We believe students learn best when working with their own data, so we design custom course materials that
teach skills and move forward projects. We are RStudio Certified Instructors of Tidyverse and Shiny.
teach skills and move forward projects. We are RStudio Certified Instructors of Tidyverse and Shiny.
Upcoming Courses
Transmitting Science
Barcelona, Spain
Introduction to R: Starting from Scratch [online]
Registration and payment via course website
This 5-day course is for ecologists, biologists, and other natural scientists who have never used R and, possibly, have never done any programming at all. By the end of the course, the participants should be able to import / export data-bases, manage data sets, carry out basic statistic analyses, draw high quality graphs, and program functions. Students are encouraged to bring data with them along with a “previously completed” statistical analysis or graphic. Ideally something fairly introductory and simple from the student’s own field of practice that you’ve worked with in Excel, SAS, or elsewhere. Students will work with these data on the last day to ensure they can load, check, tidy data and then perform the basic statistics or generate the graphs common in their respective disciplines. This time also usually provides opportunity to troubleshoot and learn to navigate web resources to find solutions to errors. Extra data will be available for students that prefer not to bring their own work or who want extra practice at specific skills. (November 11-15, 2024 live interactive sessions online)
Engage your audience with interactive data web-apps [online]
Registration and payment link available soon
This 3-day course is for individuals considering developing R Shiny apps to deliver their research. Thus, the goal will be to teach the skills necessary to translate static products (your current analysis in R) to dynamic products delivered via a simple web-based graphic-user interface. After a brief survey of the available basic tools (widgets such as slider bars, check boxes, and pick lists), we will move quickly to learn more advanced interactive features. Activities interspersed throughout the class will provide hands-on practice with sample biological and ecological data. By the end of the course, students will have built a portfolio of example code and will have designed, constructed, and published at least one example Shiny app. (January 7, 8 and 10, 2025, in-person instruction)
Clean and Manage your Data with R tidyverse [onine]
Registration and payment link available soon
This 3-day course will highlight useful tools of data manipulation from R’s Tidyverse suite of packages. The Tidyverse packages are built upon a philosophy of a tidy data structure: a rectangular (spreadsheet like) data structure where each row is one observation, each column is one variable, and each cell contains one value. The Tidyverse packages follow a set of shared rules and share a common syntax style, both designed to maximize code readability and reproducibility. The emphasis of this short-course will be on the core packages dplyr and tidyr in combination with packages specific to manipulating date-time data (lubridate), text data (stringr), and categorical data (forcats). Class exercises will provide practice restructuring data, value replacement, group operations, and row- and column-wise functions. (April 28-30, 2025, live interactive sessions online).
Communicate your Data with Beautiful Graphs from R ggplot [online]
Registration and payment link available soon
In this 3-day course, students will learn to build and customize ggplot graphics. The ggplot2 package is built upon the Grammar of Graphics of Leland Wilkenson which posits that how all quantitative data visualizations share common component elements. Learning this grammar enables efficient construction (or modification of) of professional graphics. This course will teach the core elements (data, aesthetics, and geometries) as well as more advanced topics of information communication and styling (annotation, themes, and facets). Class exercises will cover common visualization tasks such as rescaling axes, managing legends, reordering categories, and highlighting data elements of special interest. (July 28-30 2025, live interactive sessions online).
Yukon, Canada
When home in Yukon, Dr. Drew typically offer several short workshops either at (co)space or by request at client sites. In addition to the themes outlined above, she has also taught courses focused on R Markdown, Spatial Data in R, and Time Series Data in R. If you would like to receive an email when she next schedules Yukon courses or if you have a special request for a course, use the contact form.
Custom Workshops and On-Call Data Expertise
KDV has developed and taught special topic R workshops for several clients including The Nature Conservancy, United State Fish and Wildlife Service, United States Forest Service, Department of Fisheries and Oceans Canada, Parks Canada, Yukon People Metrics, Analytics, and Projects, and Environment Yukon. We also serve as on-call data and R experts for some clients via retainer contracts. If you are interested in either of these services, please use the contact form.
Barcelona, Spain
Introduction to R: Starting from Scratch [online]
Registration and payment via course website
This 5-day course is for ecologists, biologists, and other natural scientists who have never used R and, possibly, have never done any programming at all. By the end of the course, the participants should be able to import / export data-bases, manage data sets, carry out basic statistic analyses, draw high quality graphs, and program functions. Students are encouraged to bring data with them along with a “previously completed” statistical analysis or graphic. Ideally something fairly introductory and simple from the student’s own field of practice that you’ve worked with in Excel, SAS, or elsewhere. Students will work with these data on the last day to ensure they can load, check, tidy data and then perform the basic statistics or generate the graphs common in their respective disciplines. This time also usually provides opportunity to troubleshoot and learn to navigate web resources to find solutions to errors. Extra data will be available for students that prefer not to bring their own work or who want extra practice at specific skills. (November 11-15, 2024 live interactive sessions online)
Engage your audience with interactive data web-apps [online]
Registration and payment link available soon
This 3-day course is for individuals considering developing R Shiny apps to deliver their research. Thus, the goal will be to teach the skills necessary to translate static products (your current analysis in R) to dynamic products delivered via a simple web-based graphic-user interface. After a brief survey of the available basic tools (widgets such as slider bars, check boxes, and pick lists), we will move quickly to learn more advanced interactive features. Activities interspersed throughout the class will provide hands-on practice with sample biological and ecological data. By the end of the course, students will have built a portfolio of example code and will have designed, constructed, and published at least one example Shiny app. (January 7, 8 and 10, 2025, in-person instruction)
Clean and Manage your Data with R tidyverse [onine]
Registration and payment link available soon
This 3-day course will highlight useful tools of data manipulation from R’s Tidyverse suite of packages. The Tidyverse packages are built upon a philosophy of a tidy data structure: a rectangular (spreadsheet like) data structure where each row is one observation, each column is one variable, and each cell contains one value. The Tidyverse packages follow a set of shared rules and share a common syntax style, both designed to maximize code readability and reproducibility. The emphasis of this short-course will be on the core packages dplyr and tidyr in combination with packages specific to manipulating date-time data (lubridate), text data (stringr), and categorical data (forcats). Class exercises will provide practice restructuring data, value replacement, group operations, and row- and column-wise functions. (April 28-30, 2025, live interactive sessions online).
Communicate your Data with Beautiful Graphs from R ggplot [online]
Registration and payment link available soon
In this 3-day course, students will learn to build and customize ggplot graphics. The ggplot2 package is built upon the Grammar of Graphics of Leland Wilkenson which posits that how all quantitative data visualizations share common component elements. Learning this grammar enables efficient construction (or modification of) of professional graphics. This course will teach the core elements (data, aesthetics, and geometries) as well as more advanced topics of information communication and styling (annotation, themes, and facets). Class exercises will cover common visualization tasks such as rescaling axes, managing legends, reordering categories, and highlighting data elements of special interest. (July 28-30 2025, live interactive sessions online).
Yukon, Canada
When home in Yukon, Dr. Drew typically offer several short workshops either at (co)space or by request at client sites. In addition to the themes outlined above, she has also taught courses focused on R Markdown, Spatial Data in R, and Time Series Data in R. If you would like to receive an email when she next schedules Yukon courses or if you have a special request for a course, use the contact form.
Custom Workshops and On-Call Data Expertise
KDV has developed and taught special topic R workshops for several clients including The Nature Conservancy, United State Fish and Wildlife Service, United States Forest Service, Department of Fisheries and Oceans Canada, Parks Canada, Yukon People Metrics, Analytics, and Projects, and Environment Yukon. We also serve as on-call data and R experts for some clients via retainer contracts. If you are interested in either of these services, please use the contact form.