ENGR-401: Computational Applied Physics With Machine Learning

Credits 3
Grade Scheme
Session Cycle

Computational and numerical techniques for problem-solving in applied physics.  Methods for differential equations, Monte Carlo simulations, and modeling of physical systems (eg, fluid flows, waves).  Programming of neural networks / machine learning to solve problems in engineering and applied science.  Implemented in Python.  Offered on demand.

Term Offered
May Term