Predictive Modeling for Learning Analytics

EDU 6343 4 Quarter Hours
Course Level CPS - Graduate
Description Offers students an opportunity to learn how to develop models to predict categorical and continuous outcomes, using such techniques as neural networks, decision trees, logistic regression, support vector machines, and Bayesian network models. Reviews expert options for each modeling node in detail and advises when and how to use each model. A hands-on final project offers students experience implementing predictive models.

Prerequisites

Students should refer to the CPS Prerequisite Table for course prerequisite and corequisite information.

 

Course Sections

Section 01
CRN 20782
View Syllabus Download
Session Winter 2018 CPS Quarter - Full Term
Class Meeting Dates 01/08/2018 to 03/31/2018
Instructor Michael Dean
Campus Online Campus
Course Format Online
Costs Course Cost: View Tuition Rates | Books: Visit NU Bookstore Site
Next Term Starts
  • Winter Graduate
    Jan 8, 2018 (6- and 12-week classes)
    Feb 19, 2018 (6-week classes)

Academic Calendar

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