Skip to main content

EDS 220

Working with Environmental Datasets

Carmen Galaz GarcĂ­a

Units: 4


Introduces students to the broad range of data sets used to monitor and understand human and natural systems. Course will cover field and station data, remote sensing products, and large-scale climate datasets including climate model projections. Skills will include evaluating data collection and quality control methods used in existing datasets, and working with existing databases of time-series and spatial information including cloud computing databases and new repositories of environmental datasets. Students will learn basic workflows for selecting, obtaining, and visualizing datasets, and best practices for reliable data intercomparisons. Students will gain hands-on experience with an environmental dataset of their choice by developing tutorial Jupyter notebook materials for a relevant use case.

All participants are expected to (a) be familiar with the Python programming language and comfortable working on a Jupyter notebook, (b) have a GitHub profile, and (c) be familiar with using git from the command line. 

  • For MEDS students: EDS 217 Python for Environmental Data Science fulfills these requirements.

  • All non-MEDS students interested in taking the course should email the instructor explaining their experience with required skills and provide a Python code sample accessible through a GitHub repository.

Course Syllabus: Fall 2023

Course Website


Return to MEDS Course List

arrow up icon