Decision Trees and Ensemble Methods in Machine Learning (Oct 2025) - NCI
Wed, 01 Oct
|Live, interactive workshop via Zoom.
Learn the theory behind decision trees, including how they split data, handle overfitting, and work with both classification and regression problems.


Time & Location
01 Oct 2025, 9:30 am – 1:30 pm AEST
Live, interactive workshop via Zoom.
About the event
This workshop is being run as part of a collaboration between QCIF and National Computational Infrastructure (NCI).
Decision trees are a fundamental supervised learning method that form the backbone of many powerful ensemble models. In this interactive online workshop, participants will learn the theory behind decision trees, including how they split data, handle overfitting, and work with both classification and regression problems. We will also explore advanced tree-based methods, including Random Forests, Gradient Boosting, and XGBoost. Through coding exercises in Python (Scikit-Learn, XGBoost), attendees will build and fine-tune decision tree models on real-world datasets. By the end of the session, participants will have a solid understanding of decision trees, their strengths and weaknesses, and when to apply ensemble learning techniques. No prior machine learning experience is required, but basic Python and statistics knowledge are recommended.
FAQs
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Researcher
Researchers from Australian universities, Australian research organisations and those using National Computational Infrastructure (NCI) are eligible for this event. You must use your institutional email address to register for this event.
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