Are you a tech leader or IT decision-maker curious about Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) but short on time? We’ve got you covered with a 4-part YouTube workshop series that breaks down these concepts in a practical, enterprise-focused way – no deep technical dive required.
Why LLMs & RAG? LLMs (think GPT-style AI) can generate human-like text, and RAG is a clever approach to make those models even more useful by letting them fetch real-time, relevant data from your knowledge sources.
This means smarter AI applications that deliver accurate, up-to-date insights without you constantly retraining models. Imagine chatbots that actually use your latest company data or decision-support tools that combine AI with your internal knowledge.
This series is ideal for leaders who want to explore integrating AI into their business value streams without heavy technical commitment.
Workshop Sessions at a Glance
Part 1 – LLM & RAG Fundamentals: How do LLMs and RAG work together? Learn how RAG integrates real-world data into AI responses and why retrieving info on the fly is a game-changer for enterprise AI. (Watch now)
Part 2 – LLMs, Tokens & Vectors: A non-deep-dive look at the tech under the hood. Discover how external knowledge boosts LLM performance, with simple explanations of tokens, embeddings (vectors), and metadata storage. (Watch now)
Part 3 – Building a Custom RAG Model: See RAG in action. This session walks through building a custom RAG-powered app, showing how to retrieve, analyze, and generate content using your own data. (Yes, even non-developers will follow along!) (Watch now)
Part 4 – LLMs & Transformers in Action: Go behind the scenes of modern AI. Explore the basics of how transformer-based LLMs work across text, images, and more – all explained in plain language to help you understand the tech shaping today’s AI innovations. (Watch now)
If you’re looking to ramp up your AI strategy or just want to see what’s possible when you combine LLMs with your company’s data, this workshop series is a friendly place to start.
