Architecting LLM Apps on Azure: RAG, Agents, and Real-World

About this course

Architecting LLM Apps on Azure: RAG, Agents, and Real-World GenAI Solutions

This course gives you a practical, architecture-focused pathway to master Retrieval-Augmented Generation (RAG) and architect advanced LLM applications on Azure’s AI ecosystem. Whether you're a developer, architect, or product manager, this course helps you design context-aware AI systems that are secure, scalable, and enterprise-ready.

RAG ARCHITECTURE AS THE CORE AI PATTERN

Unlike general LLM courses, this program is laser-focused on Retrieval-Augmented Generation as a modern architecture pattern. You’ll understand:

• Why RAG is essential to combat hallucinations
• How it grounds responses using enterprise data
• How to integrate Azure services like Azure AI Search, Azure OpenAI, and vector databases into the pipelineFROM CONCEPTS TO PRODUCTION-READY DEPLOYMENT
• We begin with the fundamentals of LLMs—what they are good at, where they fail, and how RAG bridges the gap. But this course goes much further.

You will learn:

• Key LLM application architecture concepts on Azure
• The differences between LLM apps and RAG solutions

How to extend LLM apps into agentic architectures by incorporating tools and dynamic data sourcesCHOOSING THE RIGHT AZURE TOOLS: AI FOUNDRY VS. COPILOT STUDIOA major highlight of the course is understanding when and how to use Azure’s no-code and low-code tools effectively:

• Copilot Studio for business-led rapid prototyping
• Azure AI Foundry for technical teams needing modular, configurable RAG/agent solutions
• We explore when to choose each tool based on business needs

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