Microsoft AI-102 Korean Value Pack
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- Exam Code: AI-102 Korean
- Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version)
- Updated: Jul 30, 2026
- Q & A: 425 Questions and Answers
- PDF Version + PC Test Engine + Online Test Engine
- Value Pack Total: $139.98 $89.99
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Microsoft AI-102 Korean dumps - Testing Engine
- Exam Code: AI-102 Korean
- Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version)
- Updated: Jul 30, 2026
- Q & A: 425 Questions and Answers
- Software Price: $69.99
- Testing Engine
About Microsoft AI-102 Korean Instant Exam Download
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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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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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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AI-102: Designing and Implementing an Azure AI Solution Exam Certified Professional salary
The average salary of a AI-102: Designing and Implementing an Azure AI Solution Exam Certified Expert in
- United State - 120,000 USD
- England - 90,532 POUND
- India - 20,00,327 INR
- Europe - 90,547 EURO
Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Build knowledge bases and search indexes - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data |
| Topic 2: Implement generative AI solutions | 15-20% | - Deploy and manage generative models - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Orchestrate multiple models and containers - Integrate Azure OpenAI and other generative models |
| Topic 3: Implement computer vision solutions | 10-15% | - Extract text and handwriting from images - Integrate vision capabilities into applications - Build and deploy custom vision models - Process and index video content - Analyze images and detect objects/features |
| Topic 4: Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Build agents with Microsoft Foundry Agent Service - Develop multi-agent workflows and orchestration - Understand agent use cases and types |
| Topic 5: Plan and manage an Azure AI solution | 20-25% | - Monitor, optimize, and secure AI solutions - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources - Select suitable AI models |
| Topic 6: Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection - Implement translation and summarization - Customize and deploy NLP models |
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