AI and Data Analysis Workshop with A/Prof Chris Brown

AI and Data Analysis Workshop with AMSA WA

Practical training for researchers working with data, modelling and scientific analysis

AMSA WA invites researchers, academics, postgraduate students and marine/ecological science professionals to join A/Prof Chris J Brown (Institute for Marine and Antarctic Studies, University of Tasmania, Australia) for two practical days exploring modern approaches to scientific data analysis.

The workshop consists of two complementary but independent days, allowing you to attend one or both depending on your interests and experience.

Day 1 - Quality data analysis with AI coding assistants

"Suitable for R or Python users. I’ll show you how to use large language models (like chatGPT and Claude) to improve the quality and efficiency of scientific coding and data analysis. In this workshop we will look at how to get the most out of coding assistants and AI agents, including how to modify your coding workflows to work well with AI agents, agentic workflows, and how to write more effective instructions and prompts. We will look at the range of software options including different model providers and integration of LLMs into your code editor. We will also see how you can run LLMs directly by code, to automate tasks like literature synthesis. We will also discuss mitigating the risks of undetected errors in AI code and data privacy issues. This workshop is suitable for people with some coding experience (e.g. can read data into Rstudio and make plots) as well as experts who want to know more about AI assistants and agents. " - A/Prof Chris Brown

Day 1 is suitable for anyone from basic programming experience with R through to experts. We will focus on showing you what tools are available and how best to use them for your experience level.

Day 2 - Bayesian modelling for ecological data

The second day focuses on Bayesian approaches to statistical modelling, providing researchers with practical tools for developing, interpreting and applying Bayesian models to their own data. This session is an opportunity to build your understanding of Bayesian modelling and explore how these approaches can be incorporated into your own research.

Day 2 will begin with an introduction to Bayesian statistical theory, then its application in the R program. It will help to have some basic R skills so that you can make the most of the course. However, the first half of the day will not require the R program, we will learn Bayesian theory and make use of simple web applications to fit models. In the second half of the day we will look at how to do Bayesian modelling in R.

Who should attend?
Marine and environmental researchers, academics, postgraduate students, research staff and professionals working with scientific data. The workshop is suitable for people with some existing coding or statistical experience who want to expand their analytical toolkit.

Some working knowledge of the R program (or Python if you prefer to use that on Day 1) is assumed. You should at least be able to load data in R (e.g. R Studio) and make a plot. 

About Chris 

Chris is an Associate Professor of Fisheries Science at the University of Tasmania and an Australian Research Council Future Fellow. He specialises in data analysis and modelling, skills he uses to better inform environmental decision makers. Generative AI holds great promise, and perils, for science. So over the past 2 years he’s been developing techniques and approaches for using AI to improve the quality of research. Chris is an enthusiastic educator. He’s taught numerous workshops on AI analysis tools over the past 2 years and cofounded a blog on AI in research Vita ex Machina https://vitaexmachina.substack.com/

To contact A/Prof Chris J Brown c.j.brown@utas.edu.au

Guest lecture spot with A/Prof Chris Brown

A/ Prof Chris Brown will also be doing a lecture on the evening of Monday 26th October titled "Climate change and fishing pressure reduce predictability of marine biodiversity change".

Location: Indian Ocean Marine Research Centre Auditorium, UWA

Time: 5:30pm