Microsoft AI-102日本語 dumps - in .pdf

AI-102日本語 pdf
  • Exam Code: AI-102日本語
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版)
  • Updated: Sep 04, 2026
  • Q & A: 425 Questions and Answers
  • PDF Price: $69.99

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  • Exam Code: AI-102日本語
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版)
  • Updated: Sep 04, 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日本語 dumps - Testing Engine

AI-102日本語 Testing Engine
  • Exam Code: AI-102日本語
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版)
  • Updated: Sep 04, 2026
  • Q & A: 425 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

About Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102日本語版) : AI-102日本語 Exam Questions

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Microsoft AI-102 Exam is an advanced-level certification that requires a deep understanding of AI technologies and their applications. Candidates are expected to have a strong grasp of AI concepts, programming languages, and data science principles. Passing AI-102J exam is a great way to demonstrate your expertise in designing and implementing AI solutions using Microsoft Azure, and it can help you advance your career in the field of AI and machine learning.

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.

Microsoft AI-102 certification exam is an essential certification for professionals who want to demonstrate their expertise in developing and implementing AI solutions in the Azure environment. By passing AI-102J exam, you will be able to showcase your skills and knowledge to potential employers and enhance your career prospects in the field of AI.

Microsoft AI-102日本語 Exam Syllabus Topics:

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

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