Learn to Program: R

Course description

Learn about the fundamental concepts in programming using R and apply them to analyse a sample research dataset.

R is quickly gaining popularity as a programming language of choice for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio development environment and the Shiny web application framework.

But getting started with R can be challenging, particularly if you’ve never programmed before. That’s where this introductory course comes in.

We teach using RStudio, which allows program code, results, visualisations and documentation to be blended seamlessly.

Join us for a live coding workshop where we write programs that produce results, using the researcher-focused training modules from the highly regarded Software Carpentry Foundation.

25 Feb: JOIN WAITLIST VIA EVENTBRITE

Registration links for the below sessions opening soon

Learn to Program: R 
Thursday 12 March 9am-12pm Part A
Friday 13 March 9am-12pm Part B
REGISTER VIA EVENTBRITE

Learn to Program: R - half day Part A
Thursday 9 April 9am-12pm
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Learn to Program: R - half day Part B
Friday 10 April 9am-12pm
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Learn to Program: R - Full Day
Tuesday 28 April 9am-4pm
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Learning Outcomes:

• Introduction to the RStudio interface for programming
• Basic syntax and data types in R
• How to load external data into R
• Creating functions 
• Repeating actions and analysing multiple data sets 
• Making choices 
• Ways to visualise data in R

Prerequisites:
No prior experience with programming needed to attend this course. We strongly recommend watching the Start Coding without Hesitation: Programming Languages Showdown and Thinking like a computer: The Fundamentals of Programming webinars. Recordings of these webinars can be found here.

Training will be conducted via Zoom. A Zoom link will be shared with registrants a week before training date. There will be a one-hour lunch break at 12 pm, in addition to two 10–15-minute breaks.

About your Trainer:
Dr Ankit Beniwal is Intersect’s Digital Research Analyst (DRA) for Flinders University in 2026. He holds a PhD in Physics from the University of Adelaide and has held multiple post-doctoral positions in Europe. His technical expertise includes Python and R, complemented further by proficiency in qualitative research tools like Qualtrics, NVivo, REDCap, etc.

Type of course

Workshop