Large Language Models (LLMs) have transformed the way we build intelligent applications, but using them effectively requires more than just good prompts. Out of the box, LLMs are frozen in time, lack access to your private data and, most worryingly, can produce plausible but incorrect responses. To create trustworthy AI agents - applications that can reason and act - we need to combine models with additional tools, data sources, and orchestration layers.

This one-day course will guide you through using Azure AI Foundry, Microsoft's one-stop portal for AI infrastructure. We'll use AI frameworks to build practical AI applications, including agentic systems that can plan, reason, and act on objectives. We’ll see how to extend raw LLM capabilities with techniques such as prompt engineering, Retrieval Augmented Generation (RAG), plugins (tools), and orchestration.

This hands-on, full-day course will use various AI models provisioned in Azure AI Foundry. You'll learn how to:
• Apply prompt engineering and RAG for accuracy and grounding.
• Extend LLMs with custom plugins, APIs, and business logic.
• Build multi-agent workflows.
• Make use of Computer Vision.
• Use responsible AI practices.
• Design and deploy agentic systems that go beyond text generation to perform actions.

Bring your laptop to follow along with the examples, or simply observe and learn. Either way, you’ll be equipped to design, build, and deploy AI applications that go beyond chat and deliver real business value.