Winter quarter of odd years
This course will provide an overview of some data science tools and best practices that can be used to create transparent and reproducible workflows when working with environmental data. Students will learn how to translate raw data from field and lab studies into databases and “tidy” digital formats, which can then be used for plotting, statistical analyses, etc. Students will learn how to track the history of file changes (version control), collaborate online with others, and generate “recipes” for re-creating one’s work. Although failure and frustration in science are common, the open science community tries hard to be welcoming and helpful. Thus, students will also learn how and where to ask for help when attempting something new (e.g., How do I create X from Y?), debugging or fixing code (e.g., What does this error message mean?), etc.