Course Websites

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.

This course focuses on deep learning within all areas of civil and environmental engineering. In addition to examining the basics of deep learning, students will investigate practical applications in sensor data processing, information extraction, remote sensing, surrogate modeling, and predictive analytics. Topics of interest include deep convolutional networks, recurrent neural networks, and generative adversarial learning. Students will learn to identify, understand, and compare different deep learning techniques and formulate civil engineering problems using appropriate techniques. The focus will be on understanding why and how deep learning methods may improve civil engineering problem-solving and determining the conditions when deep learning may not be a helpful approach. Ultimately, the concepts will be leveraged to formulate and solve data-intensive real-world CEE problems using the techniques discussed. Prerequisite: CEE 492, or equivalent