So you're thinking about the Microsoft AI-102 exam. Maybe you work with Azure AI every day. Maybe you just want Cloud Practitioner-level AI knowledge to help customers design Azure AI solutions. Either way, this AI-102 study guide is for you. This article covers everything you need to know about azure ai engineer certification guide. This study guide covers the most common Azure AI Architect exam scenarios, the way AI solutions are actually built and deployed. Real Azure AI service decisions. No vague language. Let's get to it.
What Is the Azure AI-102 Exam? The Azure AI-102: Designing and Implementing Microsoft Azure AI Solutions exam leads to the Microsoft Certified: Azure AI Engineer Associate certification. It tests whether you can plan, manage, and implement AI solutions using Azure AI services. Target audience: AI engineers, solution architects, developers who work with Azure AI. | Detail | Info | |
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| | Exam Code | AI-102 | | Certification | Microsoft Certified: Azure AI Engineer Associate | | Questions | 40 to 60 | | Time | 100 minutes | | Cost | 165 USD | | Passing Score | 700/1000 | ## Domain Breakdown | Domain | Weight | What You Need to Know | |
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| | Plan and manage an Azure AI solution | 20 to 25 percent | Architecture, security, deployment, monitoring | | Implement generative AI solutions | 15 to 20 percent | Foundry, RAG, prompts, content safety | | Implement agentic solutions | 5 to 10 percent | Agents, tools, workflows | | Implement computer vision solutions | 10 to 15 percent | Vision API, Custom Vision | | Implement natural language processing solutions | 15 to 20 percent | Language, Speech, Translator | | Implement knowledge mining and information extraction | 15 to 20 percent | Search, Document Intelligence | ## The Azure AI Service Map You Must Know Every scenario question comes down to picking the right Azure service. This table is your cheat sheet: | Requirement | Right Service | Wrong Choice | |
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| | Extract fields from invoices or receipts | Azure Document Intelligence | Azure AI Vision OCR | | Semantic or vector search across documents | Azure AI Search with vectors | Plain keyword search | | Moderate harmful text or images | Azure AI Content Safety | Azure AI Language | | Sentiment, PII, key phrases | Azure AI Language | Azure AI Speech | | Speech to text, text to speech | Azure AI Speech | Azure AI Language | | Translate with domain terminology | Custom Translator | Standard Translator | | Image tags, captions | Azure AI Vision | Azure AI Document Intelligence | | Build and evaluate prompts | Microsoft Foundry | Manual testing | | Ground model on enterprise data | RAG with Azure AI Search | Fine tuning | #
