This online course will be delivered over two days using a combination of live lectures and practical sessions guided by course tutors. All live lectures will be recorded. The course will run from 9:15am to 4:30pm both days.

We strongly encourage active participation to ensure you get the most from the course, especially during practical sessions in break out groups. Please ask questions, engage with the course tutors and fellow participants, and complete feedback so we can continue to improve our offering.

By the end of the course participants should be able to:

1. create high-end graphical figures, using the ‘ggplot2’ package in R;
2. customise plot features;
3. add, amend and customise plot layers;
4. produce interactive graphs and display them online;
5. generate dynamic documents using R Markdown;
6. use R Markdown documents to produce pdf, html and Microsoft word reports; and
7. develop simple web applications using Shiny to present results in tabular and graphical form.

The course is intended for individuals with an interest in data visualisation, reproducible research and data science. The course topics apply to nearly all areas of quantitative research, but the course is focussed on visual presentation of data rather than statistical analysis methods.

It is assumed participants will have attended the Introduction to R course or have a similar level of experience with R and/or RStudio. This course is not intended for people who have never used R before.

This is a two day course with practicals and demonstrations to provide participants with skills in using R to visualise data, build dynamic reports, and develop web applications.

The course will cover:

1. basic and advanced R graphics: creating simple and advanced informative graphics using 'ggplot2' that include bar plots, histograms, scatter plots, density plots, heat maps and many more;
2. customise graphs: introduce geoms, stats, layers, scales, axes, legends, facets, colour themes, general themes, fonts and grid layouts;
3. interactive graphs: introduce the 'ggplotly' tool, used to produce web-based graphs where a user can interactively select, display and highlight visualised data points, lines, etc;
4. dynamic documents: illustrate how R Markdown can be used to create dynamic reports that incorporate descriptive text and statistical plots, with the code used to perform the analyses and the generate results for reproducibility; and
5. web applications: demonstrate how R can be used to develop simple web applications to display results or perform an analysis online.

This course is lead by Dr Aimee Hanson and Dr Sarah Watkins, senior research associates based at the Integrative Epidemiology Unit at the University of Bristol. Both have an extensive background in programming and data visualisation in R, which they use regularly for their own research applications.

To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:

Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.

Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms & conditions, which can be read in full here.

For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.

Participants are granted access to our virtual learning platform (Blackboard) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.

To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.

All course participants retain access to the online learning materials and recordings for 3 months after the course. 

University of Bristol staff and postgraduate students who do not wish to attend the full course may instead register for access to the 'Materials & Recordings' version of this course: Further information and bookings.

100% of attendees recommend this course*.
*Attendee feedback from 2022.

Here is a sample of feedback from the last run of the course:

“Overall I think this was an excellent course. The course was well run and very organised, everything kept to time and the balance between taught and practical components worked well. The tutors were clearly very knowledgeable and passionate about the subject and presented the information in an engaging way” - Course feedback, March 2022

“Great introduction to RMarkdown and Shiny - definitely feel inspired to use these in my own research now!”- Course feedback, March 2022

“The content was well explained. Good amount of time dedicated to lectures/ practicals and breaks. Excellent support by tutors"- Course feedback, March 2022

“There was a nice balance of lectures and practicals, and a nice amount of breaks which are especially needed for an online course”- Course feedback, March 2022

“The pace was perfect throughout the course. Glitches were dealt with swiftly, content built up throughout the course. Plenty of feedback and use of private rooms to solve technical issues. Consistent use of 1 topic as exemplar for new learning. Answers given at outset enabling those with technical issues to keep up” - Course feedback, March 2022

“Very helpful course tutors on hand for troubleshooting, excellent presentations and practical materials” - Course feedback, March 2022

“Really good sessions, well presented lectures with sufficient time for questions and followed up with great practical classes to give us an opportunity to have a go at what had been taught in the lecture” - Course feedback, March 2022

“Well structured course, nice examples” - Course feedback, March 2022

“The tutors were really knowledgeable, enthusiastic and supportive and made it a really welcoming, friendly and encouraging learning environment (which I think is even harder to achieve when it's online). I thought the lectures were paced well for those who had little experience using the packages before. It was all very well explained and helped to make it much simpler to understand and gave me confidence to go and immediately use it in my work after the course. The content and discussions during the course were really useful and highly relevant to my work” - Course feedback, March 2022

“Clear and realistic objectives. Useful resources/material. Great course instructors and timing” - Course feedback, March 2022

“Really amazing content - it was eye-opening to the different things that can be done with R for graphical presentation! I think the first day with ggplot was excellent and the second day covering RMarkdown and Shiny was a great introduction and demystified the more 'advanced' topics” - Course feedback, March 2022