R Essentials: A Rapid Course for Data Analysis, Visualisation and Communication
- Level(s) of Study: Professional / Short course
- Start Date(s):
- Duration: Four days / one day for individual workshops
- Study Mode(s): Short course
- Campus: Clifton Campus
- Entry Requirements:
More information
Introduction:
R is a powerful tool for statistical analysis and data visualisation. In the last two decades, R has grown to be one of the 10 most popular programming languages in the world. It's becoming increasingly used in academia for both teaching and research.
This course is aimed at anyone who has heard of R and would like to know how to use it to add meaning and understanding to data. R is freely available for the public to use and is a popular tool in all areas of academic scientific research, and also widely throughout the public, and private sector.
Make the course work for you
Depending on your experience and preference, you can choose to do all four days of the workshop or pick the days that are most relevant to you.
Facilities and equipment
Access to desktop computers is provided in our computing suite, but you may also wish to bring your own laptop so you can use R in a familiar context.
The practical work and working through examples yourself was great. This helped me take in the knowledge and allowed for better understanding of the examples. Additionally, the time allowed to work with your own data was very helpful as everyone has different things they want to get out of the workshop.
Great instruction from brilliant lecturers who were more than happy to impart their knowledge from their diverse fields. To see the approaches and different ways of using the R product was great. The graphical applications were really useful and something that from a commercial approach could work really well to convince businesses that data has a place in decision making.
Feedback from a previous Introduction to R course attendee.
What you’ll study
Your instructors have different and complementary styles of teaching, but we are united in adopting a pragmatic approach. At various points in the course we will embrace the potential of Large Language Models (LLMs; such as GPT-4) to assist you in using R. LLMs can help with:
- code generation
- code validation
- in understanding error messages.
Day One: Begin with R for Data Analysis
- the installation process of R
- using R help, your on-demand companion while navigating R
- preparatory data handling techniques
- performing simple statistical analysis.
Together these skills are your first step on your journey with R.
Day Two: Explore (your Data in Colour with) R Graphics
The second day will equip you with the skills to visualise data to yield professional graphics. By the end of the day, you will be able to visualise data and produce professional graphics, a vital skill for effective data communication. You will unlock:
- the robust core graphical capabilities of R, offering you a wide array of options for your data representation needs
- the art of customising R base graphics, enabling you to adapt visualisations to your specific requirements
- the impressive features of the ggplot2 package, a powerful tool for creating complex, multi-layered graphics.
Day Three: Develop Advanced R Skills
On the third day, you will:
- learn how to write your own R functions, allowing you to tailor solutions to your unique analytical challenges
- be introduced to advanced statistical analysis, further broadening your data interpretation capabilities.
Day Four: Discover R Markdown
On day four you will delve into the powerful world of R Markdown, an efficient and versatile tool for report preparation. R Markdown allows you to create reproducible documents that combine code, rendered output (such as figures), and text into a single coherent narrative.
You will learn to:
- embed R code into your reports, allowing you to dynamically generate content based on your latest data
- customise the layout and style of your reports, giving you the power to create professional, publication-quality documents
- generate reports in a variety of formats ensuring your work can be easily shared and understood by any audience.
How you’re taught
Who will teach me?
The course will be delivered by:
Dr Golnaz Shahtahmassebi - Applied statistician
Dr Golnaz Shahtahmassebi has more than 17 years of experience working with R and similar statistical packages. She uses R in her everyday research and teaching.
Dr Ben Dickins - Bioinformatician
Dr Ben Dickins is a biologist with a track record in genomic and bioinformatic analysis and 15 years of experience working with R and other high-level programming languages. Ben teaches R to students and has introduced many PhD students to statistical and bioinformatic analyses in R.
Dr Laurence Shaw - Data scientist.
Dr Laurence Shaw is a statistician who has been working in R for more than 10 years. He has supervised student's R-based industry projects.
Contact hours
The full course will run over four days, 10 am to 5 pm each day.
There is an option to study an individual day if you do not want to complete the full course. Please contact us for details.
Campus and facilities
This course is based at our Clifton Campus, home to the School of Science and Technology. Your workshops will take place in one of our networked computer suites, giving you access to all the software and equipment you'll need.
Entry requirements
Fees and funding
Full course (four days) - £1,000 + VAT
Two days (Monday and Tuesday or Wednesday and Thursday) - £600 + VAT
Payment is due at the time of booking.
How to apply
When we have confirmed dates you will be able to book your place via the NTU online store: