Introduction to R (online)
Consumer Data Research Centre (University of Leeds)
Dr Richard Hodgett, Dr Emmanouil Konstantinidis, Dr Alan Aritad Choicharoon
Entry (no or almost no prior knowledge)
This half-day online course will provide you with an introduction to the analytical programming language R. The course will focus on data pre-processing and visualisation, two of the key steps in understanding and generating insights from data. During the course you will learn about the benefits of R, how R handles different data types and how you can begin to use R to solve complex data science, machine learning and statistical problems. Specifically, you will work with R and its various packages to import, clean, manipulate and visualise real-world data. The course assumes no prior knowledge of R or statistics. This course contains lectures interspersed with hands-on practicals. The training will be hosted and delivered via MS Teams.
- To familiarise attendees with R, including the RStudio integrated development environment;
- To learn more about the broader R ecosystem – i.e. packages that extend the functionality of ‘base R’;
- To introduce R’s syntax and a variety of primary functions;
- To learn how to tidy and manipulate data using R;
- To learn how to utilise data visualisations to communicate your results.
Richard Hodgett started his career as an engineer, gaining experience working for an automotive design company in Belgrade (Serbia) and an industrial design company in Gothenburg (Sweden). After his PhD he worked as a Research Associate at Newcastle University where he developed a software tool for analysing complex decision problems in whole process design. Following this he worked in industry as an Innovation Specialist developing an electronic toolkit that is now used by some of the world’s leading companies in the pharmaceutical and speciality chemical sectors. In 2014, Richard joined the University of Leeds as a Lecturer in Business Analytics and Decision Science where he helped to establish the MSc in Business Analytics and Decision Sciences and the BSc in Business Analytics. Richard is active in both teaching and research. With regards to teaching, Richard has designed and developed three new masters level modules and one new undergraduate module. He also regularly delivers bespoke analytical training courses for individual companies and to wider groups through the Consumer Data Research Centre. With regards to research, Richard works mostly on applied analytical problems and leads a number of projects across a range of industries. He is currently working on research projects in the music industry, the pharma and speciality chemical industries, medicine, property and real estate, finance and policing. In 2018, Richard took over as Program Director of the MSc in Business Analytics and Decision Sciences.
Emmanouil Konstantinidis is Assistant Professor of Behavioural Science at Warwick University. Before this he was a lecturer in the Leeds University Business School and part of the Centre for Decision Research at the University of Leeds. He was a post-doctoral research fellow in the School of Psychology at the University of New South Wales in Sydney, Australia (2015-2017), and the Department of Social and Decision Sciences at Carnegie Mellon University in Pittsburgh, USA (2014-2015). During his time at these institutions he was involved in research projects pertaining to various issues in the field of decision-making and learning, including risky decision-making, decision-making in uncertain and dynamic environments, and computational modelling thereof. His main research interest is in cognitive psychology and decision-making with an emphasis on mathematical and computational modelling of the underlying psychological and cognitive processes. Specifically, one strand of his research concerns the examination of decision-making behaviour in uncertain and dynamic environments.
Alan Choicharoon is a Teaching Fellow in Business Analytics at Leeds University Business School where his research interests include: the integration of data, machine learning, and decision science in the music industry, as well as applied machine learning, application of deep learning/reinforcement learning in managerial decision making and interpretable artificial intelligence.
Is this course for you?
R is one of the most popular and fastest-growing programming languages today. It is also the most popular data mining tool in business and academia. One of the key strengths of R is its great versatility for data manipulation, exploration and testing, not to mention its ability to produce publication ready graphics. Despite this, R’s lack of “point and click” functionality can be intimidating for first time users. In this course we aim to demystify R by providing you with practical hands-on experience of using R to explore and analyse your data. The three hour session assumes no prior experience of R, just a keen willingness to learn! We hope to see you there.
£45 – Students; £70 – Academics, public and charitable sector employees; £150 – Private sector
Website and registration:
Yorkshire and Humberside
ICT and Software, R, Open source, programming, coding for beginners
Related publications and presentations: