What is R?
R is a programming language and computing environment. It's designed specifically for statistics and data analysis. In the last two decades, R has grown to be one of the 10 most popular programming languages in the world.
R has between 10 and 20 million regular users. There are over 18,000 add-on statistics and data science packages available. It's widely and increasingly used throughout academia for both teaching and research.
Outside academia, R is also used in:
- the internet and tech sector
- the healthcare sector
- the financial services industry
- the public sector.
R is a dominant tool in any sector of the economy where data analysis plays a vital role. Learning to use R and its most popular packages has become essential in many industries. R users are increasingly sought after.
The benefits of learning R
By learning R or by expanding your current R skillset, you can:
- become a more effective and efficient data analyst
- efficiently process and manipulate large and complex data sets
- produce visualizations to explore patterns in the data
- perform more sophisticated statistical analyses.
Who can attend an R short course
This is a series of six workshop-based online continuing professional development (CPD) courses. Each course is two or three days in duration. We've designed them for research scientists and data analysts who:
- are at any stage of their careers, and
- are seeking to learn R, or
- wish to advance their R-based computational statistics and data science techniques and skills.
Foundation short courses
These courses will introduce R and cover general topics like data manipulation and processing (also known as "data wrangling") and data visualisation.
Introduction to statistics using R and Rstudio
This two-day foundation course is aimed at anyone interested in using R for data science or statistics. R is widely used in all areas of academic scientific research, and also widely throughout the public, and private sector.
Introduction to Data Wrangling using R and tidyverse
This two-day foundation course is aimed at anyone involved in real world data analysis, where the raw data is messy and complex. Data analysis of this kind is practiced widely throughout academic scientific research, as well as widely throughout the public and private sectors.
Introduction to Generalized Linear Models in R
This two-day intermediate course is aimed at anyone interested in advanced statistical modelling, as it's practiced widely throughout academic scientific research, as well as widely throughout the public and private sectors.
Intermediate short courses
These courses cover the widely used statistical modelling methods of generalized linear models and mixed effects and multilevel models.
Introduction to Multilevel (hierarchical, or mixed effects) Models using R
This two-day intermediate course is aimed at scientific researchers and data analysts interested in advancing statistical knowledge and techniques beyond standard regression analysis to regression methods suitable for modelling clustered or hierarchical data sets, which are very common in the social and biological sciences.
Introduction to Data Visualization with R using ggplot
This two-day foundation course is aimed at anyone interested in data visualization using R. Data visualization is a major part of data science and statistical data analysis, and R is the most widely used program for data science and statistics.
Advanced short courses
Our advanced course in R covers Bayesian data analysis and Bayesian statistics.
Introduction to Bayesian Data Analysis with R
This three-day advanced course is aimed at anyone looking to learn and apply Bayesian data analysis in any area of science, including the social sciences, life sciences, physical sciences. No prior experience or familiarity with Bayesian statistics is required.