Centre for Continuing Education

Introduction to R Programming Course

Data Analysis and Analytics. Uncover insights and transform your organisation.

The ability to extract useful insights from large amounts of data is rapidly becoming one of the most highly valued skills in modern information workers. This growing demand is reflected in the increasing ubiquity of R in business, government and academia.

Learning R will turn you into a data surgeon, able to examine, filter, transform and visualise datasets in ways simply not possible with spreadsheets or relational databases. With the proliferation of user-friendly software environments such as RStudio, and increasing support for R from companies such as Microsoft and Oracle, it’s easier than ever to get started. This course will give you a solid foundation in R and equip you to deploy it for your own analytics needs.

Aims

This course aims to provide you with:

  • a working familiarity with the R language
  • the ability to perform basic data transformation, analysis and visualisation with R
  • a framework for applying R to their own domain-specific problems
  • an introduction to resources for continuing to develop their R skill set.

Outcomes

By the end of this course, you should be able to:

  • use RStudio to write and run R code
  • write syntactically correct R expressions that involve variables, variable assignment, operators and functions
  • identify basic R data types (character, double, integer and logical)
  • identify basic R data structures relevant to modern data analysis (atomic vectors and data frames)
  • find, install and use R packages
  • import data into R
  • apply the basic verbs of data transformation (filtering, selecting, mutating, renaming and arranging)
  • create statistical graphics with ggplot2
  • find and read documentation for R packages and functions.

Content

This course covers the following topics:

  • introduction to R and RStudio
  • performing arithmetic and variable assignment
  • understanding, creating and using vectors
  • understanding and performing vectorised operations
  • understanding and identifying the different types of vector
  • using functions
  • finding and reading function documentation
  • understanding and identifying common data structures
  • finding, installing and loading R packages
  • importing data from a file into R
  • transforming and summarising datasets
  • drawing statistical graphics.

Intended Audience

This course is suitable for:

  • business and IT professionals looking to improve their data analysis and automation skills, or address a particular business need
  • government and other administrative professionals who work with big data, and in particular those who frequently need to present reports and data visualisations, an area in which R is particularly strong.

Prerequisites

No previous programming experience is required. However It is assumed you have computer and data literacy knowledge to the level of performing basic data analysis tasks in Microsoft Excel.

Delivery Style

Delivered as presenter-taught computer-based training in a computer lab. It will involve a mixture of didactic and interactive activities in a variety of learning modes. You will spend most of the course time interacting with R on your individual workstation, asking questions and discussing issues as they arise. Between and during these interactive exercises, new material will be delivered verbally by the instructor, with demonstrations on a screen projector showing a live R session. Key concepts will also be developed on the whiteboard with tables and diagrams.

Materials

You will be provided with a hard-copy workbook including a mixture of explanations and demonstration code which you can refer to at their own pace.

Please bring a USB flash drive to class if you would like to make a copy of your work or any relevant class materials. Alternatively, you can save these to a cloud storage space or email them to your personal email address.

Recommended Reading

Teetor, P 2011, R Cookbook, O’Reilly, Sebastapol.

Wickham, H 2015, Advanced R, CRC Press, Boca Raton.

Wickham, H 2016, ggplot2, 2nd ed., Springer.

Wickham, H & Grolemund, G 2016, R for Data Science, O’Reilly, Sebastopol.

Features

  • $50 repeat class - Conditions apply
  • Expert trainer
  • Dedicated computer for every student
  • Small class size
  • Student notes – yours to keep
  • Statement of completion

Introduction to R Programming Course

<p>{block name:“Course Tagline - Data Analysis and Analytics”}</p><p>The ability to extract useful insights from large amounts of data is rapidly becoming one of the most highly valued skills in

...
Introduction to R Programming Course

<p>{block name:“Course Tagline - Data Analysis and Analytics”}</p><p>The ability to extract useful insights from large amounts of data is rapidly becoming one of the most highly valued skills in

...
Introduction to R Programming Course

<p>{block name:“Course Tagline - Data Analysis and Analytics”}</p><p>The ability to extract useful insights from large amounts of data is rapidly becoming one of the most highly valued skills in

...
Introduction to R Programming Course

<p>{block name:“Course Tagline - Data Analysis and Analytics”}</p><p>The ability to extract useful insights from large amounts of data is rapidly becoming one of the most highly valued skills in

...
Introduction to R Programming Course

<p>{block name:“Course Tagline - Data Analysis and Analytics”}</p><p>The ability to extract useful insights from large amounts of data is rapidly becoming one of the most highly valued skills in

...