Course Description
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.
Spring 2025
Instructors
Meeting Patterns
Classes Start:
January 6, 2025
Classes End:
April 22, 2025
Distance Education:
Yes
Class Days:
[TBA]
Class Type:
Lecture
Credits:
3.00
Restrictions:
Prerequisite: ST 525 or ST 512