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Course Preview | AI-103 | Develop AI apps and agents on Azure

Building an AI solution goes beyond calling a model. The focus is on creating production-ready AI applications and agents with Microsoft Foundry that can use enterprise data, interact with tools, process different content types, and collaborate to complete real tasks.

Core capabilities to know

Area What you should understand
Generative AI apps Build conversational applications using models, APIs, and SDKs
Grounding Connect models to your own data for relevant, fact-based responses
Agents + tools Let agents retrieve information and take actions
Multi-agent systems Orchestrate specialized agents to collaborate on workflows
Multimodal AI Process text, documents, vision, and speech
Production Deploy, publish, monitor, secure, and apply responsible AI safeguards

Exam focus: Understand not just what these capabilities do, but when and why you would use them together in an Azure AI solution.

Think in solution flows

A useful mental model for AI-103 is:

User → AI App/Agent → Model → Data + Tools → Action/Response

For more complex solutions:

User → Orchestrator → Agent A + Agent B + Agent C → Tools/Data → Result

An agent therefore isn't simply a chatbot. It combines a model's reasoning capabilities with instructions, knowledge, and tools so it can perform useful work.

Preparing effectively

The course assumes working knowledge of Python, REST APIs/SDKs, Azure fundamentals, and generative AI concepts. Hands-on practice is important: build applications in Microsoft Foundry, connect models to data, add tools to agents, experiment with multimodal inputs, and create multi-agent workflows.

Key takeaway: Think beyond prompts and models. AI-103 is about assembling the components required for an end-to-end AI solution:

Models → Grounding → Tools → Agents → Orchestration → Production

Related Snipps

AI103
Azure
Foundry
Agents
Certification

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