CHEME 6880

Industrial Big Data Analytics and Machine Learning

Course Description

Course information provided by the 2018-2019 Catalog.

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.

Prerequisites/Corequisites Prerequisite: Basic probability (CEE 3040/MATH 4710/ORIE 3500 or equivalent) and optimization (CHEME 6800/SYSEN 6800, ORIE 3310/ORIE 5310, or ORIE 5380).

Permission Note Enrollment limited to: ChemE majors.

When Offered Spring.

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