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This course introduces students to the rapidly growing field of data science and its applications in predictive modeling within Agriculture, Food, and Life Sciences. Students will learn techniques to access, explore, validate, prepare, manipulate, analyze, and report on data. They will be able to create analysis flow diagrams for both pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision trees, ensembles of trees like forests and gradient boosting, regression, logistic regression, neural networks, and support vector machines) in an interactive and exploratory manner.

Prerequisite: ³§°ÕÌý525 or ³§°ÕÌý512

Typically offered in Fall and Spring