PDF Version DemoHow to study the AI-102: Designing and Implementing an Azure AI Solution Exam
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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam
- Length of Examination: 50 mins
- This is beta exam.
- Language: English, Japanese, Chinese (Simplified), Korean.
- Passing Score: 700 / 1000
- Type of Questions: This test format is multiple choice.
- Number of Questions: 40 to 60 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice.)
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Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Plan solutions aligned with responsible AI principles - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select suitable AI models - Monitor, optimize, and secure AI solutions - Create and configure Azure AI resources |
| Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Implement model monitoring and feedback - Deploy and manage generative models |
| Implement knowledge mining and information extraction solutions | 15-20% | - Build knowledge bases and search indexes - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data |
| Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection - Customize and deploy NLP models - Implement translation and summarization |
| 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 computer vision solutions | 10-15% | - Build and deploy custom vision models - Extract text and handwriting from images - Analyze images and detect objects/features - Integrate vision capabilities into applications - Process and index video content |
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