What you'll learn:
- Learn about Azure Kubernetes Service
- Learn about kubernetes networking, multi-container design patters, ingress controllers etc.
- Containerize and deploy AI Agents on AKS (Azure Kubernetes Service) for scalable, production-ready inference.
- Implement Retrieval-Augmented Generation (RAG) with secure data access and enterprise-grade architecture.
Unlock the power of Azure AI Foundry Agents and AKS to build, deploy, and scale real-world enterprise LLM applications.
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
