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May 12, 2024
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2021-2022 Graduate Catalogue Archived Catalogue
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BAN 502 - Predictive Analytics
Course Description: This course explores computer-intensive methods for model selection, parameter estimation, and validation for predictive analytics. The course focuses on techniques and algorithms from the statistical and machine learning disciplines, and has a strong programming component. Example topics that could be included in this course include: ordinary least squares regression, multi-nominal logistic regression, classification and regression trees, neural networks, support vector machines, naive Bayes, principal components analysis, cluster analysis, and regularization. Each technique is accompanied with a focus on application and problem-solving.
Credit Hours: 3
Corequisite Courses: None
Prerequisite Courses: BAN 500 and MIS 503 (may be taken concurrently)
Additional Restrictions/ Requirements: None
Course Repeatability: Course may not be repeated Maximum Repeatable Hours: 3
ADDITIONAL COURSE INFORMATION
Equivalent Courses: None
Undergraduate Crosslisting: None
Additional Course Fees: None
Course Attribute: None
Click here for the Fall 2024 Class Schedule.
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