Learn with Microsoft : AI-102日本語 training material for 100% pass
Last Updated: Aug 11, 2026
No. of Questions: 425 Questions & Answers with Testing Engine
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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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Prep Options to Choose
The preparation process for the exam is a vital step on your way of passing the test, that’s why you need to find the most actual and reliable resources. Microsoft offers two options for you to choose from online free training or instructor-led, which is a paid one. For example, the free training represents a collection of learning paths each of which contains the different number of modules, from one to five. Thus, you can choose which ones to follow: Prepare for AI engineering (1 module), Process and Translate Speech with Azure Cognitive Speech Services (2 modules), Create computer vision solutions with Azure Cognitive Services (3 modules), to name a few. The paid course is known to be Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution and lasts for 4 days. It is intended for software developers interested in developing skills to build AI infused apps that use Azure Cognitive Search and Services, and Microsoft Bot Framework.
In addition, you can check the Amazon website to find the books on the topics included in the exam to ace it from the first attempt. Only after the successful passing the AI-102 exam you will earn the Microsoft Certified: Azure AI Engineer Associate certification. So, good luck!
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Designing and Implementing a Microsoft Azure AI Solution Exam Certification Details:
| Exam Price | $165 (USD) |
| Schedule Exam | Pearson VUE |
| Books / Training | Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution |
| Passing Score | 700 / 1000 |
| Number of Questions | 40-60 |
| Duration | 130 mins |
| Sample Questions | Designing and Implementing a Microsoft Azure AI Solution Sample Questions |
| Exam Name | Microsoft Certified - Azure AI Engineer Associate |
| Exam Code | AI-102 |
Skills measured
- Implement conversational AI solutions (15-20%)
- Implement knowledge mining solutions (15-20%)
- Implement Computer Vision solutions (20-25%)
- Plan and manage an Azure Cognitive Services solution (15-20%)
- Implement natural language processing solutions (20-25%)
Microsoft AI-102日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Integrate vision capabilities into applications - Process and index video content - Extract text and handwriting from images - Build and deploy custom vision models - Analyze images and detect objects/features |
| Topic 2: Implement knowledge mining and information extraction solutions | 15-20% | - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Implement intelligent search and retrieval - Ingest and process structured/unstructured data |
| Topic 3: Implement generative AI solutions | 15-20% | - Implement model monitoring and feedback - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers - Apply prompt engineering and fine-tuning - Deploy and manage generative models |
| Topic 4: Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Customize and deploy NLP models - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection |
| Topic 5: 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 6: Plan and manage an Azure AI solution | 20-25% | - 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 suitable AI models - Select appropriate Microsoft Foundry Services - Monitor, optimize, and secure AI solutions |
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