Data Science in Earth and Environmental Sciences

Course
R
Python
Environmental data science
An approximately 30-hour online course introducing R, Python, and environmental data analysis.

About the course

Learn introductory R and Python programming through Earth and environmental science applications. The course connects coding practice to data analysis and machine learning, including examples involving wildfire and groundwater quality.

  • Audience: Learners with geoscience interests and varied programming experience; the host lists no prerequisites.
  • Estimated time: Approximately 30 hours.
  • Tools: An internet-connected computer, R/RStudio, Python/Jupyter Notebook, and a CUAHSI HydroShare account.
  • Course authors listed by the host: Tao Wen, Christina Bandaragoda, and Lucas Harris.
  • Host: HydroLearn.

Activities build toward designing a scientific question, writing and adapting code, and developing a reproducible data-analysis workflow. Consult HydroLearn for course access and enrollment information.

Open the course on HydroLearn

Citation

The host recommends: Bandaragoda, C., and Wen, T. (2020). Data Science in Earth and Environmental Sciences. HydroLearn.

Illustration of a robotic hand and a human hand reaching toward a globe, with network patterns and leaves.

Illustration created with the assistance of DALL·E.