Specialist training in applied statistical methods for researchers in ecology, biology, and environmental sciences.
Courses are taught by leading academics
Live online course on time series modelling & forecasting, taught by Mark Andrews, Senior Lecturer & experienced instructor in Bayesian data analysis & statistical computing
11–15 May
https://t.co/KwBpeQB6ZA
#PhDStudents#TimeSeries#MachineLearning#DataScience#RStats
Live online course on movement ecology & the analysis of telemetry data, taught by leading ecologists working at the interface of behaviour, habitat selection, & biodiversity dynamics
11–15 May
https://t.co/NcbItCREUe
#MovementEcology#QuantitativeEcology#SpatialEcology#RStats
Live online course on Bayesian statistical modelling with Stan & brms, taught by Mark Andrews, Senior Lecturer & experienced instructor in applied Bayesian methods
5–7 May 2026
Details: https://t.co/yncySc9BzM
#PhDStudents#BayesianStatistics#Stan#RStats#DataScience
Live online course on scalable Bayesian modelling using INLA, taught by Virgilio Gómez-Rubio, author of Bayesian Inference with INLA and leading contributor to Bayesian & spatial modelling in R
4–8 May
https://t.co/BtNSRP2zzb
#BayesianStatistics#INLA#RStats#SpatialStatistics
Turn your R analyses into interactive research
Live course building interactive data applications with Shiny, taught by Mark Andrews, Senior Lecturer in Bayesian modelling & statistical computing
28–29 Apr
https://t.co/M1Bl5mHFyr
#RStats#Shiny#DataVisualization#DataScience
Live online course on stable isotope mixing models using SIBER, SIAR, & MixSIAR, taught by Andrew Parnell, Hamilton Professor of Statistics with extensive expertise in Bayesian modelling.
27–30 Apr
https://t.co/CWks3bAhr0
#StableIsotopes#BayesianStatistics#Ecology#RStats
Live online course on workflows for species distribution & ecological niche modelling, taught by Neftalí Sillero, a spatial ecologist with over 70 peer reviewed publications
23–24 Apr
https://t.co/uVHaeUDBiL
#SpeciesDistributionModelling#SpatialEcology#GIS#Biodiversity
Strengthen your ecological inference
Live course on analysing ecological data with imperfect detection, taught by Péter Solymos, developer of widely used R tools for ecological modelling
20–23 Apr
https://t.co/SEIQwz3fAQ
#Ecology#RStats#EcologicalStatistics#Biodiversity
Live online course on single cell RNA-seq analysis, taught by Frances Turner, a bioinformatician at the University of Edinburgh with experience supporting real research projects
16–19 March
https://t.co/4WxtgKC0ae
#PhDStudents#SingleCell#Bioinformatics#Genomics#DataScience
Live online course on advanced Python for biological research, taught by Martin Jones, founder of Python for Biologists and former Lecturer in Bioinformatics at University of Edinburgh
23–26 Mar
https://t.co/Oz7q9S5VSC
#PhDStudents#Python#Bioinformatics#ComputationalBiology
Live online course on deep learning using R, taught by Mark Andrews, Senior Lecturer in Psychology with extensive experience in Bayesian modelling, statistical computing, and machine learning
21–22 Apr
https://t.co/PnAEMIXyMI
#DeepLearning#RStats#MachineLearning#DataScience
Live online course on community ecology analysis using vegan in R, taught by Antoine Becker-Scarpitta, a community and forest ecologist with extensive experience in applied ecological modelling.
20–24 April
https://t.co/WIgn1tsKp3
#PhDStudents#Ecology#RStats#Biodiversity
Deep learning with real data
Live online course on deep learning using Python, taught by Mark Andrews, an experienced instructor in applied modelling and computational methods
14–15 Apr
https://t.co/7TUKisX4TO
#PhDStudents#DeepLearning#Python#MachineLearning#DataScience
Python for data science and statistical computing in PhD research.
Taught by Mark Andrews, Senior Lecturer in Psychology and long standing instructor in applied Bayesian data analysis.
7–8 April
https://t.co/tKrb4CXyhe
#PhDStudents#Python#DataScience#BayesianStatistics
Live online Python course for biological data exploration and visualisation, taught by Martin Jones, founder of Python for Biologists and former Lecturer in Bioinformatics at Edinburgh University
2–5 Mar
https://t.co/S4iOWpcZaj
#PhDStudents#Python#Bioinformatics#DataScience
Live online course on Bayesian modelling with R-INLA, taught by Virgilio Gómez-Rubio, author of Bayesian Inference with INLA and a leading contributor to the R Bayesian ecosystem.
23–27 Feb
Details: https://t.co/fOkZva63YY
#PhDStudents#BayesianStatistics#RStats#DataScience
Deep Learning Python course 12–13 Feb. A practical introduction to neural networks, model training, and applied deep learning workflows. Led by Dr Mark Andrews, an instructor in data science and machine learning.
https://t.co/7TUKisWx4g
#DeepLearning#Python#MachineLearning
Spatial Multiplexed Proteomics Data course 9 to 13 Feb
Intro to processing fluorescence microscopy taught by Dr Victor Perez Meza, an image analysis specialist focused on artefact correction
https://t.co/PR1EiGbNmE
#SpatialProteomics#SpatialOmics#ImageAnalysis#Bioinformatics
Our Python for Data Science and Statistical Computing course runs 9 to 10 Feb. A practical introduction to data manipulation, visualisation, and statistical workflows
Taught by Dr Mark Andrews.
https://t.co/tKrb4CXyhe
#Python#DataScience#StatisticalComputing#ResearchSkills
GLMM for Ecologists course 2-6 Feb.
An introduction to building mixed models in R. Taught by Dr Andrew MacDonald, a statistician focused on connecting ecological theory with expressive statistical models
https://t.co/Z20fsSAQAr
#GLMM#Ecology#RStats#MixedModels#DataAnalysis