Predictive Analytics
Durham
Paul College of Business&Econ::Administration
Credits: 3.0
Class Size: 39
Term:
Spring 2024
-
Term 4 (03/25/2024
-
05/17/2024)
CRN:
53003
Grade Mode:
Letter Grading
This course will focus on modern predictive analytic techniques. Each module is designed to introduce a set of statistical techniques and their application to real data from various business fields. The course will focus on 4 broad topics 1) Finding the most appropriate model for the data, 2) selecting optimal set of predictors, 3) reducing dimensionality of the data, 4)improving prediction performance. Programming using R, open source software, is fundamental to the course.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): ADMN 950
Instructors:
Gorkem Turgut (G.T.) Ozer
Times & Locations
| Start Date | End Date | Days | Time | Location |
|---|---|---|---|---|
| 3/25/2024 | 5/17/2024 | M | 5:40pm - 9:00pm | PCBE 115 |
