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 COURSE 6 January (3 days £1995 + VAT) BOOK NOW

JBI training course London UK

  • Explore and summarise your data with the tidyverse with Exploratory Data Analysis
  • Clean, normalise and gather data from Excel, SPSS, .csv files
  • Gain an introduction to Business Intelligence and its tools
  • Combine ggplot2 and the tidyverse to calculate meaningful summaries
  • Produce Data visualisations from your data
  • Design effective data visualisations
  • Gain an introduction to Web scraping with HTML and CSS 
  • Gain an Introduction to Web scraping: programmatically extract links, images from websites
  • 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 all sorts of different data formats and topics, so you will have the skills necessary to start working with most types of data in R.


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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