AI RAG Engineering

Learn to build production-ready Retrieval-Augmented Generation (RAG) systems that intelligently combine large language models with contextual knowledge.

Intermediate

Artificial Intelligence

2 days

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What you will learn in this course

WHY THIS COURSE IS A GAMECHANGER: Most engineers treat RAG as a black box – they may understand the theory but struggle to architect, optimize, and deploy RAG systems that work reliably in production. This course transforms RAG from abstract concepts into tangible, deployable skills. You'll build a complete chatbot system from scratch, understanding every component of the RAG pipeline.

ABOUT THIS COURSE: Instead of abstract examples, you're building a Chatbot – a real RAG system that answers customer questions by retrieving and synthesizing information from actual website content. By the end of the course, you'll have a working prototype that you can deploy. You'll learn abbout data ingestion, embeddings & vector search, LLM integration, security & quality controls, and Docker deployment.

Agenda

RAG Fundamentals & Architecture

Data Foundation & Embeddings

Advanced Retrieval

LLM Integration & Chat Backend

Security & Production Readiness

Deployment

audience

This course is designed for

Software Engineers wanting to understand RAG systems
DevOps Professionals deploying AI systems
AI/ML Practitioners building production applications
Anyone interested in AI development

prerequisites

To get most out of this course, you should have:

Basic Python knowledge (familiar with functions, classes, libraries)
Understanding of APIs (REST, HTTP basics)
Comfortable using AI tools (Copilot or similar)

style

Our trainers have years of experience and will deliver the right mix of:

Inhalte mit echten Szenarien aus dem Entwickleralltag
Praktische Übungen in Form von Hands on Labs
Offizielle Trainingspartner (Mondoo & IBM HashiCorp)
Lebenslanger Zugriff auf Kursunterlagen
Update Infos auch nach dem Workshop
Expert:innen mit echter Projekterfahrung

Technical requirements

We recommend the following equipment:

Stable internet connection
Access to AI tools and services (e.g., OpenRouter, Groq, OpenAI API) (Free accounts may need to be created)
Browser compatible with modern web applications (e.g., Chrome)
If you're eager to try out demonstrated tools on your own: Code editor (e.g., VS Code) with sufficient hardware (GPU) and a Python installation

Need more than training?

Training is often a first step. Many teams realize they need support beyond the course to make things work in production, speed up the process or bridge short-term bottlenecks..

Explore Consulting Solutions

We can support you beyond training, through hands-on consulting, project collaboration, or as an embedded enablement team, we are helping you apply what you learned, validate decisions, and move forward with confidence.

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