Learn fundamental Environmental Data Science (EDS) skills using Python and GitHub. Here, participants will learn how to use open EDS tools, including the following Python libraries: Pandas, Geopandas, Rioxarray, Folium and Matplotlib.

Learners will also get to practice their GitHub skills with GitHub Classroom, GitHub Pages and GitHub Codespaces. Course materials will be made available using cloud-based Jupyter Notebooks that learners will be able to take with them upon completion.

Eligibility

All members of the general public, including those from corporations, community members, and others, are welcome to participate in this micro-credential program.

Delivery Mode

Online.


Credit Status

Noncredit

Academic Level

Professional

Time to Completion

Weekly meetings for four consecutive weeks.

Requirements

Participants will be required to: 

  • Attend all regularly held synchronous meetings.

  • Participate in all asynchronous discussions.

  • Complete all assigned work (weekly homework, final project/presentation).

Criteria

At the completion of the micro-credential, learners will be able to: 

  • Complete the following tasks with Python:

    • Open, clean, describe and plot data using Pandas.

    • Create plots with Matplotlib.

    • Create maps with Folium.

    • Work with vector spatial data using Geopandas.

    • Work with raster spatial data using Rioxarray.

  • Complete the following tasks with GitHub:

    • Create a professional portfolio pages using GitHub pages.

    • Create a cloud-based programming environment using GitHub codespaces.

    • Accept and submit assignments with GitHub Classroom.

    • Learn how to use GitHub for collaboration.

Skills

  • Coding
  • Data science fundamentals
  • Data visualization
  • Environmental data science
  • GitHub
  • Jupyter Notebook
  • Open science
  • Python (pandas, matplotlib, geopandas, rioxarray, folium)
  • Science communication