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Dec 05, 2025
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BSE 464 - Data Analytics in Agricultural and Ecological Systems3 Credit Hours
This course 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. This 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. This course is designed for students in a natural resources and life sciences discipline
Credit Restriction: Students may not receive credit for both BSE 464 and BSE 564
(RE) Prerequisite(s): MATH 125* or MATH 141* ; CHEM 122* and CHEM 123* ; BSE 231 or CHEM 132* and CHEM 133* ; STAT 201* or STAT 251
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