Learn LLMs in R
Resources for learning how to work with LLMs in R:
Comprehensive: The Athlyticz course covers ML with tidymodels through to LLMs, RAG, and deployment.
Self-paced: My LLMs in R course if you want to learn at your own pace.
Cohort-based: My Practical AI for R course with live sessions and group learning.
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Athlyticz: ML and LLMs in R
A comprehensive course I developed with Christoph Scheuch covering the full journey from machine learning fundamentals to building LLM-powered applications in R.
The course covers:
- ML foundations with tidymodels: model evaluation, resampling, tuning, preprocessing
- Regression and classification models including neural networks
- Model deployment with vetiver and orbital
- Working with LLMs using ellmer
- Retrieval-augmented generation (RAG) for building apps with your own data
Aimed at R users comfortable with the tidyverse who want to build and deploy ML and LLM applications.
LLMs in R (Self-Paced)
Learn to work with large language models in R at your own pace.