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Last Updated: Oct 07, 2026
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Reference: https://www.microsoft.com/en-us/learning/exam-ai-100.aspx
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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| Section | Objectives |
|---|---|
| Topic 1: Design AI Solutions on Azure | - Select appropriate Azure AI services
|
| Topic 2: Implement Natural Language Processing (NLP) | - Language understanding solutions
|
| Topic 3: Implement Knowledge Mining and Search Solutions | - Azure Cognitive Search
|
| Topic 4: Responsible AI and Monitoring | - AI ethics and governance
|
| Topic 5: Implement Computer Vision Solutions | - Image analysis and processing
|
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