Overview
Go beyond prompt engineering and truly understand how LLMs learn, reason, and adapt.
In this live online session, you’ll uncover the art and science behind Retrieval-Augmented Generation (RAG) and Fine-Tuning, learning how to transform open-source models into sharp, domain-aware problem solvers.
Expect a practical, no-fluff walkthrough from data preparation and embedding strategies to evaluation and deployment. You’ll see what actually works in production, not just what sounds good on paper.
What you’ll gain:
- A clear mental model of how RAG pipelines operate end-to-end.
- Step-by-step fine-tuning flow for open-source models like Gemma, LLaMA, or Mistral.
- Insights into optimizing quality, latency, and cost.
- Real implementation tips from production use cases.
💡 Added Bonus:
All participants get access to downloadable notebooks + resource pack, including fine-tuning templates, RAG architecture blueprints, and curated datasets to practice on after the session.
