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AI-103 Skills measured breakdown

AI-103 Skills Measured

The AI-103 skills measured page should reflect Microsoft objective language, not local question counts. Use the four official skill areas to organize study and then map each area to the Azure service decisions it tests.

Plan and Manage an Azure AI Solution

This skill area focuses on selecting Azure AI services, planning resources, managing access, applying responsible AI controls, evaluating systems, and choosing the right Foundry services for generative AI and agents. It is the foundation for the implementation topics that follow.

Implement Generative AI and Agentic Solutions

This area covers building generative applications and agentic workflows with Azure AI Foundry and Azure OpenAI. Study system messages, prompt design, model selection, tool definitions, connectors, grounding, evaluation, and operational considerations for generative systems.

Implement Computer Vision Solutions

Computer vision topics involve image and video workloads. Review when Azure AI Vision fits object detection, image analysis, multimodal processing, or video-related tasks, and keep those use cases separate from document extraction or text-based retrieval scenarios.

Implement Information Extraction Solutions

Information extraction focuses on retrieval, grounding, document extraction, structured outputs, and workflows that turn unstructured or semi-structured content into usable data. Azure AI Document Intelligence and Azure AI Search often appear here, but they solve different parts of the problem.

Next steps

Use these DotCreds paths when you are ready to practice, compare options, or keep studying.

DotCreds Guided CourseProvides structured learning for the AI-103 exam. DotCreds Practice BankOpens practice questions for checking AI-103 understanding. Related CertificationsCompare nearby credentials and next study options.
Frequently asked questions
What is the AI-103 certification?

Exam AI-103: Developing AI Apps and Agents on Azure is the credential this DotCreds guide is organized around. Use this page to understand the topic, then move into practice or the guided course when you are ready.

How should I start studying for AI-103?

Start with the beginner guide and study roadmap, then use practice questions to find weak areas before you spend time rereading everything.

Is AI-103 worth studying?

It can be worth studying when the skills match your target role, current experience, and next job move. The related certifications page can help compare nearby options.

How long should I study for AI-103?

Study time depends on your background. Use a self-paced plan, review missed questions, and keep the official objectives close while you practice.

Ready to start your AI-103 journey?

Start with a focused practice set, then use your missed questions to decide what to study next.

Get started now
Reviewed sources

Official and vendor docs used to ground this page.

Source

Azure OpenAI Service models

Documents Azure OpenAI Service models, which appears in the source-backed concepts for this DotCreds bank.