EDS 214
Course Name
Analytical Workflows and Scientific Reproducibility
The generation and analysis of environmental data is often a complex, multi-step process that may involve the collaboration of many people. Increasingly, data scientists use tools that document and help to organize workflows to ensure reproducibility, shareability, and transparency of the results. The goal of this course is to enable MEDS students to collaboratively create reproducible analyses. Essential skills and concepts are: 1) Automate the steps in an analytical workflow using scripts, 2) Organize workflow components modularly, 3) Document individual components and their relationships, 4) Scale workflows for computational performance and large datasets, 5) Collaborate in a team to develop a workflow.
Course Syllabus: Summer 2025