CHEM.4750 Machine Learning and AI in Energy Applications

Id: 042296 Credits: 3-3

Description

Recent developments in Machine Learning (ML) and Artificial Intelligence (AI) have revolutionized how we approach science and engineering. ML and AI have accelerated the discovery of new materials for catalysis and applications in solar or nuclear energy. They have enabled the high-throughput screening of nonporous materials for sustainable energy solutions. This course will provide a practical introduction to the machine learning concepts, methods, and tools to STEM students, including regression models, neural networks, modern deep learning, ensemble models, and reinforcement learning. Examples will be drawn form the entire spectrum of energy applications to illustrate the applications of ML approaches. The hands-on use of Python notebooks will be a key aspect of the course.

Prerequisites

CHEM.1210 Chemistry I, or CHEM.1350 Honors Chemistry I, and Restricted to Science, Math, and Engineering Majors or Instructor Permission.

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Course prerequisites/corequisites are determined by the faculty and approved by the curriculum committees. Students are required to fulfill these requirements prior to enrollment. For courses offered through online or GPS delivery, students are responsible for confirming with the instructor or department that all enrollment requirements have been satisfied before registering.