R Programming Course: Introduction

Start your R programming journey with this beginner’s course. Learn the essentials of data import, manipulation, and visualisation with R and RStudio. Perfect for anyone looking to dive into data analysis with no prior experience.
Duration
1 day, 8 hours total
Next date
4 December 2026
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Next class mode
Face-to-face (CCE Building, Sydney)
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Cost
From $550.00

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Course summary

Welcome to the fascinating and exciting world of R programming. R is an elegant programming language specifically designed for data science, analytics, and statistics. This ‘R for Beginners’ course takes you through the fundamental skills and techniques required to use R. By the time you leave this focused R tutorial, you will be equipped with the required skills to embark on your own data science adventures. Even the most inexperienced participants will walk away from the course with newfound confidence using R for statistics and data analysis.

Bringing a combination of private, public, and academic professional experience, your instructor will guide you through this R tutorial, showing you step by step how to utilise R.

You’ll set up R and the excellent development environment RStudio, import external data, utilise add-in packages, process data for specific use, derive elementary summary statistics, and produce basic statistical visualisations.

We encourage you to use the CCE R Programming level self-assessment tool if you are unsure which course level to enrol in.

Aims

This course aims to provide a practical introduction to the R programming language. By the end of the day-long course, the user will be comfortable operating in the R environment, including importing external data, manipulating data for specific needs, and running summary statistics and visualisations.

Learning outcomes

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

  • download and install R and RStudio
  • navigate and optimise the R integrated development environment (IDE) RStudio
  • install and load add-in packages
  • import external data into R for data processing and statistical analysis
  • learn the main R data structures – vector and data frame
  • compute basic summary statistics
  • produce data visualisations with the ggplot package
  • solve fundamental error problems.

Content

  • The R Statistical Programming Language
  • The RStudio Integrated Development Environment (IDE)
  • Data importation methods
  • Basic R Data Types
  • Data processing and manipulation techniques
  • External add-in packages for R
  • Summary statistic functions
  • Data visualisations using ggplot
  • Error types

Who this course is for

  • Business professionals
  • Managers
  • IT knowledge workers
  • Lifelong learners looking to use and understand the basics of R

Prerequisites

This course is designed with the beginner in mind. While some participants may have experience in other computer programming languages, no prior programming skills are required.

Delivery style

This course is taught through a series of concepts, examples, problem exercises, and in-class knowledge challenges. The material is presented so that participants of varying backgrounds, skills and abilities can all move together in a brisk, but comfortable learning pace. Utilising principles of productivity, efficiency, and time management, the course material and timeline is structured to optimise learning and value add.

Delivery modes

  • Face-to-face, presenter-taught training using your own device
  • Online training via the platform Zoom

Materials

A link to access and download the following online course materials (using Dropbox) is provided:

  • PowerPoint notes with examples
  • all code and script files used throughout the course
  • ancillary hand-outs and learning aids.

What you need to do before the course

To participate in this course, you will need R and RStudio installed on your device. They can be downloaded free of charge from:

Face-to-face classes

Please bring your own laptop with all required software pre-installed.

Online classes

For the best experience, we recommend using a computer with a large monitor or dual screens/devices. Small laptop screens can make it difficult to follow the facilitator’s display while working in the software.

Course Brochure

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Meet the facilitators

John Le Mesurier

John brings a wealth of business, management, IT, consultancy and training experience to many of the professional development courses on offer at CCE. This experience has included senior corporate and general management roles in American, British and Chinese multinationals, as well as consultancies for several leading UK and Irish management firms. His consulting projects have covered advanced practice studies in leadership, sales & customer service processes, strategic sourcing, human resource models and organisational issues. These projects have been undertaken in North & South America, Europe and China. His international client list includes Procter & Gamble, Red Bull, Johnson & Johnson, SC Johnson, Eli Lilly, Roche, Mitsubishi, Vodafone/ Hutchison Telecoms, Danone, Heineken, BOC/ Linde, Boehringer Ingelheim, British Government and Qantas. John also works for an Australian consulting firm, Newfocus, conducting projects in the government and Not-For-Profit sectors. John has been involved in projects at PwC and Macquarie University.

John is currently undertaking a M. Phil/ PhD and holds a Master of Business Administration (with Distinction), Bachelor of Arts (with Distinction), majors in Psychology and Statistics, sub-majors in Accounting and Economics; Diplomas in Management, Change Management, Risk Management, Project Management; Digital Badge in Advanced Analytics, Graduate Certificate in Learning & Teaching, and Certificate IVs in Competitive Manufacturing (Lean) and Training and Assessment. John has been awarded the highest qualification by The Australian Research Society, namely Qualified Professional Researcher. John is an accredited Sydney Lifeline counsellor, where he also trained counsellors for more than 20 years.

John has lectured in Bachelor of Business at Torrens University, Master of Business Analytics at Kaplan Business School and Master of Community Development offered through Southern Cross University (SCBIT Sydney campus). John has been an Executive Coach at UNSW, where he has also been a guest lecturer in marketing and change management. He has taught 1st year statistics at UTS (Insearch) and Macquarie University (Navitas) and delivered IT training in corporate settings for 30 years.

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Andrew Taylor

Andrew has delivered workshops on data strategy, program evaluation and AI applications in social science. His expertise includes machine learning, multimodal AI pipelines and advanced statistical analysis. He has previously taught on topics including restorative justice program evaluation and data-driven decision making.

Andrew worked as a Senior Research Associate at the Vera Institute of Justice, where he led AI-driven data solutions and ETL pipeline development across cloud platforms. He has managed research teams and analytics projects for John Jay College of Criminal Justice and government agencies, with a focus on equity, diversion programs and public health.

Andrew holds a Master of Public Administration from the University of Washington and is a Pi Alpha Alpha Honours inductee. He has completed advanced training in AI and machine learning, including LangChain systems, LLMOps, and prompt engineering, alongside certifications in Principles of Machine Learning and AI strategies from UC Berkeley and Deeplearning.ai.

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Tony Arnold

Tony spent the first 12 years of his professional career developing software algorithms for companies including Canon, the CSIRO and Fairlight before transitioning into the transport sector where he has worked on a variety of issues such as freight optimisation and network design. Tony's key areas of expertise are geospatial analysis, software development (C++, Python, Django, R, Javascript), discrete choice modelling and mixed-methods research. He teaches several subjects at the University of Sydney and the Centre for Continuing Education including Python, R and GIS analysis.

Tony leads the Data & Analytics work on walking and cycling at Transport for NSW, and completed a PhD exploring the impacts of automated vehicles on walking and cycling in contrasting environmental contexts. He uses a diverse set of technical skills to tackle challenging problems, and is passionate about encouraging walking and cycling as a means to improve the life of people and the cities they inhabit.

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