SYSEN 6880

SYSEN 6880

Course information provided by the Courses of Study 2019-2020.

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.

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Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Combined with: CHEME 6880

  • 4 Credits Opt NoAud

  • 12399SYSEN 6880  LEC 001

  • Instruction Mode: Hybrid - Online & In Person
    Enrollment limited to PhD& MS students.