Updated: Oct 08, 2026
No. of Questions: 425 Questions & Answers with Testing Engine
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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Certificate Validity Period: | 1 year (renewable via free online assessment) |
| Exam Format: | Hot area, Drag-and-drop, Case studies, Performance-based scenarios, Multiple choice, Multiple select |
| Available Languages: | Spanish, Chinese (Simplified), Korean, Indonesian, German, Italian, French, Portuguese (Brazil), English, Arabic (Saudi Arabia), Japanese |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals (AI-900) Microsoft Certified: Azure Developer Associate Microsoft Certified: Azure Data Scientist Associate |
| Passing Score: | 700 (scaled score out of 1000) |
| Real Exam Qty: | 40-60 |
| Exam Price: | $165 USD (varies by region: £113 GBP, €126 EUR) |
| Exam Duration: | 100 minutes |
| Recommended Training: | Microsoft Learn Learning Paths for AI-102 AI-102T00: Designing and Implementing a Microsoft Azure AI Solution |
| Exam Registration: | Microsoft Certification Exam Registration Pearson VUE Scheduling |
| Sample Questions: | Microsoft AI-102 Korean Sample Questions |
| Exam Way: | Online proctored (OnVUE) or onsite at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; recommended: experience with Azure services, AI concepts, and proficiency in Python or C#; AI-900 certification is recommended but not required |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-102 |
These are following steps for registering the AI-102: Designing and Implementing an Azure AI Solution exam.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
| Section | Weight | Objectives |
|---|---|---|
| Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data - Build knowledge bases and search indexes - Implement intelligent search and retrieval |
| Plan and manage an Azure AI solution | 20-25% | - Plan solutions aligned with responsible AI principles - Select suitable AI models - Select appropriate Microsoft Foundry Services - Monitor, optimize, and secure AI solutions - Create and configure Azure AI resources - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining |
| Implement generative AI solutions | 15-20% | - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Implement model monitoring and feedback - Deploy and manage generative models - Integrate Azure OpenAI and other generative models |
| Implement computer vision solutions | 10-15% | - Build and deploy custom vision models - Integrate vision capabilities into applications - Extract text and handwriting from images - Process and index video content - Analyze images and detect objects/features |
| Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration |
| Implement natural language processing solutions | 15-20% | - Perform text analysis, sentiment detection, and language detection - Implement translation and summarization - Customize and deploy NLP models - Build conversational AI and chatbots |
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