QM 47400 - Predictive Analytics

Credit Hours: 3.00. Students build and evaluate predictive models to support regression-type and classification-type business problems using popular industry tools (e.g., RStudio, SAS Enterprise Miner). Methods covered include multiple linear regression, ridge regression, lasso, CART, logistic regression, LDA/QDA, SVM, and ensemble methods such as random forests.

Learning Outcomes
1. Generate a valid predictive analytics solution by following a structured process. 2. Demonstrate practical understanding of frequently used predictive analytics techniques. 3. Demonstrate a working knowledge of RStudio and SAS Enterprise Miner to build an access predictive models. 4. Demonstrate project poster and presentation of a predictive analytics solution to a business problem.

Credit Hours: 3.00

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QM 47400 - Predictive Analytics