The Spring 2024 iteration of the ECEN 689 Scientific Machine Learning class is open for enrollment to Texas A&M undergraduate and graduate students. There will be a remote section for students not in College Station (this section will be available for registration soon).
The class is inherently multidisciplinary and its audience is all STEM students on campus. It covers elements of machine learning, discretization methods for ODEs and PDEs, automatic differentiation, PDE-constrained neural networks, PDE-Constrained Gaussian Process and Kernel Methods, inverse problems, and uncertainty quantification. The class requires knowledge of python and Tensorflow.
The class website for the Spring 2023 class can be found here: https://sciml.tamids.tamu.edu/ecen-689-scientific-machine-learning-spr-2023/
The class offers an opportunity for students to improve their analytical and computational skills in the rapidly-developing field of scientific machine learning. The class will prepare the students to work in highly interdisciplinary research and development projects.