R Shiny Masterclass Series

Delve into R Shiny with us and learn from our dashboard experts in an Introductory and Advanced Masterclass, depending on your skill level.

R Shiny dashboards are a game-changer for effective and highly-customisable data visualisation of everything from simple research and sampling outputs to highly-dynamic and complex datasets.

While R Shiny is able to draw on the analytical power of R it can also be used to visualise any data or outputs from other statistical software such as STATA or SAS. Learn how to use R Shiny for your next data visualisation project and get insights into what R Shiny is capable of.

The training is collaborative, hands-on and supported by our online learning platform. If you are unsure if this training or R Shiny is right for you, please feel free to email us at events@epi-interactive.com for support.

Note: All our trainings are supported by fully qualified software engineers and interface design experts trained under our partnership with RStudio to bring best practice to participants; whatever their background.

 

Learn about the Introductory Masterclass
Learn about the Advanced Masterclass

Contact us at info@epi-interactive.com if you would like to discuss custom workshops for your organization or individual tutoring.

If you are interested in being notified about the upcoming events in our Masterclass Series, please register below.

Go to:  Schedule  |  Prerequisites  |  Resources

Introduction to R Shiny

3-week period   |   Interactive online sessions   |   Active learning support

Keen to branch out from Excel or are you currently using out of the box tools such as Tableau or Power BI that leave you frustrated? Struggling to get your app of the ground by yourself?

Join this class for a leg up into R Shiny programming. We will take you in a structured and time-efficient way through what you need to know and will cover e.g. R Shiny capabilities, design approaches, coding essentials and how to publish your newly created app. Case studies will be used to provide applied examples of R Shiny apps in action.

Where
Online Masterclass

When
Dates to be announced

If you are interested in being notified about the next events in our Masterclass Series, please register here.

Or contact us at info@epi-interactive.com if you would like to discuss custom workshops for your organisation.

Conference schedule

Session
start times

North America:
Los Angeles (PDT) 12pm
Toronto (EDT) 3pm

Europe:
London (BST) 8pm
Paris (CEST) 9pm

Oceania (next day):
Sydney (AEST) 7am
New Zealand (NZDT) 9am


Each session is 90min long (online Zoom tutorial). We also recommend to put some time aside in-between the sessions to work on assignments and to practice in your own time, ideally one hour.

 

Session 1

  • What is Shiny and why do we use it?
  • Introduction to RStudio Cloud interface, walkthrough and creating your first Shiny application
  • Introduction to Git Version Control

Session 2

  • R Shiny core concepts and mobile ready layout
  • HTML tags with Shiny, setting up navigation in your application, responsive layouts with the Bootstrap Grid

Session 3

  • R Shiny user interface components, reactivity and debugging
  • User inputs in Shiny, reactivity and debugging tools for Shiny applications

Session 4

  • Data sources and data processing in R Shiny
  • What format to use for data in your Shiny application
  • Using R to load and prepare your data for use in Shiny visualisations
  • Exporting processed data from Shiny applications

Session 5

  • Why use Plotly?
  • Types of plots, step-by-step creating Plotly charts & options available at each step.

Session 6

  • Maps and spatial visualisation with Leaflet
  • Case study: Spatial data visualisation with the AIS Explorer
  • Step-by-step creating a Leaflet visualisation & options available at each step

Session 7

  • Design considerations, Publishing R Shiny apps
  • Case study: Establishing equine primary care data surveillance in NZ
  • Design tips to improve the look/feel/UX of your Shiny application
  • Walk-through of publishing a completed Shiny app to shinyapps.io with scaling and performance settings.

Session 8

  • Case study: NZ Ministry of Health & the Annual Data Explorer
  • Top 10 tips for working with R and Shiny

Prerequisites

  • Basic R programming skills; we can provide online learning resources prior to the Masterclass if you haven’t used R before or are unsure if you have the required knowledge.
  • Some experience with HTML & CSS would be beneficial; however, it is not mandatory.

Resources

Provided

  • Interactive online sessions with individual feedback
  • Online support forum throughout with expert support
  • Online access to Masterclass material and coding examples

 

Software (instructions will be provided)

  • R and RStudio Desktop
  • R packages
  • Git version control
Go to:  Schedule  |  Prerequisites  |  Resources

Advanced R Shiny

3-week period   |   Interactive online sessions   |   Active learning support

This advanced Masterclass will expand on basic R Shiny functionality and teach you how to tackle more complex features in a structured way. We will dive into creating dynamic interfaces for multi devices and explore R packages that provide a richer user experience.

Where
Online Masterclass

When
Dates to be announced

If you are interested in being notified about the next events in our Masterclass Series, please register here.

Or contact us at info@epi-interactive.com if you would like to discuss custom workshops for your organisation.

Conference schedule

Session
start times*

North America:
Los Angeles (PDT) 1pm
Toronto (EDT) 4pm

Europe:
London (BST) 8pm
Paris (CEST) 9pm

Oceania (next day):
Sydney (AEST) 7am
New Zealand (NZDT) 9am


Each session is 90min long (online Zoom tutorial). We also recommend to put some time aside in-between the sessions to work on assignments and to practice in your own time, ideally one hour.

 

* These times are valid for session one, but will change during the Masterclass due to daylight savings. We are happy to discuss flexible arrangements for European participants.

 

Session 1

  • Recap of Introductory Masterclass
  • Expanding on Bootstrap
  • CSS Media queries
  • RenderUI for responsive layout creation

Session 2

  • Advanced reactivity and UX considerations
  • New ways of managing and using reactivity in R Shiny, such as observeEvent, isolate and reactiveValues.
  • Common considerations to improve your User Experience (UX)

Session 3

  • Useful R packages to extend core Shiny functionality
  • Further practice with new reactivity concepts, then introducing 3 useful R packages for Shiny development – DT, shinyjs and shiny.router.

Session 4

  • Managing complexity: modularising code with the module pattern
  • Case study: Epidemix.app
  • Refactoring your Shiny application into modules to minimise repetition and simplify your development in complex applications.

Session 5

  • Advanced data sources and processing
  • Integrating remote data sources with databases into your application, when and how
  • Techniques for improving the performance of your Shiny application
  • Scaling Shiny applications for production environments

Session 6

  • User authentication, permissions and management
  • Case study: Wildlife/SAVI
  • Creating a built-in user authentication system for your Shiny application

Session 7

  • Automated report generation: Exporting your Shiny application to a R Markdown or LaTeX document on demand & examples of custom visualisations.

Session 8

  • Programming sins and how to avoid them: 10 tips for common pitfalls when working with R Shiny
  • Discussion on new developments in R, Shiny and open source development

Prerequisites

  • You have joined the Introduction Masterclass or have worked with R and R Shiny before. You are familiar with elementary R Shiny UI and server functions.
  • Some programming experience in HTML would be beneficial; however, it is not mandatory.

Resources

Provided

  • Masterclass notes and instructions
  • Coding examples
  • Online forum and materials
  • Assignments between sessions

 

Software (instructions will be provided)

  • R and RStudio Desktop
  • R packages
  • Git version control