CEE 492
Fall 2025 Part of Term 1
Aug 25-Dec 10
Credit: 3 OR 4 hours.
Students will learn to leverage data to study civil and environmental engineering problems, identify patterns, and make actionable insights. This course includes training in computational thinking and exploratory data analysis; data processing techniques including singular value decomposition, principal component analysis, and Fourier and wavelet transforms; and machine learning techniques including k-means, classification trees, neural networks, and neural differential equations. Students are required to bring a laptop computer to class.
3 undergraduate hours. 4 graduate hours. Prerequisite: CS 101; CEE 202; and CEE 300, CEE 330, or CEE 360.
| CRN | Type | Section | Time | Day | Location | Instructor | Section Details | |
|---|---|---|---|---|---|---|---|---|
|
77425
|
Lecture-Discussion
|
DS3
|
12:00PM
-1:20PM
|
TR
|
3019 Civil & Envir Eng Bldg
|
Park, M
Tessum, C |
|
|
|
77426
|
Lecture-Discussion
|
DS4
|
12:00PM
-1:20PM
|
TR
|
3019 Civil & Envir Eng Bldg
|
Park, M
Tessum, C |
|
|
|
78538
|
Online
|
ONC
|
ARRANGED
|
n.a.
|
n.a.
|
Tessum, C
|
|
|
|
77427
|
Online
|
ONL
|
ARRANGED
|
n.a.
|
n.a.
|
Tessum, C
|
|