Azure AI-103 exam guide covering app design, agents, retrieval, tool use, monitoring, and security decisions.
This Microsoft Certified: Azure AI Apps and Agents Developer Associate guide helps AI-103 candidates focus on what the exam tests, where close answers usually split, and which review page to use next.
Use the study plan to group Azure service, identity, and deployment choices, the cheat sheet for scenario decisions, the sample questions for applied practice, the FAQ for scope checks, the resources page for Microsoft Learn exam references, and the glossary when product names blur together.
| Item | Guide value |
|---|---|
| Vendor | Microsoft |
| Exam or credential | Microsoft Certified: Azure AI Apps and Agents Developer Associate |
| Code or shorthand | AI-103 |
| Study level | Associate developer |
| IT Mastery page | AI-103 exam page |
| Guide shape | Start-here page, study plan, cheat sheet, sample questions, FAQ, resources, and glossary. |
| Lane | What to master | Common weak answer |
|---|---|---|
| Foundry solution planning | Choose models, deployment shape, identity, network boundaries, cost controls, and responsible AI checks before coding. | Jumping straight to a model or prompt when the requirement is governance, private access, or deployment control. |
| Generative AI and agents | Separate prompt design, tool use, retrieval grounding, agent orchestration, evaluation, and safety filtering. | Treating every failure as prompt wording when the fix is retrieval quality, permissions, tool contract, or evaluation evidence. |
| Vision, speech, text, and extraction | Match the workload to the right multimodal, language, document, or content-understanding capability. | Using a general chat model when the scenario needs structured extraction, OCR, speech, or image-specific handling. |
| Python implementation and operations | Know where SDK calls, secrets, managed identity, telemetry, retries, and evaluation loops belong. | Shipping a demo client without auth, monitoring, error handling, or reproducible evaluation results. |
Classify the workload first: agent, retrieval, multimodal, extraction, or operations. Then apply identity, data boundary, evaluation, and observability.
Use the current Microsoft Learn exam page for live exam details, including name, status, pricing, duration, delivery method, languages, retirement or beta changes, and domain weights where applicable.