This workshop is being run as part of a collaboration between QCIF and National Computational Infrastructure (NCI).

Unsupervised learning techniques, particularly clustering, are essential for discovering hidden patterns and structures in data. In this interactive workshop, participants will explore key unsupervised learning methods, including k-means clustering, hierarchical clustering, and density-based clustering. The session will also introduce dimensionality reduction techniques, including principal component analysis (PCA) and t-distributed stochastic neighbour embedding ( t-SNE ) for visualisation and feature extraction. Through interactive coding exercises in Python (Scikit-Learn, NumPy, Pandas, Matplotlib, Seaborn), attendees will apply clustering techniques to real-world datasets and learn how to evaluate the quality of clustering results. The workshop will also discuss applications of clustering in different domains, from customer segmentation to anomaly detection. By the end of the session, participants will have the practical skills to apply clustering and unsupervised learning methods effectively in data analysis. No prior machine learning experience is required, but basic Python and statistics knowledge are recommended.

This workshop will take place from 9:30-1:30pm, Tuesday 29th July 2025. Please only register if you can fully commit to attending.

FAQs

What should I bring into the event?

This is an online workshop, so you will need to provide your own computer, and have access to a reliable internet connection sufficient for video conferencing. A second monitor is highly recommended. This workshop will run on NCI Australian Research Environment (ARE) platform. Instructions to access the NCI ARE platform will be provided prior to the workshop.

Chromebooks and tablets are not suitable for this workshop; you will need a full-function computer.

What prior experience do I need?

Basic Python knowledge (Completing either ‘Introduction to Python (NCI)’ workshop or the Carpentries ‘Introduction to Programming: Plotting and Programming in Python’).
Fundamental statistics knowledge.

Who should attend?

This workshop is open to all researchers from Australian Universities and Australian researchers currently using or interested in using the National Computational Infrastructure (NCI).

This workshop is ideal for researchers, data analysts, and professionals looking to apply clustering techniques to explore and structure large datasets without labelled outputs.

How can I contact the organiser with any questions?

You can email training@qcif.edu.au

What's the cancellation policy?

Cancellations are accepted up to 48h before the start of the workshop. If you do not join on the day without having cancelled beforehand, you may be blocked from attending any future QCIF training workshops.