Course aims

The Data Science in Ecology and Environmental Science course aims to promote the development of quantitative skills among 3rd and 4th year students (and MSc students when appropriate) at the University of Edinburgh using interactive workshops and an online learning platform.

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To find out more about the course, you can also check out the course details and syllabus.

Key skillsets in ecological and environmental sciences include quantitative skills such as data manipulation, data visualization, coding, statistics, simulation, and more - together this skillset can be called data science. Data Science in Ecology and Environmental Sciences will teach quantitative skills including data management, data visualization, programming, simulation and statistical analysis. The course will teach about the field of data science and how it applies to the disciplines of ecology and environmental science. Students will learn about best practices in data science and will contribute to peer learning. Skills will be taught using an online problem-based learning approach and in class tutorials and discussions.

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Learning outcomes

  • Understand key quantitative skills in the disciplines of ecology and environmental sciences including data management, data visualization, programming, simulation and statistical analysis.
  • Use data science tools to address research questions and challenges in ecology and environmental sciences.
  • Implement version control to back up work, code collaboratively and write reproducible workflow reports.
  • Practice teaching quantitative skills and develop an online tutorial.
  • Learn about the field of data science and future careers in this area

    • Teaching team

    Isla Myers-Smith (Course organiser)

    Gergana Daskalova (PhD tutor)

    Elise Gallois (PhD tutor)

    Maude Grenier (PhD tutor)

    Joseph Everest (PhD tutor)

    Shawn Schneidereit (Tutor)

    With support from the larger Coding Club team for the development of online tutorials.

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