Prepare for the Microsoft AI-103 Azure AI Apps and Agents Developer Associate exam with hands-on, scenario-based practice
These AI-103 practice tests are for developers preparing for the Microsoft Certified: Azure AI Apps and Agents Developer Associate credential. The exam is also called Developing AI Apps and Agents on Azure. AI-103 replaces the retired AI-102 and is built around Microsoft Foundry. It tests whether you can choose the right models and services, build grounded generative AI apps and agents, and run them securely and responsibly in production.
Why this course
AI-103 is a developer exam about implementation choices. You need to know which model fits a task, which retrieval method grounds an agent best, how to lock down a deployment with managed identity, and how to stop a prompt injection hidden inside an image. Every question here starts from a realistic build scenario and asks for the best technical decision. All questions are original, mapped to the current skills outline, and updated as Microsoft revises the exam.
What’s inside, by exam domain
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Planning and managing an Azure AI solution: choosing between large, small, and multimodal models; selecting Foundry services, retrieval, memory, and tools; deployment options and CI/CD; quotas, scaling, and cost; monitoring drift and grounding quality; security with managed identity and private networking; and responsible AI guardrails, evaluations, auditing, and agent oversight
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Generative AI and agentic solutions: retrieval-augmented generation, tool-augmented and multistep workflows, Foundry SDKs, agent roles and tool schemas, function calling and memory, multi-agent orchestration, approval flows, prompt and parameter tuning, and observability with tracing and token analytics
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Computer vision: image and video generation and editing, multimodal understanding, captions and alt text, Content Understanding for visual and video analysis, and content safety for visual inputs
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Text analysis: generative entity, topic, and summary extraction, structured JSON outputs, sentiment and sensitive-content detection, translation, and speech-to-text and text-to-speech for agents
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Information extraction: ingesting and indexing documents, images, audio, and video; semantic, hybrid, and vector search; enrichment skills; OCR-based ingestion; and Content Understanding analyzers for grounded, structured output
How the explanations help you learn
Every question includes a detailed explanation for every answer option. You see why the correct choice works for that scenario and why each of the other choices fails. A wrong option might be a less suitable model, a weaker retrieval strategy, a security gap, or a service that doesn’t support the feature. This builds the practical judgment AI-103 measures and that you need on real projects.
Who it’s for
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Azure AI engineers and Python developers who build generative AI apps and agents on Azure
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Candidates moving to AI-103 from the retired AI-102
Start practicing today
You get lifetime access, regular updates, and the protection of Udemy’s 30-day refund policy. Enroll now, find your weak domains, and go into AI-103 ready to build like an Azure AI engineer.
Disclaimer
This course is an independent, unofficial study resource. It is not affiliated with, endorsed by, or sponsored by Microsoft Corporation. Microsoft, Azure, Microsoft Foundry, and related names are trademarks of the Microsoft group of companies. They are used only to identify the exam this course helps you prepare for. All questions are original practice material and are not drawn from any Microsoft exam.
