CEE 498 MLO

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: 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

This course focuses on the theory and mathematical foundations behind advanced machine learning methods, and their applications on CEE problems. Topics include regression, Bayesian inference, deep neural networks, physics-based deep learning, and Gaussian Processes. Prerequisite: CEE 498 Data Science for CEE Restricted to online non-degree, online MCS, online MSAE, online MSME, and online MSCE students. For more details on this course section, please see http://engineering.illinois.edu/online/courses/. Non-Degree students may enroll on a space-available basis with consent of Program Coordinator, Meg Griffin (mgriffin@illinois.edu).

This course focuses on the theory and mathematical foundations behind advanced machine learning methods, and their applications on CEE problems. Topics include regression, Bayesian inference, deep neural networks, physics-based deep learning, and Gaussian Processes. Prerequisite: CEE 498 Data Science for CEE Restricted to online non-degree, online MCS, online MSAE, online MSME, and online MSCE students.

4 hours

10/11/2022