This course is your complete guide to designing AI agents using Azure AI Agent Service, integrating Azure AI Foundry, RAG (Retrieval-Augmented Generation), and deploying to production using Azure Kubernetes Service (AKS).
You’ll go beyond theory — through hands-on labs, real-world projects, and architectural blueprints, you’ll learn how to deliver scalable, secure, and observable GenAI solutions using modern Azure tools.
Whether you’re a developer, data scientist, or cloud architect, this course equips you with the end-to-end skills to move from prototype to production.
What you’ll learn:
- Implement secure, scalable RAG workflows with vector search and embedded data
- Containerize your agents and deploy them on Azure Kubernetes Service (AKS)
- Learn about AKS Networking, Ingress Controllers, Multi-Container Design Patterns etc.
Who this course is for:
- AI engineers and developers working with LLMs and Azure
- Cloud professionals looking to scale GenAI solutions on Kubernetes
- Solution architects designing secure, production-grade AI systems
- Anyone looking to master the Azure AI Agent Service + AKS combo
Prerequisites:
- Basic knowledge of Python and REST APIs
- Familiarity with Azure fundamentals
- Some understanding and experience with Docker and Containers
- Interest or background in AI and LLM-based applications





