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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 NameMicrosoft Certified - Azure AI Engineer Associate
Books / TrainingCourse AI-102T00: Designing and Implementing a Microsoft Azure AI Solution
Sample QuestionsDesigning and Implementing a Microsoft Azure AI Solution Sample Questions
Number of Questions40-60
Schedule ExamPearson VUE
Exam CodeAI-102
Passing Score700 / 1000
Duration130 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

Download exam skills outline

Microsoft AI-102日本語 Exam Syllabus Topics:

SectionWeightObjectives
Implement generative AI solutions15-20%- 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 solutions15-20%- 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 solution20-25%- 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 solutions15-20%- 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 solutions10-15%- 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 solution5-10%- 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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