ENV 617b () / 2024-2025

Real World Environmental Data Science

Credits: 3 Spring 2025: M,W, 1:00-2:20, Kroon G01

To make sound decisions, we need good data, but the reality is that data is often messy, difficult to find, and incomplete. This is a practical, accessible course for those looking to learn Python and gain the foundational skills necessary to work with real-world environmental data. The first half of the class teaches best practices for sourcing and cleaning data (missing data, duplicates, merging, etc). We then teach data visualization, mapping, and statistical techniques. No programming experience is required. The focus is on implementation, not statistics. There are assignments and a midterm. In the second half of the class, students apply skills in a data project of their choosing. We host guest speakers doing innovative work in environmental data science and provide an overview of advanced topics in machine learning, data ethics, and Python programming