Machine Learning in R 2

Machines can learn! It’s 2026 and while AI is everywhere it hasn’t taken over just yet. Here in this workshop we’re going to teach you how to use an incredibly powerful set of tools and techniques that can uncover patterns in your data. If you have collected a heap of data and aren’t sure what to do with it then we’re here for you!

This two-part workshop series is designed to take you through the whole process of machine learning, from getting your data ready, to applying, tuning, and understanding different models, to what to do with them after you’ve got everything running. This will help you understand what you can get out of your hard-earned data, impress your colleagues, and lead to a Nature publication! (Nature publication not guaranteed).

This course is aimed at someone who can read data into R, make plots using ggplot2, and can string together functions using the %>% pipe operator.

This is the second of two workshops being run over two days building on previous concepts. To get the most out of it, please sign up to both days.

Lead Trainer: Dr Angus Fisk, Data Science Trainer, Sydney Informatics Hub (SIH)

Format: In-person only, full day workshop. Level 5 Auditorium, Moore College (1 King Street, Newtown)

Learning outcomes: By the end of the workshop you should be able to:

• implement supervised machine learning algorithms for applying for classification tasks;
• perform model evaluation and validation to assess the performance of your classification model;
• explore dimensionality reduction methods such as principal component analysis (PCA);
• understand the concept of feature selection and feature extraction to reduce the complexity of datasets;
• Practice implementing dimensionality reduction techniques to address issues associated with high-dimensional data;
• use the tidymodels suite of packages.

Who the workshop is for: This workshop is for Academic and Professional Staff, research students, and affiliates of The University of Sydney (with a valid UniKey).

Please use your University of Sydney email address to register i.e. @sydney.edu.au, @uni.sydney.edu.au, etc

This workshop requires you to have some knowledge of R. You should be familiar with:

• some of the core packages of the tidyverse, including dplyr and its functions for data manipulation;
• the magrittr pipe operator (%>%) or base pipe |>;
• the ggplot2 package for data visualization.

You will need a laptop with R and RStudio installed.

If you have any questions, please contact the training team at sih.training@sydney.edu.au.

This workshop is part of a series of data science training events. If you'd like to hear when registrations open for other events, please subscribe to Sydney Informatics Hub newsletters.