In person Hobart Australia 11th and 12th November 2025
Course page and further details
The R program is a powerful tool for data analysis, but has a steep learning curve. Join us for a 2-day workshop that will accelerate your R skills. Our modern approach to teaching leverages AI to help you create analyses with natural language, and code with fewer errors, but higher accuracy.
Presenter: A/Prof Chris J Brown c.j.brown@utas.edu.au Guest presenter: Professor Anthony Richardson, The University of Queensland and CSIRO Environment
Cost per day: $200 students, $300 professionals. Waiver available for indigenous scholars. Register for 1 or 2 days.
Suitable for R or Python users**. We’ll show you how to use large language models (like chatGPT) directly in your R or Python coding environment. You can accelerate your coding and get personalised help on your research. But there are risks, AI makes mistakes. We’ve developed guidelines to help you get the most out of AI for coding. We’ll also discuss the ethical implications of using AI to assist with research and whether ‘vibe coding’ is appropriate for scientists. This workshop is suitable for people with limited coding experience (e.g. can read data into Rstudio and make plots) as well as experts who want to know more about AI assistants.
GLMs are a powerful tool for statistical analysis and prediction. We’ll teach the basics of the linear model and how it can be extended to all sorts of data in the generalized linear model. We’ll cover model verification, estimating effect size and significance and making predictions. The beauty of GLMs is that you only need some basic principles and you are ready to tackle many types of data, not like the old days when you had to know a different test for each new type of data.
**Note these workshops are not suitable for coding beginners. If you’ve never used R or Python before we suggest you take an introductory workshop. IMAS runs one, feel free to contact us for more info on that. As a rule of thumb, if you have Rstudio, know how to read data into R and make some plots you are ready for these workshops.
Designed by Chris Brown. Source on Github