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
This module gives an overview of interactive visualization, and explains how to set up the various toolkits you’ll be using throughout the course
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..
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.
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.
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
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.
There are three additional types of activity in your course to facilitate deeper learning:
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.
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.
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.
No, they are either open source or have community (free) versions.
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.
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.
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