This one-day course (10am-4.30pm) follows on from the “Introduction to R” training run by Richard Hodgett, Emmanouil Konstantinidis, and Alan Choicharoon, and will explore more advanced functions in R. This course contains lectures interspersed with hands-on practicals. The training will be hosted and delivered via MS Teams.
To introduce attendees to more advanced capabilities within R, including the RStudio integrated development environment, including:
IF statements and WHILE/FOR loops;
Mark down and reporting;
Building interactive web apps with Shiny;
Use of R on the Cloud using MS Azure.
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.
R is one of the most popular and fastest growing programming languages and is 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. This course is for those who already have some experience of using R (e.g. have attended CDRC’s “Introduction to R” training, or completed Data Camp’s online module in R).
£70 – Students
£150 – Academics, public and charitable sector employees
£350 – Private sector