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For more info read reference:
microsoft learning site AI-102 Skills measured Publish a Machine Learning Experiment with Microsoft Azure Machine Learning Studio Process and translate speech with Azure Cognitive Speech Services
Designing and Implementing a Microsoft Azure AI Solution Exam Certification Details:
| Exam Name | Microsoft Certified - Azure AI Engineer Associate |
| 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 |
| Schedule Exam | Pearson VUE |
| Exam Code | AI-102 |
| Passing Score | 700 / 1000 |
| Duration | 130 mins |
| Exam Price | $165 (USD) |
Exam Details
Speaking of the exam details, the test will contain from 40 to 60 questions of various types which you need to complete within 100 or 120 minutes (depends on the inclusion of labs). To pass the exam you need to schedule the test on the PearsonVUE platform, pay an exam fee which is currently $165, and score at least 700 points or more out of 1000. And, of course, the knowledge of exam topics is a must.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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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
Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement generative AI solutions | 15-20% | - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Implement model monitoring and feedback - Deploy and manage generative models - Integrate Azure OpenAI and other generative models |
| Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Implement intelligent search and retrieval - Ingest and process structured/unstructured data - Build knowledge bases and search indexes |
| Plan and manage an Azure AI solution | 20-25% | - Monitor, optimize, and secure AI solutions - Select suitable AI models - Create and configure Azure AI resources - Plan solutions aligned with responsible AI principles - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Select appropriate Microsoft Foundry Services |
| Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots |
| Implement computer vision solutions | 10-15% | - Process and index video content - Build and deploy custom vision models - Integrate vision capabilities into applications - Extract text and handwriting from images - Analyze images and detect objects/features |
| Implement an agentic solution | 5-10% | - Understand agent use cases and types - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration - Build agents with Microsoft Foundry Agent Service |
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