Overview
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.
Prerequisites
- 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
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
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
Containers
- 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
Flow
- A more detailed look at how to control decision making in R for later automation:
- Selection
- Iteration
Functions
- An overview of how to create functions in R
- How to call functions
- The use of variadicity in R
- Design principles for programmers
Text
- 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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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.