4 Further reading
Here are some courses and guides for actually using the LLM tools listed here. Newest entries at the top, and going forward I will record the date in which I added them.
Sharon Machlis at InfoWorld just published a post titled: GenAI tools for R: New tools to make R programming easier. The content overlaps with this guide but there are lots of well-explained examples. Worth checking out.
(added 26/03/2025)
Not a tutorial or course and not necessarily R-related, but I came across this public list of AI-related GitHub repositories compiled by Garrick Aden Buie. If you are familiar with Garrick’s work, then you know that at least some of this cool AI stuff will make it onto R packages or extensions in the near future. Worth checking out. (added 24/03/2025)
This is beyond my skillset and experience level, but Javier Orraca-Deatcu recently (07/03/2025) posted “Vector DB + RAG Maker”. The post introduces a “limited vector database and RAG system developed with Python, made for R users, designed to generate bleeding-edge responses from challenging LLM prompts using your local R technical documentation”. Looks fun and promising.
(added 18/03/2025)
Here’s a long-form video of Simon Couch as a guest on the R For the Rest of Us podcast. The interview goes through a lot of relevant AI in R topics, an includes lots of detail on using chores and gander. (added 10/03/2025)
This long-form post by Athanasia Mo Mowinckel goes through the setup process and various adventures for using various relevant tools including ellmer chores, gander and ensure with local ollama models for package development. The text shows that the tooling is not quite there yet, but on its way.
(added 03/03/2025)
David Keyes at R for the Rest of Us recently launched “Using AI with R”: a free, self-paced short course for using LLM-based assistants with R. Covers many of the tools and packages mentioned on this site.
Albert Rapp also has an in progress Quarto book “AI with R”, built from his existing blog posts for addressing different tasks using AI tool and not having to work in browser-based chat boxes. This resource includes some very well-written documentation for using mall and ellmer.
Leonardo Collado Torres gave a short course that covered many of the packages and tools used here, and the recording is available on YouTube. The course materials also include useful step-by-step instructions for setting up and using copilot.
My fellow UQ alum Chris Brown, now at UTAS, shared this recent entry about summarizing key details from a methods section to assist in literature reviews. The example uses tidychatmodels and I particularly like Chris’ advice: “I’d also recommend you manually check results so that you still learn something yourself”.
This post now has a follow-up entry (published 15/03/2025, added here 18/03/2025) which uses ellmer for the same task of literature review. Very detailed step-by-step instruction and a thoughtful discussion at the end.
This post by Nic Crane demonstrates how we can use ellmer and Shiny to build an app that creates posts for different social media platforms.