QCIF EVENTS

Develop practical R skills for analysing and visualising genomic data.

Effectively store and export data to and from Microsoft Excel and explore data using its functions and capabilities.

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.

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.

Discover how regression turns data into meaningful predictions.

Join us for this special event to discover how QCIF Digital Research partners with health researchers and practitioners to accelerate impactful, data-driven research.

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

Learn how to leverage human psychology to communicate your findings, compose a strong data driven narrative, and much more.

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

This workshop introduces the core skills for analysing RNA‑seq data with R, from preprocessing to differential expression and gene set analysis.

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

Classification is a core supervised learning technique used to categorise data into discrete classes.

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

Learn the essential command‑line skills that make it easier to work efficiently and access powerful computing tools.

Discover software containers - a reproducible, standardised, transferrable way to run research software consistently across different hardware.