An introduction to R; a mathematical and statistical modelling language used extensively in data analysis and Big Data.

This 3-day course is designed for anyone planning to work with larger Big Data solutions or Machine Learning, or for those studying a vendor specific path, such as Microsoft SQL Server.

By attending this course you will learn how to write programmes using R to create effective statistical outputs and to visualize data using R’s library.

Target Audience

Aimed at all who wish to learn the R programming language.

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  • No prior knowledge of R is assumed
  • Delegates should already be familiar with basic programming concepts such as variables, scope and functions
  • Experience of another scripting language such as Python or Perl would be an advantage
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Learning Outcomes

At the end of this course attendees will know:

  • Fundamentals of R programming language
  • R data types, containers, arrays, flow control and functions
  • R text manipulation
  • R visualisation packages
  • How to perform data exploration and analysis with R

At the end of this course attendees will be able to:

  • Write R programs for manipulating and analysing data
  • Plot graphs from data sets
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Course Outline

Overview of R

  • An introduction to the R programming language
  • History and capabilities
  • Development environments
  • Assignment
  • Tips

Data: Datatypes and Arithmetic

  • An introduction to most common data types in base R
  • Simple types
  • Composite types
  • Arithmetic
  • Data manipulation


  • A more detailed look at the most common data types in base R
  • Lists, Vectors, Factors, Data Frames
  • Converting data types

Higher Dimensions

  • A more detailed look at the most common data types in base R
  • Matrices and Arrays
  • Representing 3 or more dimensions

Databases and IO

  • A more detailed look at how to read and write to permanent storage from R
  • Various File Types
  • Databases


  • A more detailed look at how to control decision making in R for later automation:
  • Selection
  • Iteration


  • An overview of how to create functions in R
  • How to call functions
  • The use of variadicity in R
  • Design principles for programmers


  • An overview of the functions available in stringr for manipulating text.
  • A brief introduction to regex.
  • Functions for pattern matching and text manipulation

Plotting and Packages

  • Plotting in base R
  • An overview of the community approved packages: Tidyverse
  • Syntax differences
  • Overview of packages for Data Import, Transforming and Cleaning
  • Overview of packages for report creation and dashboarding
  • Overview of packages for Big Data handing and AI
  • Extra: Practical use of ggplot2, ggplotly
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Why choose QA

Dates & Locations

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QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.

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When will I receive my certificate?

Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.

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