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

AI-102 Korean real exams

Exam Code: AI-102-KR

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

Updated: Aug 13, 2026

Q & A: 425 Questions and Answers

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About Microsoft AI-102 Korean Exam Collection

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

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How to book the AI-102: Designing and Implementing an Azure AI Solution Exam

These are following steps for registering the AI-102: Designing and Implementing an Azure AI Solution exam.

  • Step 1: Visit to Microsoft Learning and search for AI-102: Developing Solutions for Microsoft Azure.
  • Step 2: Sign up/Login to Pearson VUE account
  • Step 3: Select local centre based on your country, date, time and confirm with a payment method.

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Prerequisites

Before enrolling in the process of taking the AI-102 exams, candidates should be skilled in implementing Python and C#, using APIs and SDKs based on REST to create natural language processing solutions, computer vision solutions, and knowledge mining and communicative AI solutions based on Azure. In addition, such specialists should be knowledgeable of the elements that create the Azure AI portfolio as well as the data storage options. To add more, they should be able to implement AI principles appropriately.

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Microsoft AI-102 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Plan and manage an Azure AI solution20-25%- Monitor, optimize, and secure AI solutions
- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining
- Create and configure Azure AI resources
- Plan solutions aligned with responsible AI principles
- Select appropriate Microsoft Foundry Services
- Select suitable AI models
Topic 2: Implement an agentic solution5-10%- Develop multi-agent workflows and orchestration
- Understand agent use cases and types
- Test, deploy, and optimize agents
- Build agents with Microsoft Foundry Agent Service
Topic 3: Implement natural language processing solutions15-20%- Perform text analysis, sentiment detection, and language detection
- Customize and deploy NLP models
- Build conversational AI and chatbots
- Implement translation and summarization
Topic 4: Implement knowledge mining and information extraction solutions15-20%- Build knowledge bases and search indexes
- Implement intelligent search and retrieval
- Ingest and process structured/unstructured data
- Extract entities, relationships, and key phrases
Topic 5: Implement computer vision solutions10-15%- Analyze images and detect objects/features
- Process and index video content
- Extract text and handwriting from images
- Build and deploy custom vision models
- Integrate vision capabilities into applications
Topic 6: Implement generative AI solutions15-20%- Orchestrate multiple models and containers
- Implement model monitoring and feedback
- Apply prompt engineering and fine-tuning
- Deploy and manage generative models
- Integrate Azure OpenAI and other generative models

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