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IE 5640 - Data Mining for Engineering Applications |
Introduces data mining concepts and statistics/machine learning techniques for analyzing and discovering knowledge from large data sets that occur in engineering domains such as manufacturing, healthcare, sustainability, and energy. Topics include data reduction, data exploration, data visualization, concept description, mining association rules, classification, prediction, and clustering. Discusses data mining case studies that are drawn from manufacturing, retail, healthcare, biomedical, telecommunication, and other sectors. Prereq. (a) IE 3412, MATH 3081, or IE 6200 and (b) junior, senior, or graduate standing.
4.000 Credit hours 4.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Lecture Mech & Industrial Engineering Department Course Attributes: GSEN Engineering Restrictions: Must be enrolled in one of the following Levels: Undergraduate Graduate Must be enrolled in one of the following Classifications: Junior Senior Graduate Prerequisites: Undergraduate level IE 3412 Minimum Grade of D- or Undergraduate level MATH 3081 Minimum Grade of D- or Graduate level IE 6200 Minimum Grade of C- |
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