current state of the art and a pedagogical introduction to the fundamentals of machine learning tools for fluid dynamics. The course is in its second edition. It follows the successful lecture series held in 2020, which attracted more than 200 participants and resulted in an edited book published by Cambridge University Press.