Interactive Visualization with R for Social Scientists

Interactive Visualization with R for Social Scientists
Start date:
Buy now

What you'll learn

What you'll learn

Not sure where to start or which course to take next? Check out our handy learning pathways.

What you'll learn on this self-paced online course

Learn the techniques and tools for presenting data in visually attractive and interactive ways using the R programming language. This course is perfect for social scientists who are looking to use and develop their existing R skills to communicate their research in a new and engaging way.

Not familiar with R? Try our Introduction to R course first.

By the end of this course you will be able to:

  • Understand the need for interactive visualizations and reports, and the associated workflows

  • Produce a range of visualizations relevant to the available data

  • Produce and publish a report that contains appropriate interactive visualizations to tell a story about the data

35 hours to learn
3 months access



Enroll a group
Looking to upskill a group of 5 or more learners or get access for your institution? Find out more

Inconvenient Start Date?
Register interest for future dates

Course modules

Course modules

There are four modules in this course


This module gives an overview of interactive visualization, and explains how to set up the various toolkits you’ll be using throughout the course

Getting ready

In this module, you’ll learn about: a typical visualization workflow, how to plan a story, how to prepare your data to build visual stories and a simple example of a workflow..

Interactive Charts and Maps

In this module you'll learn how to produce: charts with plotly and highcharter, an interactive map with leaflet and plotly and a network chart using tibbles and visNetwork.

Shiny basics and R markdown

In this module, you'll learn how to insert interactive charts and add controls and reactive events into a Shiny app; how to create an interactive presentation using R Markdown in RStudio; and how to publish these toolkits to the web.

Try it out

Try it out

Try it out



What our learners say





A basic understanding of the R programming language is required. A prior understanding of the pipe operator %>% would be helpful but will be covered briefly in the course



Frequently asked questions

How is the course structured?

The course is organized into a set of four interactive learning modules, and you should work through the modules sequentially. The modules contain a number of topic pages, each including a video to walk you through the concept and interactive text to reinforce what was covered in the video, quick questions and knowledge checks.

What other types of activities does the course include?

There are three additional types of activity in your course to facilitate deeper learning:

  1. Match: These activities require you to have a go at a task offline, then select the correct solution
  2. Guided: These are multi-part match activities so you do a part of the task then submit your solution, which unlocks feedback on your attempt and the next part of the task
  3. Structured: This is a more complex offline task. To see the Tutor’s solution you need to share your attempt at the task and your reasoning. You also get to see other participants' attempts and are encouraged to engage in discussion. The Tutor will then share further feedback

The vast majority of topics in the course are fundamentally practical. You are strongly encouraged to recreate and run the code as you work through them, and complete knowledge checks and activities.

How long will I have access to the course for?

You will have 3 months' access to this course.

During the first 4 weeks of your course you will receive learning support from Martin, your instructor. We recommend working through as many modules as possible in these initial 4 weeks so that you can make the most Martin’s expertise. He’ll be on hand to answer any questions, or help you if you get stuck.

After the learning support period, you’ll still have access to the course materials but you won’t receive assistance from the instructor. SAGE Campus will help you with any IT or platform issues you might have throughout the course.

What software do I need for this course?

It’s a good idea to install R Studio prior to starting this course as this will be used throughout the course (this should take about 10 minutes to do). There are a number of R libraries that are required but these will be discussed and can be installed via R Studio.

Do I need to buy any of this software?

No, they are either open source or have community (free) versions.

What do I need to participate on this course?

A computer or laptop with the suggested software and a modern browser e.g. Internet Explorer 10+ or the latest versions of Chrome and Firefox.

Can I do this course on my mobile device?

While you can access the course on your mobile device, go through the content and answer questions, you will need a desktop or laptop computer to practice and complete the activities that require you to write and/or test code.

Can't find what you're looking for? Contact Us



V2 Course Page Tag