QCIF EVENTS

Discover how to perform image classification using a convolutional neural network (CNN) by building, training and evaluating a model with a real set of images.

This practical workshop will help participants to apply logistic regression techniques in R to generate bionomial outputs from continuous data.

This workshop will provide a hands-on introduction to the widely-used SPSS statistical analysis package. Learn how to import, manage and transform datasets, and how to summarise and present data. The workshop will also include a basic introduction to statistical inference testing using SPSS.

A guide to basic hypothesis testing. Learn about correlation, categorical and continuous data, and comparisons between groups.

This workshop provides a guided introduction to the Galaxy Australia platform, including how to navigate the interface, manage data, run tools, create workflows, and access training resources.

A hands-on, introductory Python course. Learn basic programming concepts and how to automate analysis for improved reproducibility and productivity.

Discover unsupervised machine learning methods, including k-means, hierarchical, and density-based clustering, along with dimensionality reduction techniques.

A novice programmers guide to the R software environment, a powerful, popular and free statistical and graphical programming language.

This workshop introduces next generation sequencing (NGS) technologies and the fundamental bioinformatics analysis involved in modern sequencing analysis.

A guide to basic hypothesis testing. Learn about correlation, categorical and continuous data, and comparisons between groups.

A workshop on understanding statistical relationships using regression in R, covering key methods, result interpretation, and hands-on analysis practice.

Strengthen your mathematical intuition by revisiting core concepts through simple, real‑world examples.

This workshop introduces the foundations of reproducible research and shows participants how to standardise the way they approach data.

Use Large Language Models (LLMs) for reproducible workflows in literature review, data preparation, coding, analysis, and research writing.

A novice programmers guide to the R software environment, a powerful, popular and free statistical and graphical programming language.

Develop practical R skills for analysing and visualising genomic data.

Learn how you can record and trace every change made to a document, be it software code or a thesis.

A guide to basic hypothesis testing. Learn about correlation, categorical and continuous data, and comparisons between groups.