Live Online Courses

Learn to visualise spatial ecological data in R. Explore remote sensing, species distributions, temporal patterns, and colour-safe scientific graphics.

Learn 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.

Learn single cell RNA-Seq analysis with Seurat, 10x Genomics, and advanced QC methods. Gain cell type-specific insights in this live online course.

A 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.

Learn decision trees, random forests, and boosted models in R. This one-day live online course covers CART, bagging, boosting, and model interpretation for applied data analysis.

Learn advanced SDM and ENM techniques in R. Includes Maxent tuning, MESS and null models, and building mechanistic models and virtual species.

Learn applied Bayesian modelling in R with brms for ecological data. Build, fit, and interpret hierarchical and GLMMs in this hands-on workshop.

Data Visualisation in R using ggplot2 – online course covering scatterplots, histograms, bar plots, boxplots, density plots, line plots, heatmaps, maps, and advanced customisation for publication-quality graphics.

Model hierarchical ecological data using GLMMs in R. Covers lme4, brms, and Bayesian methods for ecologists.

This two-day hands-on course teaches researchers how to select, compare, and evaluate statistical models in R using cross-validation, information criteria (AIC, AICc, BIC), and regularization methods. Participants will learn model averaging, mixed effects model selection, and best practices for transparent, theory-driven analysis.

Learn Generalised Linear Models (GLMs) in R with this live online course. Covers Poisson regression, logistic regression, multinomial, ordinal, Gamma models, mixed-effects, and Bayesian GLMs. Ideal for researchers, postgraduate students, and data analysts.

RNA-Seq analysis training – live online course covering experiment design, data QC, alignment, gene expression, DESeq2 differential expression, PCA, visualisation, and functional analysis.

Learn Snakemake to automate data workflows. Build reproducible, scalable pipelines for research with hands-on training in this 4-day live online course.

Explore and visualise biological data in Python using pandas and seaborn. Ideal for applied researchers.