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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Designing and Implementing a Microsoft Azure AI Solution Exam Certification Details:
| Schedule Exam | Pearson VUE |
| Exam Code | AI-102 |
| Exam Name | Microsoft Certified - Azure AI Engineer Associate |
| Passing Score | 700 / 1000 |
| Books / Training | Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution |
| Sample Questions | Designing and Implementing a Microsoft Azure AI Solution Sample Questions |
| Number of Questions | 40-60 |
| Exam Price | $165 (USD) |
| Duration | 130 mins |
Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution
Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.
They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.
Candidates for this exam should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.
Part of the requirements for: Microsoft Certified: Azure AI Engineer Associate
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Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Integrate Azure AI services into applications - Design and implement decision automation |
| Topic 2: Implement Generative AI Solutions | 10-15% | - Use Azure OpenAI Service for generative AI - Integrate Azure OpenAI models into applications - Apply responsible AI practices - Implement prompt engineering techniques |
| Topic 3: Implement Natural Language Processing Solutions | 20-25% | - Implement speech capabilities using Azure AI Speech - Create conversational AI solutions with Azure AI Bot Service - Translate text and speech - Analyze text using Azure AI Language - Build question answering solutions |
| Topic 4: Plan and Manage an Azure AI Solution | 15-20% | - Plan and configure secure AI solutions - Manage AI costs and resource allocation - Select appropriate Azure AI services and technologies - Implement governance and compliance for AI solutions |
| Topic 5: Implement Computer Vision Solutions | 15-20% | - Process video and generate insights - Read and process documents using Azure AI Document Intelligence - Analyze images using Azure AI Vision - Implement Azure AI Face service - Implement object detection and image classification |
| Topic 6: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Design document processing pipelines - Implement Azure AI Search solutions - Create custom skills for Azure AI Search - Implement semantic and vector search |





