Managing Ecological Data in R: Introduction to Data Science and the Art of Wrangling for Ecologists - Online
- How data science principles and workflows inform ecological data management
- Managing ecological data with tidyverse tools
- Applying programming concepts (e.g., iteration) to wrangle ecological data
- How to efficiently work with big data for ecological applications
- Visualizing data using ggplot
- Communicating ecology with R scripts
- Version control (GitHub) command-line tools for file management
- Building reports and interactive web applications using Quarto and Shiny.
This course is not recommended for participants with no prior R experience. Additional learning material will be provided prior to and during the course for participants with limited previous experience.
- Dates
March 17 – May 11, 2025
- Location
Virtual (asynchronous)
- Available Formats
Graduate (CONS 697, 3 credits)
Professional Training (SMSC 0532, 8.2 CEUs)
- Cost
Professional Training: $500.00
- Deadlines
Application Deadline: February 14, 2025
Payment Deadline: Feb 28, 2025
Note that seats are filled as registrations are received and popular courses may fill well before the application deadline.
Meet the Faculty
Curriculum
Once data reach a certain size or complexity ecologists often struggle with managing their data. As big data increasingly becomes a component of ecological study, there is a developing need for understanding how to maintain large and complex datasets, prepare data for analysis, and develop a reproducible workflow. In this course, we will explore the management of ecological data using Program R. We will focus on the structure and linguistics of data in R, how to integrate R into a modern data science workflow, and explore how to think about ecological data in new ways. Participants will gain an in-depth understanding of the tidyverse packages. Through this process, participants will develop a flexible skillset for managing and exploring data. Each lesson will consist of a lecture, tutorial, and guided activities using real world ecological applications.
What’s Included
The total cost for professional training covers:
- Access to all recorded lecture material, coding demonstrations, assignments and solutions
- Access to optional weekly live sessions (Zoom) for review of weekly assignments and general Q & A with the instructor
Email [email protected] for additional information.
“This course changed the way I think about my data. I’m now a more effective coder, collaborator, and data manager that I was before. I wish I had taken this course before I even started my data collection!”
“This was an excellent course!…The quality of the course materials was incredibly high and practically useful with real-world data and issues, rather than canned exercises. Even though I use R almost daily in my job as a wildlife ecologist with a conservation organization, I still learned many new things that will enhance my work. I highly recommend the course!”
