- Schedule of Classes - September 9, 2021 7:14PM EDT
- Course Catalog - September 9, 2021 7:15PM EDT
Course information provided by the Courses of Study 2020-2021.
This course covers the basic concepts, models and algorithms of Bayesian learning, classification, regression, dimension reduction, clustering, density estimation, artificial neural networks, deep learning, and reinforcement learning. Application and methodology topics include process monitoring, fault diagnosis, preventive maintenance, root cause analysis, soft sensing, quality control, machine learning for process optimization, data-driven decision making under uncertainty, missing data imputation, data de-noising, and anomaly/outlier detection.
When Offered Spring.
Prerequisites/Corequisites Prerequisite: CEE 3040 or MATH 4710 or ORIE 3500 or equivalent, CHEME 6800/SYSEN 6800 or ORIE 3310 or ORIE 5310 or ORIE 5380.
Regular Academic Session. Combined with: CHEME 6880
Credits and Grading Basis
4 Credits GradeNoAud(Letter grades only (no audit))
Class Number & Section Details
- MW Online Meeting
- Feb 8 - May 14, 2021
Instruction Mode: Online
Enrollment limited to: PhD & MS students.
Disabled for this roster.