Online courses in Applied Statistics, Genomics, Bioinformatics, Ecology and Social Sciences
Learn from leading experts, over 350 courses delivered since 2014 across 60 diverse subjects
Understand the data behind the science
Expert-Led Training
PR Stats instructors are leading experts in their field
Live and recorded access
PR Stats offers live online courses and recorded courses
Beginner - Advanced
PR Stats offers courses for the complete beginner upto more advanced courses
Discuss your own data
PR Stats encourages you to bring and discuss your own data

£450Registration Fee
View DetailsIntroduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP02)
Delivered remotely (United Kingdom) Western European Time, United KingdomLearn spatial multiplexed proteomics data analysis with CODEX, CycIF, and MACSIMA. Master image processing, segmentation, phenotyping, and spatial analysis in R and Python.

£480Registration Fee
View DetailsIntroduction to Python for Bioinformatics (IPYB02)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomBeginner Python course for biologists. Learn file handling, loops, and bioinformatics-focused coding in Python.

£350Registration Fee
View DetailsReproducible Spatial Ecology: Visualization, Reporting, and AI-Assisted Workflows with R (RSPE01)
Delivered remotely (Portugal) , PortugalLearn spatial ecological data visualisation in R. Master mapping, remote sensing, publication-quality graphics, accessible colour scales, and reproducible workflows.

£480Registration Fee
View DetailsAdvanced Python for Bioinformatics (APYB02)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomTake your Python skills further. Learn OOP, testing, and optimisation for complex bioinformatics tasks.

£350Registration Fee
View DetailsRNA-Seq Analysis (RNAA02)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomRNA-Seq analysis training – live online course covering experiment design, data QC, alignment, gene expression, DESeq2 differential expression, PCA, visualisation, and functional analysis.







