Description:

Unlock the power of modern AI automation by learning to build fully local, production‑ready AI agents in just one day. This hands‑on workshop shows you how to transform n8n into a private, extensible AI automation engine running entirely on your own hardware—no coding required.

You’ll start by deploying a self‑hosted n8n environment with Docker, then progressively layer in real‑world capabilities: autonomous agent reasoning, document intelligence, vector‑based retrieval, and multi‑agent orchestration. Along the way, you’ll integrate both local LLMs (via Ollama and DeepSeek) and cloud models (via OpenRouter), giving you the flexibility to choose the right model for each task.

By the end of the day, you will have built a complete AI agent stack capable of research, data extraction, lead enrichment, email drafting, scheduling, and more powered by the Model Context Protocol (MCP) and connected to tools like Fire Crawl, Google Workspace, and custom sub‑workflows. You’ll walk away with reusable templates, a working local environment, and the confidence to design and deploy agentic systems for your business or clients.

This course is ideal for professionals who want to move fast, build real AI capabilities, and maintain full control over their data and infrastructure.

Duration:

1 Day

Course Code: BDT 532

Learning Objectives:

After this course, you will be able to:

1. Docker Introduction: Basic introduction to Docker as it makes it easier to build Agentic AI systems.
2. Vibe Coding & AI Velocity: Master Agent development IDE, Python, and spec-driven deployment to automate 80% of boilerplate coding .
3. Stateful Agents with LangChain/LangGraph: Move beyond linear chains to build cyclical state-machine-based agents with persistent memory and human-in-loop approvals.
4. Pydantic Agents with Pydantic AI: Leverage strict type-safety, dependency injection, and Pydantic structures for production-grade agentic behavior
5. The MCP Revolution: Build custom servers to connect LLMs directly to your SQL databases, local files, and internal APIs without exposing data to the public web.
6. Multi-Agent Orchestration: Use to tools like n8n, LangFlow to manage a “digital workforce” where specialized agents collaborate on complex business goals.
7. Enterprise RAG & Search: Optimize document retrieval using hybrid search, advanced chunking, and vector databases (Pinecone, Supabase, Chroma). (RAG: Retrieval Augmented Generation)
8. Local AI and Sovereignty: Deploy high-performance models like DeepSeek, Llama locally using Docker for total data privacy.
9. Voice and Vision Automation: Build real-time voice assistants and automated media pipelines.
10. AI Security & Compliance: Practical training on the EU AI Act, preventions for prompt injection, and data poisoning defense.

By the end of this AI Bootcamp, you will have the confidence and competence to tackle building Agentic AI systems.