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] |
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Key for Course Detail Icons
 = Course Open |
 = Course Closed |
 = Course Details |
 = Textbook Info |
 = General Education |
 = Extended University |
 = Service Learning |
 = In Person |
 = Asynchronous Online |
 = Synchronous Online |
 = Synchronous/Asynchronous |
 = Blended |
 = No Cost Course Materials |
 = Low Cost Course Materials |