Training and Workshops
These interactive workshops have been delivered in-person and remotely to individuals and small groups of up to 14 people. Some have also been be delivered online for groups of up to 500 people.
R
Introduction to data analysis with R
An introductory level course for beginners to R, covering data import, summary statistics, and visualisation.
Learning outcomes:
- Understand the difference between R and RStudio, and how RStudio works.
- Be able to complete simple operations in R such as saving objects, performing calculations, and reading in data.
- Calculate summary statistics, and make simple plots of data.
Pre-requisites:
- None.
Time: 6 hours.
Course website: nrennie.rbind.io/training-intro-to-r
Writing better R code
A course for intermediate R users who want to improve the quality of the code they are writing.
Learning outcomes:
- Understand how write to better code that is well-structured and easier to read.
- Be able to organise multiple R scripts in a project.
- Know how to manage dependencies on different R packages.
Pre-requisites:
- Basic knowledge of R.
Time: 2 hours
Course website: nrennie.rbind.io/training-better-r-code
Build an R package
An intermediate R course for people who want to build their first R package. There are many benefits to turning your R scripts or functions into a package, like making your code easier to re-use, easier to share with others, easier to document, and easier to test. But the process of writing a package can feel intimidating, especially if you haven’t done it before. But it doesn’t need to!
Learning outcomes:
- Know what things you need to make a package and how to create them
- How to write functions (in a package-friendly way) and add them to a package
- How to write documentation and examples for functions
- Best practices for package development
- How to share your package with other people
Pre-requisites:
- The session aims to be introductory, so you don’t need any previous experience of building R packages (or even writing functions!) but some basic knowledge of R will be useful.
- The session will use the following R packages:
devtoolsusethisroxygen2stringr(optional)
Time: 2 hours.
Course website: nrennie.rbind.io/training-r-packages
Introduction to Shiny
A short introductory course to creating web applications using Shiny in R, suitable for those with some existing experience of R.
Learning outcomes:
- Understand the different components of a Shiny app - UI and server.
- Be able to build a simple Shiny app with user inputs and dynamic outputs.
- Understand options for deployment - to get your Shiny app out into the world!
Pre-requisites:
- Basic knowledge of R.
Time: 1 hours
Course website: nrennie.rbind.io/training-intro-to-shiny
Introduction to machine learning with tidymodels
A course covering random forests, support vector machines, and LASSO regression and how to implement them in {tidymodels}. Suitable for those with some experience of R and statistics.
Learning outcomes:
- Be able to use some common machine learning techniques such as Lasso regression, random forests and support vector machines.
- Fit these models in R using {tidymodels}.
- Understand common concepts of machine learning such as cross-validation, hyperparameter tuning and model evaluation.
Pre-requisites:
- Familiarity with some statistical concepts such as correlation, variability, and simple linear regression.
- Being reasonably comfortable with data wrangling using {dplyr} and {tidyr}.
Time: 2 hours
Course website: nrennie.rbind.io/training-intro-to-tidymodels
Quarto
Introduction to Quarto
An introductory-level course on Quarto (an open-source scientific and technical publishing system that allows you to combine text, images, code, plots, and tables in a fully-reproducible document).
Learning outcomes:
- Understand what Quarto is and why it is useful for reproducible reporting.
- Be able to create simple HTML documents, PDFs, and revealjs presentations, with embedded code.
- Be able to set different options for: code execution, figure options, animation, and more!
Pre-requisites:
- Basic knowledge of R, Python, Julia, or ObservableJS.
Time: 2 hours
Course website: nrennie.rbind.io/training-intro-to-quarto
Styling documents using Quarto extensions
An intermediate-level course covering styling HTML and PDF documents, for those with some experience of Quarto.
Learning outcomes:
- Know how to customise Quarto HTML outputs (including documents and revealjs slides) using CSS and PDF documents using LaTeX.
- Understand what Quarto extensions are, how to install them, and use them for styling documents.
- Know what the components of Quarto extensions are and be able to create a simple style extension to make your documents look more professional and recognisable.
Pre-requisites:
- (Ideally) able to create simple Quarto documents.
- No prior knowledge of CSS or LaTeX required.
Time: 2 hours
Course website: nrennie.rbind.io/training-quarto-extensions
Other
Data visualisation
An introductory-level course to data visualisation, including best practices and how to apply them.
Learning outcomes:
- Understand why data visualisation is necessary, and what it can be used for.
- Explore common types of visualisation and how they can be leveraged to uncover relationships in data.
- Describe and apply principles of good data visualisation, and discuss the limitations of principles.
- Be able to adjust default settings of charts to get a more truthful representation of your data.
Pre-requisites:
- None.
Time: 1 hour
Course website: nrennie.rbind.io/training-data-visualisation
Git and GitHub for R users
An introductory-level course for R users getting started with Git and GitHub for version control, using RStudio as an IDE.
Learning outcomes:
- Understand why version control is necessary and useful.
- Be able to collaborate on code using Git and GitHub from RStudio.
- Edit code, track changes, and review code using GitHub.
Pre-requisites:
- Basic knowledge of R.
Time: 2 hours
Course website: nrennie.rbind.io/training-git-r