R Consortium

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The R Consortium, Inc. is a group organized under an open source governance and foundation model to support the worldwide community of users, maintainers and...

Latest Videos

Interactive and Instant GenAI-driven Creation of Clinical Trial Applications

You Should Probably Map That Introduction to Geospatial Analysis in R

When Everyone Can Code, What’s a Quant Still For

RMedicine 2026 Hackathon Kickoff

Make your first R open source project contribution with git, forks, and PRs

Fully Reproducible Model Validation Reports Using Docker, R, Quarto, {renv} and {targets}

R Consortium Webinar - Scaling up data analysis in R with Arrow

kuzco Computer Vision made easy

Introducing geodl An R package for geospatial semantic segmentation

Making Health Economic Models Shiny

mini007 - A Lightweight Framework for Multi-Agent Orchestration in R

Gradient Boosting Machines (GBMs) in the Age of LLMs and ChatGPT

Brand your docs, apps, and ggplots using LLMs

Tracking the Evolution of R and Python Tools for GenAI

Me, Myself & Claude

Keeping LLMs in Their Lane Focused AI for Data Science and Research

R+AI Use RAG from your database to gain insights into the R Consortium

How to use pointblank to understand, validate, and document your data

Modular, interoperable, and extensible topological data analysis in R

SAS to R in Pharma – Creating Custom Solutions for Closed-Source Code

J&J A Hybrid SASR Submission Story

Open Source Software Adoption in Japan’s Pharma Industry Key Findings from 2024 JPMA R Usage Survey

R Consortium Webinar Unlocking Collaborative Power with Git, GitHub CICD, and LLMs in Pharma

R for Health Technology Assessment (HTA) Identifying Needs, Streamlining Processes

From Paper to Pixels Digitizing Water Quality Data Collection with Posit and Esri Integration

“Visualise, Optimise, Parameterise!” - Writing dataviz code - UPDATED

Scaling the r-spatial ecosystem for the modern composable data pipeline

First Steps with SQL in R Making Data Talk

RMedicine 2025 - Closing Remarks - Final Day - Michael Kane

Unified Deep Learning Survival Analysis for Competing Risk Modeling with Functional Covariates