Live Courses
Introduction to Python for Ecologists and Evolutionary Biologists
Introduction to Python for Ecologists and Evolutionary Biologists
Beginner Python course for biologists. Learn file handling, loops, and bioinformatics-focused coding in Python.
Duration: 4 Days, 7 hours per day- Next Date: January 26-29, 2026
- Format: Live Online Format
£480Registration Fee
View DetailsIntroduction to Python for Ecologists and Evolutionary Biologists
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomBeginner Python course for biologists. Learn file handling, loops, and bioinformatics-focused coding in Python.
RNA-Seq Analysis
RNA-Seq Analysis
RNA-Seq analysis training – live online course covering experiment design, data QC, alignment, gene expression, DESeq2 differential expression, PCA, visualisation, and functional analysis.
- Duration: 4 Days, 3.5 hours per day
- Next Date: January 26-29, 2026
- Format: Live Online Format
£350Registration Fee
View DetailsRNA-Seq Analysis
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.
Species Distribution Modelling With Bayesian Statistics (SDMB07)
Species Distribution Modelling With Bayesian Statistics (SDMB07)
Model species distributions using BART in R. Covers uncertainty, variable selection, and full Bayesian workflow.
- Duration: 3 Days, 4 hours per day
- Next Date: January 27-29, 2026
- Format: Live Online Format
£385Registration Fee
View DetailsSpecies Distribution Modelling With Bayesian Statistics (SDMB07)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomMaster Bayesian multilevel models in R with brms. Learn GLMs, priors, spatial/temporal autocorrelation, and species distribution modelling.
Introduction to Generalised Linear Mixed Models for Ecologists (MMIE02)
Introduction to Generalised Linear Mixed Models for Ecologists (MMIE02)
Learn to build and interpret linear, generalised linear, and multilevel models for ecological data using R, lme4, and rstanarm in this five day applied training course.
- Duration: 5 Days, 6 hours per day
- Next Date: February 2-6, 2026
- Format: Live Online Format
£450Registration Fee
View DetailsIntroduction to Generalised Linear Mixed Models for Ecologists (MMIE02)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomLearn to build and interpret linear, generalised linear, and multilevel models for ecological data using R, lme4, and rstanarm in this five day applied training course.
Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP01) SOLD OUT!
Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP01) SOLD OUT!
Learn spatial multiplexed proteomics data analysis with CODEX, CycIF, and MACSIMA. Master image processing, segmentation, phenotyping, and spatial analysis in R and Python.
- Duration: 5 Days, 5.5 hours per day
- Next Date: February 9-13, 2026
- Format: Live Online Format
£450Registration Fee
View DetailsIntroduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP01) SOLD OUT!
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.
Single cell RNA-Seq analysis
Single cell RNA-Seq analysis
Learn single cell RNA-Seq analysis with Seurat, 10x Genomics, and advanced QC methods. Gain cell type-specific insights in this live online course.
- Duration: 4 Days, 3.5 hours per day
- Next Date: February 23-26, 2026
- Format: Live Online Format
£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.
Bayesian Modelling Using R-INLA
Bayesian Modelling Using R-INLA
Learn Bayesian modelling with the R-INLA package. Build, fit, and interpret INLA models, define priors and latent effects, and apply INLA to real data in a five day course.
- Duration: 5 Days, 7 hours per day
- Next Date: February 23-27, 2026
- Format: Live Online Format
£500Registration Fee
View DetailsBayesian Modelling Using R-INLA
Delivered remotely (United Kingdom) Western European Time, United KingdomLearn Bayesian modelling with the R-INLA package. Build, fit, and interpret INLA models, define priors and latent effects, and apply INLA to real data in a five day course.
Python for Biological Data Exploration and Visualization
Python for Biological Data Exploration and Visualization
Explore and visualise biological data in Python using pandas and seaborn. Ideal for applied researchers.
- Duration: 4 Days, 7 hours per day
- Next Date: March 2-5, 2026
- Format: Live Online Format
£480Registration Fee
View DetailsPython for Biological Data Exploration and Visualization
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomExplore and visualise biological data in Python using pandas and seaborn. Ideal for applied researchers.
Advanced Python for Ecologists and Evolutionary Biologists
Advanced Python for Ecologists and Evolutionary Biologists
Take your Python skills further. Learn OOP, testing, and optimisation for complex bioinformatics tasks.
- Duration: 4 Days, 7 hours per day
- Next Date: March 23-26, 2026
- Format: Live Online Format
£480Registration Fee
View DetailsAdvanced Python for Ecologists and Evolutionary Biologists
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomTake your Python skills further. Learn OOP, testing, and optimisation for complex bioinformatics tasks.
Causal Inference for Ecologists (CIFE01)
Causal Inference for Ecologists (CIFE01)
Causal Inference for Ecologists is an applied R course teaching researchers how to identify and estimate causal effects in ecological and environmental data.
- Duration: 5 Days, 4.5 hours per day
- Next Date: March 23-27, 2026
- Format: Live Online Format
£400Registration Fee
View DetailsCausal Inference for Ecologists (CIFE01)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomCausal Inference for Ecologists is an applied R course teaching researchers how to identify and estimate causal effects in ecological and environmental data.
Python for Data Science and Statistical Computing (PYDS01)
Python for Data Science and Statistical Computing (PYDS01)
Learn Python for data science and statistical computing. Build skills in NumPy, Pandas and visualisation across two days of hands-on training for researchers and analysts.
- Duration: 2 Days, 6 hours per day
- Next Date: April 7-8, 2026
- Format: Live Online Format
£300Registration Fee
View DetailsPython for Data Science and Statistical Computing (PYDS01)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomLearn Python for data science and statistical computing. Build skills in NumPy, Pandas and visualisation across two days of hands-on training for researchers and analysts.
Deep Learning Using Python (DLUP01)
Deep Learning Using Python (DLUP01)
Deep learning course using Python and PyTorch. Learn neural networks, CNNs and transformers through hands-on coding and real data across two intensive training days.
- Duration: 2 Days, 6 hours per day
- Next Date: April 14-15, 2026
- Format: Live Online Format
£300Registration Fee
View DetailsDeep Learning Using Python (DLUP01)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomDeep learning course using Python and PyTorch. Learn neural networks, CNNs and transformers through hands-on coding and real data across two intensive training days.
Analysing Ecological Data with Detection Error
Analysing Ecological Data with Detection Error
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.
- Duration: 4 Days, 4 hours per day
- Next Date: April 20-23, 2026
- Format: Live Online Format
£350Registration Fee
View DetailsAnalysing Ecological Data with Detection Error
Delivered remotely (United Kingdom) Western European Time, United KingdomLearn 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.
Multivariate Analysis of Ecological Communities Using VEGAN (VGNR09)
Multivariate Analysis of Ecological Communities Using VEGAN (VGNR09)
Analyse ecological community data in R using VEGAN. Learn ordination, clustering, and multivariate statistics with real datasets.
- Duration: 5 Days, 7 hours per day
- Next Date: April 20-24, 2026
- Format: Live Online Format
£485Registration Fee
View DetailsMultivariate Analysis of Ecological Communities Using VEGAN (VGNR09)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomAnalyse ecological community data in R using VEGAN. Learn ordination, clustering, and multivariate statistics with real datasets.
Deep Learning using R (DLUR01)
Deep Learning using R (DLUR01)
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.
- Duration: 2 Days, 6 hours per day
- Next Date: April 21-22, 2026
- Format: Live Online Format
£300Registration Fee
View DetailsDeep Learning using R (DLUR01)
Delivered remotely (United Kingdom) Western European Time, United KingdomLearn 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.
Bayesian Nonlinear Models for Ecologists (BNLM01)
Bayesian Nonlinear Models for Ecologists (BNLM01)
Learn how to build, fit, and compare theory-driven nonlinear ecological models using Bayesian methods in R with brms.
- Duration: 5 Days, 4.5 hours per day
- Next Date: April 27-May 1, 2026
- Format: Live Online Format
£400Registration Fee
View DetailsBayesian Nonlinear Models for Ecologists (BNLM01)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomCausal Inference for Ecologists is an applied R course teaching researchers how to identify and estimate causal effects in ecological and environmental data.
Interactive Data Applications with Shiny (SHID01)
Interactive Data Applications with Shiny (SHID01)
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.
- Duration: 2 Days, 6 hours per day
- Next Date: April 28-29, 2026
- Format: Live Online Format
£300Registration Fee
View DetailsInteractive Data Applications with Shiny (SHID01)
Delivered remotely (United Kingdom) Western European Time, United KingdomInteractive Data Applications with Shiny is a practical R Shiny course for researchers focused on building, customising, and deploying interactive web applications from data analyses.
Bayesian Statistical Modelling with Stan and brms (BMSB01)
Bayesian Statistical Modelling with Stan and brms (BMSB01)
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.
- Duration: 3 Days, 6 hours per day
- Next Date: May 5-7, 2026
- Format: Live Online Format
£400Registration Fee
View DetailsBayesian Statistical Modelling with Stan and brms (BMSB01)
Delivered remotely (United Kingdom) Western European Time, United KingdomBayesian Statistical Modelling with Stan and brms is an advanced R course for researchers covering Bayesian model building, diagnostics, and interpretation using Stan and brms.
Movement Ecology (the Analysis of Movement Data)
Movement Ecology (the Analysis of Movement Data)
Learn to analyse animal movement data using spatial methods, home range estimation, interaction metrics and resource or step selection models through hands-on training in R.
- Duration: 5 Days, 8 hours per day
- Next Date: May 11-15, 2026
- Format: Live Online Format
£480Registration Fee
View DetailsMovement Ecology (the Analysis of Movement Data)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomLearn to analyse animal movement data using spatial methods, home range estimation, interaction metrics and resource or step selection models through hands-on training in R.
Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP02)
Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP02)
Learn spatial multiplexed proteomics data analysis with CODEX, CycIF, and MACSIMA. Master image processing, segmentation, phenotyping, and spatial analysis in R and Python.
- Duration: 5 Days, 5.5 hours per day
- Next Date: June 1-5, 2026
- Format: Live Online Format
£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.
Bioacoustics Data Analysis (BIAC06)
Bioacoustics Data Analysis (BIAC06)
Analyse animal acoustic signals in R. Learn spectrograms, annotations, and bioacoustic workflows.
- Duration: 5 Days, 4 hours per day
- Next Date: October 19-23, 2026
- Format: Live Online Format
£400Registration Fee
View DetailsBioacoustics Data Analysis (BIAC06)
Delivered remotely (United Kingdom) Western European Time, United KingdomAnalyse animal acoustic signals in R. Learn spectrograms, annotations, and bioacoustic workflows.
Network Analysis for Ecologists (NWAE02)
Network Analysis for Ecologists (NWAE02)
Use R to analyse ecological networks. Learn metrics, simulation, and visualisation with igraph.
- Duration: 2 Days, 3 hours per day
- Next Date: November 3-4, 2026
- Format: Live Online Format
£250Registration Fee
View DetailsNetwork Analysis for Ecologists (NWAE02)
Delivered remotely (United Kingdom) Western European Time Zone, United KingdomUse R to analyse ecological networks. Learn metrics, simulation, and visualisation with igraph.