Course Websites

TAM 598 EON - Eng & Sci App of Deep Learning

Last offered Spring 2025

Official Description

Subject offerings of new and developing areas of knowledge in theoretical and applied mechanics 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 to a maximum of 12 hours.

Section Description

Prerequisites: Math 257 Linear Algebra with Computational Applications (or equivalent); CS 12 Intro to Computer Science. This class explores the application of deep learning techniques to solve complex problems in engineering and the physical sciences. Students will learn to implement and adapt neural networks, convolutional architectures, and recurrent models to analyze data and discover patterns in physical systems. Topics include data-driven modeling, inverse design, generative approaches for applications in mechanics and materials, and integration with domain-specific physics constraints. The course emphasizes practical implementation, with hands-on projects that involve tasks such as simulation optimization, parameter estimation, and prediction in engineering systems.

Related Faculty

Schedule and Instructors

TitleSectionCRNTypeHoursTimesDaysLocationInstructor
Eng & Sci App of Deep LearningEON62822ONL4 -    Elif Ertekin