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
Live and recorded access
Beginner - Advanced
Discuss your own data
£450Registration Fee
View DetailsSpatial Data Visualisation and Mapping using TMAP (COURSE FULL)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomVisualise spatial data in R using the tmap package. Learn to create static and interactive maps, customise layouts, and publish high-quality visualisations.
£480Registration Fee
View DetailsVisualizing Spatial Ecological Data (COURSE FULL)
Delivered remotely (Portugal) , PortugalLearn to visualise spatial ecological data in R. Explore remote sensing, species distributions, temporal patterns, and colour-safe scientific graphics.
£450Registration Fee
View DetailsIntroduction to Spatial Data Analysis (COURSE FULL)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomLearn spatial data analysis in R with this 5-day live online course. Covers vector and raster data, CRS, spatial joins, autocorrelation, interpolation, variograms, spatial regression, and reproducible workflows.
£300Registration Fee
View DetailsAnalysis of Avian Point-Count Data in the Presence of Detection Error
Delivered remotely (United Kingdom) Western European Time, United KingdomAnalyse bird point-count data in R. Learn N-mixture, time-removal, and distance sampling models.
£350Registration Fee
View DetailsSingle cell RNA-Seq analysis
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomLearn single cell RNA-Seq analysis with Seurat, 10x Genomics, and advanced QC methods. Gain cell type-specific insights in this live online course.
£150Registration Fee
View DetailsZero-Inflated Models (COURSE FULL)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomA one-day live online course on zero-inflated models in R. Learn to model count data with excess zeros using ZIP, ZINB, and hurdle approaches, plus model diagnostics and interpretation.





