Learning R

Coursera Courses

Past R Users Group Presentations

  • 8 December 2023: Julian Matthewman demonstrated GitHub CoPilot in RStudio, by solving Advent of code puzzles. Recording here.
  • 27 September 2023: Ed Parker presented on the shiny package for making interactive web apps in R. Recording here, slides here, and code on Ed’s Github page- Vaccine tracker here and Covid tracker here
  • 29 September 2023: Malcolm Mistry presented on the rgee package for using Google Earth Engine for R. Recording here, slides here, demo script here, configuration script here (both temporarily added as word docs- paste into an R script) and sample locations data here
  • 4 May 2023: Amy MacDougall presented on how to compute and plot predictions, slopes, marginal means, and comparisons for different statistical models with the marginaleffects package. Recording here and slides here.
  • 10 Mar 2023: Joshua Lambert gave and introduction to R package developement. Recording here. Julian Matthewman demonstrated how to work with multi-file & larger-than-memory data with the arrow package and parquet files (see cheatsheet). 
  • 18 Nov 2022: Kate Nelson presented: An introduction to Advent of Code. Arturo de la Cruz Libardi presented an introduction to Rctapi and rctexplorer. Recording here and Arturo’s GitHub page with links to packages here 
  • 14 October 2022: Amy MacDougall and Julian Matthewman presented on getting started with Quarto. Recording from Amy’s presentation here
  • 15 Jul 2022: Pierre Masselot presented: Coding on the shoulders of giants: the development of the cirls package. Recording here and package here
  • 1 Apr 2022: Julian Matthewman presented on reproducible computation at scale using the targets pipeline tool – slides here script here and recording here
  • 17 June 2022: Hope Simpson and Will Oswald presented on using RMarkdown to create interactive dashboards to monitor research and implementation activities. Recording here and Hope’s code and data here
  • 25 Feb 2022: William Oswald presented on Git and Github – slides here and recording here
  • 28 May 2021: Naomi Waterlow presented on web scraping using the rvest package – materials here and here
  • 19 Apr 2021: Andrei Morgan presented on analysing sensitive data via DataSHIELD – materials here
  • 07 May 2020: Calum Davey presented on how to produce a reproducible PhD using Bookdown – materials here
  • 27 Mar 2020: Amy MacDougall, Carl Pearson, Julia Shen, Lauren Bell, Martina Cusinato, and Calum Davey presented their plots – materials here
  • 31 Jan 2020: Michelle Clements talked about using Shiny – materials here
  • 28 Jun 2018 and 12 Dec 2019: Chris Jarvis presented on how to use the tools in the Tidyverse, covering dplyr and piping — materials here
  • 29 Nov 2019: Chathika Weerasuriya explained how to use Git to keep track of changes that you make to your projects — materials here
  • 27 Sep 2019: Kamaryn Tanner talked about machine learning in R using Super Learner — materials here
  • 26 Jul 2019 and 31 Oct 2019: Sam Clifford led a seminar on ggplot2 – one of the most popular data visualisation packages in R, but also one of the least accessible without some introduction – materials here
  • 30 May 2019: Rosalind Eggo and Hunter Blanks introduced us to the wonderful world of Git — materials here, and Hunter’s nice hand-drawn diagrams are available here
  • 28 Jun 2019: Jenny Thompson and Amy Mulick explained how to do parallel processing using two alternative methods, based on the package parallel (materials here) and foreach/doParallel (materials here), respectively. Carl Pearson provided some additional info on parallelisation within the LSHTM HPC system (materials here) and parallelisation through data table (materials here)
  • 26 Apr 2019: Carl Pearson presented on data.table and make files – slides here, and .R files here
  • 4 Apr 2019: Hannah Brindle and Hope Simpson presented on using spatial data in R – materials here
  • 01 Mar 2019: Leonard Roth presented on using the package Rcpp as an alternative to using loops in R, which are known to be slow. Moving on from using loops is a difficult but necessary step for those transitioning from Stata to R – materials here
  • 31 Jan 2019: Matteo Quartangno presented on missing data in R — NA, NULL, NaN; what do they mean, and how do we deal with them? – scripts here and slides here
  • 29 Nov 2018: Peninah Murage talked about how to use the high performance cluster available at the school – materials here
  • 25 Oct 2018: Antonio Gasparrini presented on regression in R, getting us thinking again about the bread-and-butter of statistical research with R – materials here
  • 27 Sep 2018: Liz Fearon and Nick Magill shared their experiences of producing Shiny Apps in R  – materials here
  • 20 July 2018: Claudio Fronterre presented on reproducible research in R – materials here