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
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PR Stats instructors are leading experts in their field
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PR Stats offers live online courses and recorded courses
Beginner - Advanced
PR Stats offers courses for the complete beginner upto more advanced courses
Discuss your own data
PR Stats encourages you to bring and discuss your own data
Events
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Duration: 5 Days, 7 hours per day
Next Date: April 13-17, 2026
Format: Recorded with a live Q & A- Duration: 2 Days, 6 hours per day
- Next Date: April 14-15, 2026
- Format: Live Online Format
- Duration: 4 Days, 4 hours per day
- Next Date: April 20-23, 2026
- Format: Live Online Format
- Duration: 5 Days, 7 hours per day
- Next Date: April 20-24, 2026
- Format: Live Online Format
- Duration: 2 Days, 6 hours per day
- Next Date: April 21-22, 2026
- Format: Live Online Format
- Duration: 2 Days, 5 hours a Day
- Next Date: April 23-24, 2026
- Format: Live Online Format
Machine Learning for Ecological Time Series (METR01)
Machine Learning for Ecological Time Series (METR01)
Machine Learning for Ecological Time Series is an applied R course teaching ecologists how to analyse, model, and predict ecological time series data.
£450Registration Fee
View DetailsMachine Learning for Ecological Time Series (METR01)
Delivered remotely (United Kingdom) Western European Time, United KingdomMachine Learning for Ecological Time Series is an applied R course teaching ecologists how to analyse, model, and predict ecological time series data.
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.
£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 (AEDD01)
Analysing Ecological Data with Detection Error (AEDD01)
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.
£350Registration Fee
View DetailsAnalysing Ecological Data with Detection Error (AEDD01)
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.
£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.
£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.
Standard modelling procedure for Species Distribution and Ecological Niche Modelling (SDMS01)
Standard modelling procedure for Species Distribution and Ecological Niche Modelling (SDMS01)
Species Distribution and Ecological Niche Modelling is an applied R course teaching standard workflows for building, evaluating, and interpreting SDMs.
£275Registration Fee
View DetailsStandard modelling procedure for Species Distribution and Ecological Niche Modelling (SDMS01)
Delivered remotely (Portugal) , PortugalSpecies Distribution and Ecological Niche Modelling is an applied R course teaching standard workflows for building, evaluating, and interpreting SDMs.
Testimonials
PR Stats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PR Stats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Testimonials
PR Stats provided excellent training in stable isotope analysis through the SIMMPR course, which was incredibly valuable for my research. I was fortunate to attend the course through a generous fee waiver, which directly supported my work and enabled me to develop skills that contributed to my recent publication on reservoir food webs in Sri Lanka. I’m very grateful for the opportunity and support, and would highly recommend their courses to others working in ecological research.
Subodha Silva
Aquatic Ecology Researcher
Courses attended
SIMMPR
Testimonials
PR Stats has become an invaluable part of developing my skills in advanced statistical and spatial analysis. Through training in areas such as Bayesian statistics and Species Distribution Modelling, I’ve gained both practical expertise and exposure to leading experts in the field. The impact on my research has been significant with at least four of my published papers have been directly influenced by PR Stats courses. My most recent work benefitted from modelling advice on sample design and model accuracy evaluation and can be seen here.
Carlos P.E. Bedson
Quantitative Spatial Ecology, Ecology and Environment Research Centre, Manchester Metropolitan University, United Kingdom
Courses attended
ADVR08, ENMR03, BMIN02, ISBD01, BADA01, SDMB06