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

  • Exam Code: AI-102-KR
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version)
  • Updated: Jul 22, 2026
  • Q&As: 425 Questions and Answers

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Topics of AI-102: Designing and Implementing an Azure AI Solution Exam

Candidates should apprehend the examination topics before they begin of preparation. because it'll extremely facilitate them in touch the core. Our AI-102 exam dumps will include the following topics:

1. Analyze solution requirements (25-30%)

Recommend Cognitive Services APIs to meet business requirements

  • Select the processing architecture for a solution
  • Identify components and technologies required to connect service endpoints
  • Select the appropriate AI models and services
  • Select the appropriate data processing technologies
  • Identify automation requirements

Map security requirements to tools, technologies, and processes

  • Identify appropriate tools for a solution
  • Identify auditing requirements
  • Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
  • Identify which users and groups have access to information and interfaces

Select the software, services, and storage required to support a solution

  • Identify appropriate services and tools for a solution
  • Identify integration points with other Microsoft services
  • Identify storage required to store logging, bot state data, and Cognitive Services output

2. Design AI solutions (40-45%)

Design solutions that include one or more pipelines

  • Design pipelines that call Azure Machine Learning models
  • Design the integration point between multiple workflows and pipelines
  • Design pipelines that use AI apps
  • Select an AI solution that meet cost constraints
  • Design a strategy for ingest and egress data
  • Define an AI application workflow process

Design solutions that uses Cognitive Services

  • Design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs

Design solutions that implement the Bot Framework

  • Integrate bots and AI solutions
  • Design bots that integrate with channels
  • Integrate bots with Azure app services and Azure Application Insights
  • Design bot services that use Language Understanding (LUIS)

Design the compute infrastructure to support a solution

  • Identify whether to create a GPU, FPGA, or CPU-based solution
  • Select a compute solution that meets cost constraints
  • Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure

Design for data governance, compliance, integrity, and security

  • Define how users and applications will authenticate to AI services
  • Ensure that data adheres to compliance requirements defined by your organization
  • Design a content moderation strategy for data usage within an AI solution
  • Ensure appropriate governance of data
  • Design strategies to ensure that the solution meets data privacy regulations and industry standards

3. Implement and monitor AI solutions (25-30%)

Implement an AI workflow

  • Develop streaming solutions
  • Create solution endpoints
  • Define and construct interfaces for custom AI services
  • Develop AI pipelines
  • Manage the flow of data through the solution components
  • Implement data logging processes

Integrate AI services with solution components

  • Configure integration with Cognitive Services
  • Configure prerequisite components to allow connectivity to the Bot Framework
  • Configure prerequisite components and input datasets to allow the consumption of Cognitive Services APIs
  • Implement Azure Search in a solution

Monitor and evaluate the AI environment

  • Identify the differences between KPIs, reported metrics, and root causes of the differences
  • Recommend changes to an AI solution based on performance data
  • Identify the differences between expected and actual workflow throughput
  • Maintain an AI solution for continuous improvement
  • Monitor AI components for availability

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

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What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam

  • Language: English, Japanese, Chinese (Simplified), Korean.
  • Number of Questions: 40 to 60 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice.)
  • Passing Score: 700 / 1000
  • Type of Questions: This test format is multiple choice.
  • This is beta exam.
  • Length of Examination: 50 mins

The benefit of obtaining the AI-102: Designing and Implementing an Azure AI Solution Exam Certification

  • AI-102 credential delivers higher earning potential and increased promotion opportunities because it shows a good understanding of designing and implementing an Azure AI Solution
  • AI-102 Certification provides practical experience to candidates from all the aspects to be a proficient worker in the organization.
  • AI-102 Exam provide proven knowledge to use the tools to complete the task efficiently and cost effectively than the other non-certified professionals lack in doing so.
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  • AI-102 certified candidates will be confident and stand different from others as their skills are more trained than non-certified professionals.
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  • This certification will be judging your skills and knowledge on your understanding Designing and Implementing an Azure AI Solution concepts & Understanding of how to operate on Planning and Administering Designing and Implementing an Azure AI Solution .
  • AI-102 Certifications provide opportunities to get a job easily in which they are interested in instead of wasting years and ending without getting any experience.
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Microsoft AI-102 Korean Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement Natural Language Processing Solutions20-25%- Implement speech capabilities using Azure AI Speech
- Translate text and speech
- Analyze text using Azure AI Language
- Create conversational AI solutions with Azure AI Bot Service
- Build question answering solutions
Topic 2: Implement Generative AI Solutions10-15%- Integrate Azure OpenAI models into applications
- Apply responsible AI practices
- Use Azure OpenAI Service for generative AI
- Implement prompt engineering techniques
Topic 3: Implement Computer Vision Solutions15-20%- Analyze images using Azure AI Vision
- Implement Azure AI Face service
- Process video and generate insights
- Implement object detection and image classification
- Read and process documents using Azure AI Document Intelligence
Topic 4: Implement Decision Support Solutions10-15%- Design and implement decision automation
- Monitor and optimize decision support solutions
- Integrate Azure AI services into applications
Topic 5: Implement Knowledge Mining and Document Intelligence Solutions15-20%- Implement Azure AI Search solutions
- Implement semantic and vector search
- Create custom skills for Azure AI Search
- Design document processing pipelines
Topic 6: Plan and Manage an Azure AI Solution15-20%- Implement governance and compliance for AI solutions
- Manage AI costs and resource allocation
- Select appropriate Azure AI services and technologies
- Plan and configure secure AI solutions

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