R training course

A comprehensive introduction to R - The language widely used among statisticians and data miners for developing statistical software and data analysis.

Next 14 September (Remote)
3 days £1995 + VAT

JBI training course London UK

  • Clean, normalise and gather data from Excel, SPSS, .csv and other sources 
  • Learn the basics of tidyverse
  • Perform exploratory data analysis
  • Combine ggplot2 and tidyverse to calculate meaningful summaries
  • Design effective data visualisations and produce them from your data 
  • Gain an introduction to Business Intelligence and its tools
  • Gain an introduction to Web Scraping: programmatically extracting links and images from websites
  • Learn about Web Scraping with HTML and CSS 
  • Automate scraping with functions and parallel programming
  • Create, obtain and design maps and geographic data 
  • Visualise geographic markets interactively with the leaflet package



Our R for data analysts training course is designed for teams looking to replace or augment Excel, SPSS or SAS workflows with R.

It will help you gain a clear understanding of the principles of data analysis and wrangling, and how to use the versatile R programming language for data analysis.   

We will cover many different data formats and topics, so you will have the skills necessary to start working in R with most types of data. 


JBI training course London UK
JBI training course London UK

This course is aimed at those who want to incorporate R into their data analysis and business intelligence, particularly to replace existing Excel-based workflows. You’ll leave the course confident in using R to empower business decisions and harnessing data to understand and better communicate with your customers


Related Courses

Introduction to R and RStudio

•    Basics of the R language
•    Advantages of RStudio
•    Discovering, installing and using R packages

Data wrangling and tidyverse basics

•    Introduction
•    Importing data from Excel, .csv, SPSS and SAS files
•    Long vs Wide Data
•    Data.frames, tibbles and tidy data
•    Factors, Dates and other data types


Exploratory Data Analysis

•    Introduction
•    Summary statistics
•    Cross-tabulation and hierarchical group summaries
•    Quickly visualise and explore datasets with ggplot2

Business Intelligence

•    Introduction
•    Design effective data visualisations
•    Create functions to automate repetitive tasks
•    Use RMarkdown to create PDF, HTML and MS Word reports



Web scraping

•    Introduction
•    HTML and CSS basics for web scraping
•    Extracting links with rvest
•    Automating scraping with functions and parallel programming

Maps and Geographic Data

•    Introduction
•    Creating geoscatterplots
•    Obtaining shapefiles to create choropleth
•    Designing effective choropleth with leaflet


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