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AI-102 Korean
  • Exam Code: AI-102
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version)
  • Updated: Jul 25, 2026
  • No. of Questions: 425 Questions and Answers
  • Download Limit: Unlimited
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AI-102: Designing and Implementing an Azure AI Solution is a privileged achievement one could be graced with. But adverse to general notion certifying with Microsoft is not that challenging if the candidates have proper preparation material to pass the AI-102: Designing and Implementing an Azure AI Solution exam with good grades. Questions answers and clarifications which are designed in form of Lead2Passed exam dumps make sure to cover entire course content. Lead2Passed have a brilliant AI-102: Designing and Implementing an Azure AI Solution exam dumps with most recent and important questions and answers in PDF files. Lead2Passed is sure about the exactness and legitimacy of AI-102: Designing and Implementing an Azure AI Solution exam dumps and in this manner. Candidates can easily pass the AI-102: Designing and Implementing an Azure AI Solution exam with genuine AI-102: Designing and Implementing an Azure AI Solution exam dumps and get MICROSOFT certification. These exam dumps are viewed as the best source to understand the AI-102: Designing and Implementing an Azure AI Solution well by simply pursuing examples questions and answers. If candidate completes practice the exam with certification AI-102 exam dumps along with self-assessment to get the proper idea on MICROSOFT accreditation and to ace the certification exam.

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

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

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Topics Covered

Exam AI-102 contains five topics each of which is intended to check specific skills.

1. Plan and Manage an Azure Cognitive Services Solution

This topic implies your ability to choose the suitable Cognitive Services resource, create it, plan and design security for a Cognitive Services solution, and apply Cognitive Services containers. This means that you should be competent in selecting the appropriate cognitive service for solutions that refer to language analysis, speech, decision support, and vision. You also should possess skills to operate costs of Cognitive Services, create a Cognitive Services resource, and monitor a cognitive service. This part also checks how well you can operate Cognitive Services account keys, and protect Cognitive Services. Your knowledge of using Face API, Computer Vision, Speech, Text Analysis, and ability to integrate Cognitive Services Containers in Microsoft Azure will also be assessed.

2. Implement Computer Vision Solutions

The second topic is designed to check your skills in using the Computer Vision API to get image descriptions, define landmarks, find brands, edit content in images, and create thumbnails. In this part, you are expected to be able to detect faces and recognize them in images, analyze facial features, and match similar faces with the help of the Face API. Being competent in utilizing the Custom Vision service, you should demonstrate your skills in applying image classification and implementing an object detection solution. Besides, your ability to analyze video by implementing Azure Video Analyzer for Media will be measured.

3. Implement Natural Language Processing Solutions

In the third topic, candidates are required to show their skills in analyzing text by utilizing the Text Analytics service, control speech by implementing the Speech service, translate the text with the help of the Translator service. This domain also checks your proficiency in creating and optimizing an initial language model by utilizing LUIS, and finally, managing it.

4. Implement Knowledge Mining Solutions

In this domain, you will be required to have expertise related to applying a Cognitive Search solution, which implies creating data sources, identifying an index, running an indexer, and using synonyms. This topic also aims to evaluate your ability to apply an enrichment pipeline, use a knowledge store, operate a Cognitive Search solution and indexing.

5. Implement Conversational AI Solutions

This domain will evaluate your capacity in utilizing QnA Maker to make a knowledge base, creating and implementing conversation flow, creating a bot by utilizing either the Bot Framework Composer or the Bot Framework SDK. Finally, you will need to demonstrate your skills in integrating Cognitive Services into a bot.

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Microsoft AI-102 Korean Exam Syllabus Topics:

SectionWeightObjectives
Plan and manage an Azure AI solution20-25%- Select appropriate Microsoft Foundry Services
- Monitor, optimize, and secure AI solutions
- 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 suitable AI models
Implement generative AI solutions15-20%- Apply prompt engineering and fine-tuning
- Deploy and manage generative models
- Orchestrate multiple models and containers
- Integrate Azure OpenAI and other generative models
- Implement model monitoring and feedback
Implement natural language processing solutions15-20%- Perform text analysis, sentiment detection, and language detection
- Build conversational AI and chatbots
- Implement translation and summarization
- Customize and deploy NLP models
Implement computer vision solutions10-15%- Integrate vision capabilities into applications
- Build and deploy custom vision models
- Process and index video content
- 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
- Build agents with Microsoft Foundry Agent Service
- Develop multi-agent workflows and orchestration
Implement knowledge mining and information extraction solutions15-20%- Ingest and process structured/unstructured data
- Implement intelligent search and retrieval
- Build knowledge bases and search indexes
- Extract entities, relationships, and key phrases

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