A practical, end-to-end bootcamp for building real-world generative AI applications, from concept to deployment.
October 16, 2026 | Conference Center Karolos Papoulias, Ioannina – Greece
An immersive, hands-on technical bootcamp designed for engineers who want to dive into the AI era. Participants will learn LLM fundamentals, set up local models (Ollama, LM Studio), and build their first generative AI web application using TypeScript, Vercel AI SDK, Next.js, and Shadcn UI components. The session covers Retrieval-Augmented Generation (RAG) and tool integration, empowering attendees to code and deploy their own GenAI apps in one day—all running on their local machines.
By day’s end, every participant will have a working AI application running on their local machine—ready to extend and deploy to production.
FULL TIME
8 HOURS
IN PERSON INSTRUCTOR LED TRAINING
HANDS ON FRAMEWORKS AND USE CASES
Participants are welcomed into the bootcamp with a clear overview of the agenda, learning objectives, and expected outcomes. The session sets the context of the AI era, aligns on terminology, and establishes a shared understanding of how generative AI is reshaping products and engineering workflows.
This session demystifies Large Language Models by explaining how they are trained and how they generate responses. Core concepts such as tokens, context windows, temperature, prompting techniques, and common use cases are explored to build a strong conceptual foundation.
Participants install and configure a local LLM using Ollama or LM Studio, run their first inference, and compare different models. The session covers performance considerations, privacy benefits, and trade-offs between local and cloud-based models.
Deliverable: Working local LLM instance running on participant laptops
An introduction to building GenAI backends using TypeScript and the Vercel AI SDK. Participants explore SDK architecture, API patterns, streaming responses, and prompt engineering techniques while creating their first working GenAI application.
Deliverable: Hello World GenAI app with streaming responses
This module focuses on building a modern frontend using Next.js and shadcn/ui. Participants learn about project structure, reusable components, UI/UX best practices, state management, and how to connect the frontend seamlessly to their AI backend.
Deliverable: Functional frontend scaffold with chat UI and state management
Participants learn the fundamentals of Retrieval-Augmented Generation, including embeddings, vector databases, and retrieval workflows. The session also introduces tool calling and basic agentic patterns to enable more reliable and context-aware AI applications.
In this guided lab, participants complete their GenAI application by integrating the local LLM, RAG pipeline, and tools. The session concludes with deployment and validation of a fully working end-to-end AI application.
Deliverable: Deployed GenAI application with all features working
Selected participants present their applications live, showcasing different approaches and use cases. The session concludes with feedback, awards, and open networking to reinforce learning and strengthen the community.
Deliverable: Recognition, community building, inspiration for participants