AI-103 Study Roadmap

Begin by listing the four current skill areas: plan and manage an Azure AI solution, implement generative AI and agentic solutions, implement computer vision solutions, and implement information extraction solutions. Use that list as the roadmap backbone.

Start with service selection, access, responsible AI, evaluation, and deployment considerations. Review Azure AI Foundry, Azure OpenAI model choices, content filtering, managed identities, and monitoring concepts before moving into deeper implementation.

Next, work through generative AI and agentic scenarios. Study system messages, prompt structure, model behavior, grounding, tools, connectors, and agent workflows. Build a small example so the relationship between prompts, tools, retrieval, and evaluation is concrete.

Review Azure AI Vision and Azure AI Document Intelligence separately. Vision questions tend to involve images, video, object detection, or visual analysis. Document Intelligence questions involve forms, invoices, documents, fields, and extracted structure. Keeping those inputs separate prevents service-selection mistakes.

Finish each study cycle by reviewing practice explanations and Microsoft documentation. If the weak area is retrieval, revisit Azure AI Search and vector search. If the weak area is safety, revisit content filtering and responsible AI. If the weak area is agents, revisit Azure AI Foundry agent development and tool definitions.