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Work smarter, not harder. Here's exactly where to focus your study hours.
| Objective Domain | Weight | Difficulty | Our Study Strategy |
|---|---|---|---|
| Implement Generative AI & Agentic Solutions | 30-35% | Critical | This makes or breaks your score. Don't sleep on agentic workflows, multi-agent orchestration, and function calling inside Microsoft Foundry. Know how to hook up tool connections and manage conversational memory—these aren't just basic API calls anymore. |
| Plan & Manage an Azure AI Solution | 25-30% | High | Easy marks if you know the architecture rules. Focus heavily on Microsoft Foundry resource deployment, RBAC permissions, network isolation, and cost tracking. Candidates usually miss points here by choosing the wrong deployment SKU or missing token quota limits. |
| Implement Information Extraction Solutions | 10-15% | High | This catches people off-guard. It's all about RAG ingestion pipelines, hybrid and vector search in Azure AI Search, and chunking strategies. Make sure you know when to trigger custom skillsets versus pre-built Document Intelligence extraction. |
| Implement Computer Vision Solutions | 10-15% | Medium | Stick to the 2026 specs. Pay attention to Azure Content Understanding, multimodal image analysis, and visual grounding. You don't need to overcomplicate classic vision APIs—focus on how models parse reference media and structured visual prompts. |
| Implement Text Analysis Solutions | 10-15% | Medium | Straightforward points. Master LLM-based structured JSON extraction, sentiment analysis, and Content Safety guardrails. Make sure you can spot indirect prompt injection attempts in user-supplied text. |
Get a glimpse of the real exam environment. Download our free Azure AI Engineer Associate AI-103 demo PDF and test the interactive browser engine right now.
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