Learn spatial multiplexed proteomics data analysis with CODEX, CycIF, and MACSIMA. Master image processing, segmentation, phenotyping, and spatial analysis in R and Python.

Bayesian Statistical Modelling with Stan and brms is an advanced R course for researchers covering Bayesian model building, diagnostics, and interpretation using Stan and brms.

Interactive Data Applications with Shiny is a practical R Shiny course for researchers focused on building, customising, and deploying interactive web applications from data analyses.

Learn deep learning in R using the torch ecosystem. Build MLPs, CNNs and transformer models through hands-on coding and gain practical skills for real research workflows.

Learn to analyse ecological field data with detection error using R. Work with point counts, ARU data, N-mixture models, distance sampling and time-removal methods.

Machine Learning for Ecological Time Series is an applied R course teaching ecologists how to analyse, model, and predict ecological time series data.

Learn Bayesian modelling with R-INLA in R. Practical online training in hierarchical models and spatial Bayesian workflows.

Learn spatial multiplexed proteomics data analysis in R and Python. Practical online training in image processing and spatial analysis workflows.

Learn avian point count data analysis in R with detection error. Practical training in abundance estimation & occupancy modelling workflows.

Learn bioacoustics data analysis in R. Practical online training in spectrograms, annotations, and acoustic workflows.

Learn spatial & spatio-temporal modelling with R-INLA in R. Practical online training in Bayesian spatial analysis and prediction workflows.