Generative AI & RAG Workshop

We’re so excited you’re here! 🎉

You’re one step closer to building your own GenAI app — and gaining hands-on experience with the technology powering tools like ChatGPT and Perplexity.

This is a 4-hour remote workshop where you’ll:

✅ Learn how Retrieval-Augmented Generation (RAG) works

✅ Build your own AI assistant with real code

✅ Earn a Certificate of Completion

✅ Walk away with a project you can showcase on your resume or GitHub

Generative AI & RAG Foundations: From LLMs to Retrieval-Augmented Systems

Step into the world of Generative AI and Retrieval-Augmented Generation (RAG) with this comprehensive 4-hour workshop designed for Students, Developers, Leaders, and AI Enthusiasts. This session provides a dual foundation: understanding how modern generative AI models work and learning how RAG extends their capabilities to deliver accurate, context-rich answers.

What You’ll Learn

By the end of this session, participants will:

1. Grasp the fundamentals of Generative AI and the architecture behind large language models (LLMs).
2. Understand the limitations of standalone LLMs and why RAG is a powerful enhancement.
3. Explore the building blocks of RAG, including embeddings, vector databases, and retrieval workflows.
4. Learn to design and deploy a simple end-to-end RAG pipeline integrated with generative models.
5. Review real-world use cases combining GenAI and RAG—from chatbots and knowledge assistants to enterprise search solutions.
6. Gain actionable insights on evaluation, optimization, and trends shaping the future of applied GenAI.

Agenda Overview

1. Introduction to GenAI & LLMs: Core concepts, how LLMs generate text, and the strengths/limitations of generative models.
2. Introduction to RAG: What RAG is, why retrieval is crucial, and how RAG complements generative capabilities.
3. Essential Components: Explore embeddings, vector databases, indexing strategies, and prompt orchestration.
4. Hands-On Lab: Build and test a simple RAG-enabled GenAI pipeline with guidance from experts.
5. Applications and Best Practices: Examine practical enterprise use cases, performance tuning, and evaluation techniques.
6. Q&A and Interactive Discussion: Engage directly with instructors, clarify concepts, and share insights.

Who Should Attend?

This session is ideal for professionals or enthusiasts who want to go beyond the buzzwords, understand the mechanics of GenAI, and learn how retrieval-based systems are built for accuracy and scalability. No prior experience with RAG is required; basic familiarity with AI concepts is sufficient.