A space for things I am learning and want to share — primarily in AI, data science, and engineering systems. Each tutorial is meant to be short, hands-on, and reproducible.

I add to this page as I learn. If you spot an error or have a suggestion, please get in touch.

Topics in Progress

I am currently building out tutorials in the following areas. Check back soon for the first published pieces.

  • Practical AI for Engineers — prompt patterns, retrieval-augmented generation (RAG), and agentic workflows for everyday engineering tasks.
  • Reinforcement Learning Foundations — from Q-learning to deep RL, with code-first examples.
  • Federated Learning on the Edge — building privacy-preserving ML pipelines for IoT devices.
  • Climate-Health Data Engineering — using the climatehealth R package and reproducible analytical pipelines (RAP).
  • IoT System Design — from sensor selection through edge inference to cloud dashboards (ESP32, Raspberry Pi, MQTT).
  • R Package Development — what I learned shipping climatehealth to CRAN.

Coming Soon

  • Building a Document-Grounded Chatbot with Claude Code — a step-by-step walkthrough of the live demo from my NSE Glasgow webinar (April 2026).
  • From Notebook to CRAN — the workflow I used to turn a research codebase into a CRAN-published R package.
  • Federated Anomaly Detection on a Budget — a minimal working example you can run on a laptop.

Last updated: April 2026.