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Nov 05, 2024
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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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