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Apr 21, 2026
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BSE 564 - Data Analytics in Agricultural and Ecological Systems3 Credit Hours
Provides students with the fundamentals of data science and modeling for analyzing environmental, ecological, and agricultural systems using the open-source software R. Note that prior programming experience is not required. Course is organized into the following sections: (1) introduction to programming in R, including the development of skills for cleaning environmental data, summarizing data, and creating visualizations, (2) overview of data-based and process-based modeling approaches, (3) applications, evaluation, and challenges of modeling in relation to environmental systems. Students will gain a broad understanding of different analytical tools and learn to apply such methods to agricultural and ecological data. Designed for students in a natural resources and life sciences discipline.
Credit Restriction: Students cannot receive credit for both BSE 464 and BSE 564.
Recommended Background: General chemistry, one semester of calculus, one semester of statistics.
Registration Restriction(s): Minimum student level - graduate.
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