Description: Hours: Two hours lecture and three hours lab per week
Prerequisite: COMP 350, COMP 362, MATH 151, MATH 240, MATH 352 and Consent of Instructor
Practical programming introduction to tools, methods, techniques, and workflows for understanding large quantities of data. Familiarizes students with instruments for data representation, preprocessing including data cleaning and reduction, input feature selection, data analysis including classification, clustering, and prediction, and data visualization.
Units: 3.00
Grading: Letter Grade
| Session | Section | Class # | Type | Days | Time | Location | Instructor | Course Details [Key] |
|---|---|---|---|---|---|---|---|---|
| E5 | 1 | 1013 | LEC | ARR | Online | Jason Isaacs |
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| E5 | 1L | 1014 | LAB | ARR | Online | Jason Isaacs |
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= Extended University |
 = Service Learning |
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= Asynchronous Online |
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