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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

Understand the data behind the science

PR Stats delivers cutting-edge courses in Statistics, Genomics and Bioinformatics, designed by researchers for researchers, equipping you with the tools to tackle real-world data, publish with confidence, and push the boundaries of your field!

Expert-Led Training

PR stats instructors are leading experts in their field

Live and recorded access

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

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SPMP01

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.

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    Duration: 5 Days, 5.5 hours per day
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    Next Date: February 9-13, 2026
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    Format: Live Online Format

£450Registration Fee

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Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP01) SOLD OUT!

Delivered remotely (United Kingdom) Western European Time, United Kingdom

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

Get Tickets £450.00
BMIN03

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.

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    Duration: 5 Days, 7 hours per day
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    Next Date: February 23-27, 2026
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    Format: Live Online Format

£500Registration Fee

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Bayesian Modelling Using R-INLA

Delivered remotely (United Kingdom) Western European Time, United Kingdom

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.

Get Tickets £500.00

PYBD01

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.

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    Duration: 4 Days, 7 hours per day
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    Next Date: March 2-5, 2026
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    Format: Live Online Format

£480Registration Fee

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Python for Biological Data Exploration and Visualization

Delivered remotely (United Kingdom) Western European Time Zone, United Kingdom

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

Get Tickets £480.00 24 tickets left
SCRN02

Single cell RNA-Seq analysis (SCRN02)

Single cell RNA-Seq analysis (SCRN02)

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

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    Duration: 4 Days, 3.5 hours per day
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    Next Date: March 16-19, 2026
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    Format: Live Online Format

£350Registration Fee

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Single cell RNA-Seq analysis (SCRN02)

Delivered remotely (United Kingdom) Western European Time Zone, United Kingdom

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

Get Tickets £350.00
APYB01

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.

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    Duration: 4 Days, 7 hours per day
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    Next Date: March 23-26, 2026
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    Format: Live Online Format

£480Registration Fee

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Advanced Python for Ecologists and Evolutionary Biologists

Delivered remotely (United Kingdom) Western European Time Zone, United Kingdom

Take your Python skills further. Learn OOP, testing, and optimisation for complex bioinformatics tasks.

Get Tickets £480.00 17 tickets left
CIFE01

Causal Inference for Ecologists (CIFE01) SOLD OUT!

Causal Inference for Ecologists (CIFE01) SOLD OUT!

Causal Inference for Ecologists is an applied R course teaching researchers how to identify and estimate causal effects in ecological and environmental data.

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    Duration: 5 Days, 4.5 hours per day
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    Next Date: March 23-27, 2026
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    Format: Live Online Format

£400Registration Fee

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Causal Inference for Ecologists (CIFE01) SOLD OUT!

Delivered remotely (United Kingdom) Western European Time Zone, United Kingdom

Causal Inference for Ecologists is an applied R course teaching researchers how to identify and estimate causal effects in ecological and environmental data.

Sold Out £400.00

Testimonials

PRStats 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 PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.

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Rolando O. Santos

PhD Assistant Professor, Florida International University

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Courses attended

SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07

Testimonials

I have attended six different courses organised by PR Stats. When I was midway through my PhD it was apparent that statistical ecological science was inevitably evolving faster than the knowledge of some of my university tutors. Attending courses with PR Stats became a vital fundamental way of learning advanced statistical and spatial analysis. Since then, I have continued attending courses covering new material, mixed effects models, Bayesian statistics, and including recently introduced R packages and their functionality. The courses have also given me exposure to some world leaders in their field. I have appreciated discussing with them different modelling approaches, which have been informative for my research. I can count four of my published papers as having been directly influenced by courses from PR Stats. My most recent work benefitted from modelling advice on sample design and model accuracy evaluation and can be seen here.

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Carlos P.E. Bedson

Quantitative Spatial Ecology, Ecology and Environment Research Centre, Manchester Metropolitan University, United Kingdom

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Courses attended

ADVR08, ENMR03, BMIN02, ISBD01, BADA01, SDMB06

Testimonials

PRStats 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 PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.

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Rolando O. Santos

PhD Assistant Professor, Florida International University

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Courses attended

SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07

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