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Sep 17, 2024
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MBA 6390 - Predictive Analytics
Predictive analytics encompasses a variety of statistical and machine learning techniques and applications within business environments. The primary goal of this course is to discover and apply relationships found within historic datasets in order to make predictions about the future or otherwise unknown events. In this hands-on course, students are introduced to concepts related to constructing, testing, and applying predictive models in various business settings. From this perspective, students utilize software tools in order to conduct an analysis of continuous, classification, and clustering models.
Requisites: Admission to COB graduate or certificate program or permission
Credit Hours: 3
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,PR,WP,WF,WN,FN,AU,I
Learning Outcomes:
- 1. Students will be able to define and explain fundamental terminology used in predictive analytics.
- 2. Students will be able to explain the differences between supervised and unsupervised learning.
- 3. Students will be able to pre-process a dataset so that it can be modeled using quantitative methods.
- 4. Students will be able to create and apply continuous, classification, and clustering models based on business scenarios.
- 5. Students will be able to use appropriate testing techniques and metrics in order to determine the performance of a model.
- 6. Students will be able to post-process the results of a quantitative method so the results are more easily understood.
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