Microsoft Designing and Implementing an Azure AI Solution (AI-100日本語版) : AI-100日本語

  • Exam Code: AI-100日本語
  • Exam Name: Designing and Implementing an Azure AI Solution (AI-100日本語版)
  • Updated: Aug 25, 2026     Q & A: 163 Questions and Answers

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Exam AI-100: Designing and Implementing an Azure AI Solution

THIS EXAM RETIRED ON JUNE 30, 2021. A replacement exam, AI-102, is available. For more information, visit the AI-102 exam details page.

Candidates for this exam should have subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.

Responsibilities for an Azure AI Engineer include analyzing requirements for AI solutions, recommending the appropriate tools and technologies, and designing and implementing AI solutions that meet scalability and performance requirements.

Azure AI Engineers translate the vision from solution architects and work with data scientists, data engineers, IoT specialists, and software developers to build complete end-to-end solutions.

A candidate for this exam should have knowledge and experience designing and implementing AI apps and agents that use Microsoft Azure Cognitive Services, Azure Bot Service, Azure Cognitive Search, and data storage in Azure. In addition, a candidate should be able to recommend solutions that use open source technologies, understand the components that make up the Azure AI portfolio and the available data storage options, and understand when a custom API should be developed to meet specific requirements.

Part of the requirements for: none

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Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx

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Microsoft AI-100日本語 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design AI Solutions40-45%- Design conversational AI solutions
  • 1. Conversational workflows
  • 2. Knowledge integration
  • 3. Bot architecture
- Design natural language processing solutions
  • 1. Language understanding solutions
  • 2. Translation solutions
  • 3. Text analytics solutions
- Design computer vision solutions
  • 1. Object detection solutions
  • 2. Image classification solutions
  • 3. OCR and text extraction solutions
Topic 2: Implement and Monitor AI Solutions25-30%- Monitor and optimize solutions
  • 1. Model and service optimization
  • 2. Logging and diagnostics
  • 3. Performance monitoring
- Implement AI services
  • 1. Configure security and authentication
  • 2. Deploy Azure Cognitive Services
  • 3. Integrate AI APIs and SDKs
Topic 3: Analyze Solution Requirements25-30%- Analyze AI workloads
  • 1. Identify business requirements
  • 2. Select appropriate Azure AI services
  • 3. Determine data requirements

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