ESPM 157: Data Science in Global Change Ecology

Overview

This course is designed for upper division undergraduate students regardless of prior experience. We aim to be accessible to those new to programming, but those who have been using R for years will find new material in this opinionated and fast moving area. The course is project focused and centered around four core modules reproducing important results in global change ecology. A series of short tutorials will introduce relevant technology, but most concepts will be first introduced in reading outside of class, leaving class time to focus on the more complex examples encountered in the modules.

Approach

This course will use a flipped classroom model, with new material introduced in reading assignments prior to class, while class time will focus on applying these skills to explore interesting data sets. Students will be expected to work collaboratively in and out of class, and course content and grading will emphasize communication and reproducibility of an analysis as much as scientific or technical completeness. The Course Syllabus provides an overview of the modules and topics covered as well as links to weekly reading, assignments, and any lecture material. This syllabus is preliminary and always subject to change.

Texts

We will use Grolemund and Wickham’s R For Data Science as the primary text for this course. A hard copy of the book is not required and the openly licensed full text can be found on the author’s website for this book. Additional reading material will be linked from the syllabus. Please be sure to review the relevant reading prior to each class session.