Best Practices in Environmental Data Science

3 credits

Provides overview of data science tools and best practices to create transparent and reproducible workflows when working with environmental data. Students learn how to translate raw data into databases and tidy digital formats. Covers how to track the history of file changes (version control), collaborate online with others, and create digital recipes for re-creating one's work. Recommended: either working knowledge of R programming, or FISH 552 and FISH 553. Offered: W, odd years.