Centre for Continuing Education

Advanced R Programming Course

Data analysis and analytics. Uncover insights and transform your organisation.

COVID-19 update: arrangement of our courses

We are now delivering courses online and in-person. Please check the delivery format of each class before enrolling.

Please note that course materials (excluding prescribed texts) are shared electronically within 48 hours of course commencement. Printing is not available.

Looking to take your data science skills into the stratosphere? Welcome to Advanced R Programming.

Writing elegant R code for data analysis is a critical skill for any modern data scientist, analyst, or programmer. This elegant code can handle advanced data structures like spatial data and regular expressions, and can maximise automation through the functional programming paradigm in R’s apply family of functions.

The advanced R user can also do much more than write code and perform analysis. You can develop custom packages and functions that save time. You can share these time saving techniques with others. You can communicate your findings in clean and tidy ways.

In this course, you will learn how to work with advanced data structures and communicate outside of the R environment. This includes package development, RMarkdown, and database connections. Further, students will be taught how to host packages and other relevant information on Github, a software development platform. Finally, students will learn how to use the Python language within the R environment.

To take this course, we recommend having skills equivalent to the learning outcomes for CCE’s Introduction to R Programming and Intermediate R Programming courses. These courses are not a prerequisite but will provide the foundation skills needed for this course.


This course aims to teach advanced R topics like package development, spatial data, and RMarkdown, package development, and GitHub. These aims are taught through the development of an R package, from the ground up.


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

  • develop your own R package
  • operate and host your data to github
  • confidently use advanced formatting types
  • share your code and analysis in tidy R markdown documents
  • create interactive maps using spatial data
  • automate complex functions
  • connect to databases in R Studio.


  • Regular expressions (regex)
  • Spatial data (packages sf, tmap, leaflet)
  • Automation through Functionals (packages apply and purr)
  • Developing packages in R
  • Creating R markdown documents
  • Running Python within R
  • SQL in R
  • Connecting to databases within R / R Studio

Intended audience

Regular users of R, Python, SQL, SAS, SPSS, or other data science programming languages will find the course most beneficial. Managers and leaders will also find Advanced R advantageous for gaining organisation efficiencies.


As this is an advanced class some technical programming experience is required. Students who have completed CCE’s Introduction and Intermediate R Programming short courses will be well prepared for Advanced R material.

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 at a brisk, but comfortable learning pace.

Delivery options:

  • presenter-taught training in a computer lab on University premises
  • online training via the platform Zoom.

Face-to-face classes

These classes run in a computer lab with R and RStudio pre-installed on all machines. You do not need to bring your own device. Certain R installation procedures are covered, for participants needing guidance after the course completes.

USB devices are recommended for those who wish to save their work (code scripts, notes, etc) for later viewing.

Online classes

If you are attending an online class, you will need your own device with both R and RStudio installed. Both pieces of software are free to download as follows:

  • R here
  • RStudio here (the free version will suffice)


You will be provided with a link to access and download the following course materials:

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

Recommended reading

Burns, P 2012, R Inferno, Lulu.com.

DeVries, A 2015, R for Dummies, 2nd edition, For Dummies.

Gilespie, C and Lovelace, R, Efficient R Programming, O’Reilly Media.

Jones, O, Maillardet, R, and Robinson, A 2014, Introduction to Scientific Programming and Simulation Using R, 2nd edition, Chapman and Hall/CRC.

Wickem, H 2019, Advanced R, 2nd edition, Chapman and Hall/CRC.

Wickem, H 2017, R for Data Science, O’Reilly Media.

Wickem, H 2015, R Packages, O’Reily Media.


  • $50 repeat class - Conditions apply
  • Expert trainer
  • Small class size
  • CCE Statement of Completion

Apply for the IT repeat discount.

Advanced R Programming Course

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Advanced R Programming Course

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<p>{block name:"Block - COVID 19 updates"}</p>

<p>Looking to take your data science skills into the stratosphere? Welcome to Advanced

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