ABE 412
Fall 2025 All Classes
Credit: 3 hours.
Use of data to study problems unique to agricultural and biological engineering, identify patterns, and make actionable insights. Course includes (1) exploratory data analysis including data profiling, missing data, description, and data visualization; (2) data processing techniques including singular value decomposition, dimensionality reduction, and Fourier and wavelet transforms; (3) machine learning techniques including regression, classification, feature selection, clustering, and neural networks.
3 undergraduate hours. 3 graduate hours. Prerequisite: CS101 or equivalent and MATH 257.
| CRN | Type | Section | Time | Day | Location | Instructor | Section Details | |
|---|---|---|---|---|---|---|---|---|
|
80969
|
Lecture
|
AB
|
12:30PM
-1:50PM
|
TR
|
242 Agricultural Engr Sciences Bld
|
Tessum, M
|
|