1 Environmental Data Science

This working repository hosts all lecture material, code, assignments, and the syllabus for Data Issues in Hydrology (WR674) taught at Colorado State University.

1.1 Course Goals

The broadest goal for this course is to make analysis easier and more intuitive for you. In my experience, code fluency can dramatically increase the efficiency of your work and significantly add to the the amount of time you enjoy working whether it be in graduate school, as a post-doc, in government work, or really anything else. Further, coding is a versatile skill that is transferable across languages and problems.

Specifically in this course you will learn:

  • How to use R, RStudio, and the tidyverse

  • How to write dynamic scientific documents using RMarkdown

  • How to collaboratively code in an open and reproducible framework using Git and GitHub

  • How to quickly and efficiently organize, clean, and visualize complex environmental datasets using tidydata principles

  • How to pull down publicly available datasets within R (no more pointing and clicking on the interwebs)

  • How to do basic geospatial analyses in R

  • How to create interactive visualizations using html and JavaScript libraries

  • Finally, you will be doing all of this work with your own data and/or data that is similar to your core datasets. Ideally, the final for this project will be an analysis that goes into your undergrad, masters, or PhD thesis.