Jun 16, 2024  
2018-19 Catalog 
2018-19 Catalog [ARCHIVED CATALOG]

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DA 420 - Predictive Analytics

5 CR

Students will study the process of formulating business objectives, data selection, preparation, and partition to successfully design, build, evaluate, and implement predictive models for a variety of practical business applications. Topics include a variety of predictive models such as classification, decision trees, machine learning, supervised and unsupervised learning.

Recommended: DA 460 .
Prerequisite(s): MATH 342  with a C or better, or permission of the instructor.

Course Outcomes
- Identify the common predictive analytics techniques, and their advantages and limitations. - Identify common predictive models and classifiers and their applications. - Evaluate the relevant aspects of a real world data set and choose an appropriate

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