Microsoft AI-900日本語 : Microsoft Azure AI Fundamentals (AI-900日本語版)

  • Exam Code: AI-900日本語
  • Exam Name: Microsoft Azure AI Fundamentals (AI-900日本語版)
  • Updated: Sep 21, 2026   Q&As: 336 Questions and Answers

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About Microsoft AI-900日本語 Exam

What is Microsoft AI-900 Exam

Microsoft AI-900 exam is designed for Microsoft partners who are certified by Microsoft to integrate Microsoft Azure Intelligent Solutions into their own products and solutions. Explore the objectives of the AI-900 exam. Protection of the Azure platform and its components. Reference architecture for Azure solutions. Implementation, configuration, and management of Azure services. Request, manage and monitor Azure services. Troubleshooting of Azure services. Microsoft AI-900 exam dumps exam tests Questions are designed to identify the exam takers level of competence in the functions, features, and services of Azure. Depth and Breadth of Knowledge. Processes and practices for developing and deploying intelligent solutions. Hope you like this article. Associate in IT, Eugene is an expert in the fields of software applications and internet technologies. Paying attention to the latest technology is the reason Eugene uses his knowledge of high-end computer systems, application programming, and data entry.

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About Azure AI Fundamentals Certification and Who It Is Intended for

The Microsoft Certified: Azure AI Fundamentals qualification authenticates the learner's understanding and skills in AI & ML concepts along with associated Azure services. In particular, the individual with this certification is competent in demonstrating their understanding of various workloads related to those terms along with their implementation in Azure cloud computing services. In addition, this certification is an excellent way to get a step ahead in the preparation for other role-based Azure certificates as well as showcasing one's skill in the fundamentals of ML as well as AI. All in all, the Azure AI Fundamentals validation form Microsoft is for beginners and thus, doesn't require any technical knowledge and expertise like, for example, engineering for software. However, some understanding of programming will help you a lot to easily nail test AI-900.

Test AI-900 Scope of Knowledge

Overall, AI-900 exam tests the applicant's understanding of AI and ML through various topics categorized into 5 domains:

  • Workloads for computer vision based on Azure and features (15-20%)

    This segment of the official test is all about workloads for computer vision in relation to Azure services. To get through this part, one must have a general grasp of the various common forms of computer vision solutions that include image classification, object detection, semantic segmentation, recognition for the optical character, and facial detection. The applicants are also required to have an understanding of the diverse methods including services used in Azure for activities that utilize computer vision. Such methods and services include the vision for computers, vision for custom, services for face vision, and at last, the recognizer of the form.

  • Conversational workloads for AI based on Azure and features (15-20%)

    The fifth and final domain for such an exam tests the entrant's understanding of conversational AI workloads. This requires the comprehension of facets as well as cases for the usage of conversational traits for AI which includes web chatbots, voice menus for the telephone, and digital assistants used for personal purposes. The applicant also needs to know how to check various Azure services related to conversational AI. Additionally, they should have a firm understanding of the QnA Maker Service & Bot service. Finally, it is essential for candidates to know and be able to describe the common characteristics of conversational artificial intelligence solutions.

  • Workloads for Natural Language Processing (NLP) related to Azure (15-20%)

    The fourth portion of AI-900 exam deals with Natural Language Processing or NLP workloads in Azure. To get a passing score, the entrant must have a firm grasp on the facets and usage of diverse NLP scenarios for workloads which comprise the extraction of the key phrase, the recognition of entities, the analysis of sentiments, modeling for languages, the recognition of speech, and translation traits. The applicants are also required to know about different techniques as well as services of Azure used for various NLP workloads. They are required to be capable of identifying diverse abilities of various services such as text analysis, LUIS, speech, and translator text.

  • AI workloads and considerations (15-20%)

    The first topic of the final exam deals with AI workloads that are usually common. It includes candidates' understating various types of workloads such as predicting forecasting traits, the detection of anomalies, vision for computer systems, NLP, and conversational AI workloads. The examinees are also required to have a thorough understanding of the principles of AI that possess responsibility traits. It means that the candidate needs to be well aware of all the considerations for different solutions for AI which include fairness, reliability, security, privacy, inclusiveness, transparency facets, and finally, functions for accountability.

  • Fundamental principles of machine learning on Azure (30-35%)

    In the second section, the applicant's knowledge of fundamental principles of machine learning in relation to Azure cloud computing services will be tested. This requires the applicant to have a clear comprehension of all the common types of various scenarios for ML that include classification, regression, and clustering. It is also essential to have a thorough understanding of the core MI concepts such as labels & features in datasets, dataset training that go with the validation process, etc. The entrant must as well as be capable of identifying the core task required in developing an ML solution. So, understanding the ingestion and preparation of data chunks, selection and engineering of various features, evaluation procedure as well as training for models, and deployment & management of those models will be vital. Finally, this portion of AI-900 exam includes concepts of ML automated user interface that are ML Wizard UI and Azure ML designer.

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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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Microsoft AI-900日本語 Exam Syllabus Topics:
SectionWeightObjectives
Fundamentals of machine learning on Azure25-30%- Core machine learning concepts
  • 1. Supervised vs unsupervised learning
    • 2. Training and validation concepts
      Features of computer vision workloads on Azure15-20%- Computer vision solutions
      • 1. Object detection
        • 2. Image classification
          • 3. OCR and image analysis
            Features of natural language processing (NLP) workloads on Azure30-35%- Text analytics and language understanding
            • 1. Sentiment analysis
              • 2. Key phrase extraction
                • 3. Language modeling and translation
                  Describe AI workloads and considerations20-25%- Fundamentals of artificial intelligence concepts
                  • 1. Common AI workloads
                    • 2. Responsible AI principles

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