CH E 358A - Process Data Analytics and Machine Learning

0 units (fi 8)(EITH/SP/SU, 3-0-4)

Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include linear and nonlinear regression, dimensionality reduction, classification, deep learning, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and CH E 345.

CH E 358B - Process Data Analytics and Machine Learning

5 units (fi 8)(EITH/SP/SU, 3-0-4)

Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include linear and nonlinear regression, dimensionality reduction, classification, deep learning, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and CH E 345.

CH E 358 - Process Data Analytics and Machine Learning

5 units (fi 8)(EITH/SP/SU, 3-0-4)

Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include linear and nonlinear regression, dimensionality reduction, classification, deep learning, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and CH E 345.

CME 265 - Process Analysis

4.5 units (fi 8)(EITHER, 3-0-3)

Basic process principles; material and energy balances, transient processes, introduction to computer-aided balance calculations. Prerequisites: ENCMP 100, MATH 102 and CHEM 105. Corequisites: CH E 243 and MATH 209 or equivalent. Credit may not be obtained in this course if previous credit has been obtained for CH E 265.