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Subject offerings of new and developing areas of knowledge in civil and environmental engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

Experimenting with Large Language Models (LLMs) such as ChatGPT to understand their capabilities in supporting learning and research in scientific computing (SC). In a discussion-based and laboratory format, student groups will investigate how LLMs can help SC students master their research and coding skills. The focus will be on computational approaches such as solution methods for differential equations (such as finite element, finite difference), Monte Carlo methods, uncertainty quantification and optimization problems. Deliverables include regular summary/progress reports and a research or education paper at the end of the semester. Pre-requisites: Familiarity with a coding language, research experience in scientific computing, background in machine learning (taken a graduate level course); please check with the instructor.