NUEN 489/689: Deep Learning for Engineering Applications
This is a project-oriented graduate level course. The curriculum encompasses a broad spectrum of topics, including the basics of machine learning and deep neural networks, alongside specialized subjects such as physics-informed machine learning, uncertainty quantification, and the integration of domain-specific knowledge into machine learning frameworks. Through an engaging blend of lectures, interactive coding exercises, and comprehensive project work, students will gain hands-on experience in deploying SciML techniques. By the end of this course, participants will be equipped with the proficiency to navigate and leverage the evolving landscape of machine learning in scientific and engineering contexts, effectively bridging the theoretical and practical aspects of technology and innovation.
NUEN 302: Introduction to Nuclear Engineering II