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Exam AI-100: Designing and Implementing an Azure AI Solution
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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What is the duration of the AI-100 Exam
- Number of Questions: 45-55
- Passing Score: 700/1000
- Format: Multiple choices, multiple answers
- Length of Examination: 120 minutes
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Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx
Microsoft AI-100日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Design AI Solutions | 40-45% | - Select appropriate Azure Cognitive Services - Integrate open-source and custom AI components - Design conversational AI and bot solutions - Design computer vision solutions - Design knowledge mining and search solutions - Design natural language processing solutions |
| Analyze Solution Requirements | 25-30% | - Evaluate data storage and processing options - Define solution performance and scalability criteria - Identify business and technical requirements - Assess security, compliance, and governance needs |
| Implement and Monitor AI Solutions | 25-30% | - Integrate AI models and services into applications - Deploy AI solutions to Azure infrastructure - Monitor performance, usage, and health - Maintain and update AI solutions - Configure security and access controls |
