Discover how to use visualisation techniques in R to present key messages from complex data with hands-on examples, including building a dashboard to aid in identifying the impact, patterns, and trends present in a complex dataset.
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If you’re looking to learn how to create advanced visualisations in R, this course is ideal for you. An individual subscription gives you 3 months’ online access to:
As Well As
Our Industry and Actuartech Resource Libraries which feature curated additional content to assist you on your data science journey.
You can also request to access to a coding project to practice the skills you learn in this course.
Visualisations can be very useful at deriving insights from data. By using the open-source programming language R, this course will illustrate how visualisations can be optimised in the data science pipeline. The course aims to build on the initial visualisation techniques learned in our foundations in R course by way of a case study. We take a hands-on approach to this course and encourage students to explore further visualisations beyond those presented in the examples.
The course discusses two examples of case studies in order to illustrate how, with the use of visualisation techniques in R, we can better interpret the data we are working with. The aim of the first example is to show how visualisation techniques can aid in preliminary data analysis and to develop an understanding of how to best deal with partially complete data sources. In the second example, we address visualisation as it can be used for reporting. We refer to techniques for understanding time series data by visually comparing data overtime across various regions.
In both cases, we set out a scenario in which we analyse the available data set in order to derive insight, understand, and draw conclusions using visualisation techniques in R.
As a final visualisation technique, the course covers interactive dashboarding through the use of R Shiny. We provide an end-to-end tutorial for building a deployable COVID-19 dashboard.
If you're not already familiar with R, we recommend that you start with our Foundations in R course.
Chapter 1 introduces the data science pipeline, the datasets used, high level principles and considerations, and techniques for visualising data in R.
Chapter 2 sees us performing a preliminary analysis and visually comparing trends and various factors within the dataset.
Chapter 3 covers techniques for visualising time series data with a focus on identifying trends and adding multiple layers to a plot.
Chapter 4 discusses creating a simple, interactive dashboard by offering students a tutorial which they can use to create their own dashboard.
The Appendix and further resources section offers students additional sources that may assist in their visualisations journey.
We have tailored packages available to ensure that corporate teams have the option to attend structured live lessons by our tutors, and the option to request a practical assignment and bespoke feedback. Invoicing option available.
