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Last Updated: Jul 22, 2026
No. of Questions: 425 Questions & Answers with Testing Engine
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Candidates for AI-102 Exam are seeking to prove fundamental knowledge and skills in Designing and Implementing an Azure AI Solution domain. Before taking this exam, aspirants ought to have a solid fundamental information of the concepts shared in preparation guide as well as basic understanding of Azure administration, Azure development, and DevOpss would give an added edge.
This exam validates the ability to use the various services within the Microsoft Azure Artificial Intelligence (AI) portfolio.
It is suggested that professionals accustomed to the ideas and also the technologies represented here by taking relevant training courses. Candidates are expected to have some hands-on experience on bot services that use Language Understanding , bots with Azure Application Insights, creating a GPU, FPGA, or CPU-based solution, implementing AI workflow.
After passing this exam, candidates get a certificate from Microsoft that helps them to demonstrate their proficiency to their clients and employers.
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The price of the Microsoft Mobility and Devices Fundamentals exam is $165 USD, for more information related to exam price please visit to Microsoft Training website as prices of Microsoft exams fees get varied country wise.
These are following steps for registering 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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| Section | Weight | Objectives |
|---|---|---|
| Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Ingest and process structured/unstructured data |
| Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration - Understand agent use cases and types - Build agents with Microsoft Foundry Agent Service - Test, deploy, and optimize agents |
| Implement computer vision solutions | 10-15% | - Process and index video content - Build and deploy custom vision models - Integrate vision capabilities into applications - Analyze images and detect objects/features - Extract text and handwriting from images |
| Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Monitor, optimize, and secure AI solutions - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources - Plan solutions aligned with responsible AI principles |
| Implement natural language processing solutions | 15-20% | - Customize and deploy NLP models - Implement translation and summarization - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection |
| Implement generative AI solutions | 15-20% | - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Deploy and manage generative models - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers |
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