Introduces students to scientific programming commonly used in environmental research with an emphasis on open-source languages and tools (e.g., R, Python, Jupyter Notebooks, tidyverse, ggplot, etc.). Coursework will include best practices in experimental design and data collection, interacting with different data structures, data cleaning and wrangling, hypothesis testing, and basic data visualization. No prior experience with coding (R, Python, etc) is required for this course.
Gopher Grades is maintained by Social Coding with data from Summer 2017 to Spring 2026 provided by the University in response to a public records request