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What You'll Study
  • Basic coding in R for loops and custom functions
  • How data science principles and workflow inform ecological data management
  • Database structure and design
  • Online task automation using Application Programming Interfaces (API)
  • Managing ecological data in base R and tidyverse environments
  • Communicating ecology with R scripts
  • Version control (GitHub) command-line tools for file management
  • Using R as a Geographic Information System (GIS)
  • Visualizing data using ggplot and Leaflet
  • Building reports and interactive web applications using rMarkdown, Shiny, and html.

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.

Program Details
Dates

August 23 – October 11, 2021

Location

Virtual (asynchronous)

Available Formats

Graduate (CONS 697, 3 credits)

Professional Training (SMSC 0532, 4.0 CEUs)

Cost

Professional Training: $500.00

Deadlines

Application Deadline: July 26, 2021 

Payment Deadline: August 9, 2021

Note that seats are filled as registrations are received and popular courses may fill well before the application deadline.

Meet the Faculty

Brian Evans
Brian S. Evans
Migratory Bird Ecologist
Smithsonian Migratory Bird Center
Brian has been a researcher at the Smithsonian Migratory Bird Center since 2007, specializing in environment-bird interactions with a focus on the landscape ecology of Greater Washington, D.C.

Curriculum

Once data reach a certain size or complexity ecologists often struggle with the data management process. 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 package. Through this process, participants will develop a flexible skillset for managing and exploring data. Each lesson will consist of a lecture and guided lab activities using real world ecological applications.

Detailed Curriculum >>

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 SCBItraining@si.edu for additional information.

“This course was exactly what I needed. Prior to attending, my R abilities were haphazard and self-taught. I lacked a foundation to build a broader data science skill set. The instructor is engaging, passionate, and dedicated. I cannot say enough good things about this course.”

Course Participant 2019 On-campus offering

“This course is one of the few that offers a comprehensive approach to completing a project in R from start to finish. While other courses focus on using R for certain tasks, this course focuses on maximizing the student’s overall R skills.”

Course Participant 2019 On-campus offering
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