Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version) : AI-102 Korean

AI-102 Korean pass collection

Exam Code: AI-102-KR

Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version)

Updated: Oct 11, 2026

Q & A: 425 Questions and Answers

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About Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version) : AI-102 Korean Exam

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How much AI-102: Designing and Implementing an Azure AI Solution Exam Cost

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.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102

Who should take the AI-102: Designing and Implementing an Azure AI Solution Exam

The AI-102 Exam certification is an internationally-recognized certification which help to have validation for Azure AI Solution Architects who have ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.

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The average salary of a AI-102: Designing and Implementing an Azure AI Solution Exam Certified Expert in

  • India - 20,00,327 INR
  • England - 90,532 POUND
  • Europe - 90,547 EURO
  • United State - 120,000 USD

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Microsoft AI-102 Korean Exam Syllabus Topics:

SectionWeightObjectives
Implement an agentic solution5-10%- Build agents with Microsoft Foundry Agent Service
- Test, deploy, and optimize agents
- Understand agent use cases and types
- Develop multi-agent workflows and orchestration
Implement knowledge mining and information extraction solutions15-20%- Ingest and process structured/unstructured data
- Build knowledge bases and search indexes
- Extract entities, relationships, and key phrases
- Implement intelligent search and retrieval
Implement generative AI solutions15-20%- Apply prompt engineering and fine-tuning
- Integrate Azure OpenAI and other generative models
- Implement model monitoring and feedback
- Orchestrate multiple models and containers
- Deploy and manage generative models
Implement computer vision solutions10-15%- Integrate vision capabilities into applications
- Extract text and handwriting from images
- Build and deploy custom vision models
- Analyze images and detect objects/features
- Process and index video content
Implement natural language processing solutions15-20%- Implement translation and summarization
- Customize and deploy NLP models
- Build conversational AI and chatbots
- Perform text analysis, sentiment detection, and language detection
Plan and manage an Azure AI solution20-25%- Select appropriate Microsoft Foundry Services
- Select suitable AI models
- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
- Monitor, optimize, and secure AI solutions
- Create and configure Azure AI resources
- Plan solutions aligned with responsible AI principles

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