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Mar 14, 2026
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ACS 4410 - Advanced Predictive Analytics3 lecture hours 0 lab hours 3 credits
Course Description
This course introduces students to statistical learning and advanced predictive analysis methods. Students will become proficient in fundamental statistical learning techniques. Topics covered include decision trees, random forests, classification, generalized linear mixed models, and clustering analysis.
Prereq: ACS 3420
Note: None
This course meets the following Raider Core CLO Requirement: None
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Construct and evaluate decision trees for both regression and classification
- Apply appropriate supervised and unsupervised statistical learning techniques.
- Use advanced predictive analytic techniques to solve real-world business problems
- Use statistical software to solve problems related to course topics.
- Interpret and effectively communicate the results from these problems
Prerequisites by Topic
- Regression analysis
- Generalized linear model
Course Topics
- Decision trees
- Random forests
- Clustering analysis
- Generalized linear mixed model
- Foundational statistical learning techniques
Coordinator
Dr. Won Chul Song
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