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Exam knowledge moves fast, and study material that stands still falls behind. ITCertMagic notifies you the moment the Microsoft Azure AI Fundamentals (AI-901日本語版) set changes, free for 365 days; after that, future updates cost half price. Your 2026 AI-901日本語 prep stays current by default.

Microsoft AI-901日本語 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals (AI-900) Exam
Exam Number:AI-900
Passing Score:700 (out of 1000)
Real Exam Qty:40-60
Certificate Validity Period:Does not expire (Fundamentals certification)
Exam Format:Case study (limited), Multiple response, Multiple choice, Drag and drop
Related Certifications:Microsoft Azure Fundamentals (AZ-900)
Microsoft Azure Data Fundamentals (DP-900)
Exam Duration:60 minutes
Exam Price:Approx. 99 USD (varies by region)
Available Languages:Spanish, French, Chinese (Simplified), Japanese, Portuguese (Brazil), German, Korean, Chinese (Traditional), English
Recommended Training:Microsoft Learn - AI-900 Learning Path
Azure AI Fundamentals Course
Exam Registration:Microsoft Certification Portal
Schedule exam via Pearson VUE
Sample Questions: DOWNLOAD DEMO
Exam Way:Online proctored exam or in-person test center
Pre Condition:No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/

Microsoft AI-901日本語 Exam Syllabus Topics:

SectionWeightObjectives
Describe features of generative AI workloads on Azure10-15%- Azure OpenAI and generative services
  • 1. Azure OpenAI Service capabilities
    • 2. Use cases: chatbots, content generation, summarization
      - Generative AI concepts
      • 1. Responsible use of generative AI
        • 2. Large language models (LLMs)
          • 3. Prompt engineering basics
            Describe fundamental principles of machine learning on Azure25-30%- Azure Machine Learning basics
            • 1. AutoML concepts
              • 2. Azure ML workspace components
                - Machine learning concepts
                • 1. Regression and classification
                  • 2. Supervised vs unsupervised learning
                    • 3. Training and evaluation concepts
                      Describe Artificial Intelligence workloads and considerations20-25%- Responsible AI principles
                      • 1. Inclusiveness
                        • 2. Fairness
                          • 3. Privacy and security
                            • 4. Reliability and safety
                              • 5. Transparency and accountability
                                - Identify features of common AI workloads
                                • 1. Document processing and extraction
                                  • 2. Conversational AI and chatbots
                                    • 3. Natural language processing use cases
                                      • 4. Computer vision use cases
                                        Describe features of natural language processing (NLP) workloads on Azure15-20%- Azure NLP services
                                        • 1. Azure AI Language
                                          • 2. Speech services (speech-to-text, text-to-speech)
                                            - Text analysis
                                            • 1. Key phrase extraction
                                              • 2. Sentiment analysis
                                                • 3. Language detection
                                                  Describe features of computer vision workloads on Azure15-20%- Image analysis
                                                  • 1. Optical character recognition (OCR)
                                                    • 2. Image classification
                                                      • 3. Object detection
                                                        - Azure AI Vision services
                                                        • 1. Azure AI Vision
                                                          • 2. Face detection and analysis (limited use cases)

                                                            Frequently Asked Questions: Microsoft AI-901日本語

                                                            60 minutes for 40-60 questions — tighter than it looks once hard items start eating minutes. Train the pace now: assign each question a time budget, flag the stubborn ones, and run full timed sessions in the ITCertMagic engine so test day feels like practice, not pressure.

                                                            Yes:

                                                            Courses build the base; measurement finishes the job. Once training ends, the AI-901日本語 practice questions from ITCertMagic show whether the knowledge actually holds under exam conditions.

                                                            5 domains make up the Microsoft Azure AI Fundamentals (AI-901日本語版) blueprint, led by Describe features of natural language processing (NLP) workloads on Azure (15-20%), Describe Artificial Intelligence workloads and considerations (20-25%), Describe fundamental principles of machine learning on Azure (25-30%). The weights show where the vendor concentrates its questions — that's where your hours should concentrate too. The complete outline above details every subtopic.

                                                            Delivery is automatic: successful payment emails the product to your mailbox within a minute — install on unlimited computers, and if 2 hours pass with nothing (check spam first), contact us. If you fail: sit the corresponding AI-901日本語 exam within 60 days of purchase, then submit a scanned enrollment slip and official Score Report PDF within 2 days of the exam — full refund, processed within 7 days. Excluded: exams taken within 3 days of purchase, name mismatches between candidate and payer, and free or expired products. Alternatively, exchange for two equal-value exam products free and keep your updates.

                                                            The AI-901日本語 exam is Microsoft's official certification exam for the Microsoft Azure AI Fundamentals credential, positioned at the Fundamentals level. It has never been considered easy — which is precisely why it impresses employers. It also relates to Microsoft Azure Data Fundamentals (DP-900), Microsoft Azure Fundamentals (AZ-900).

                                                            Through the vendor's official registration channels:

                                                            The exam is available Online proctored exam or in-person test center — pick the delivery method that suits you at booking.

                                                            The enrollment fee is Approx. 99 USD (varies by region) — not cheap — and the passing score is 700 (out of 1000). Since the fee applies in full to every attempt, each retake doubles down on the cost. The smarter sequence: drill the 127 practice questions from ITCertMagic first, book the exam second.

                                                            Yes — hesitating is normal, and the free demo exists for exactly that. Download it, get a feel for the Microsoft Azure AI Fundamentals (AI-901日本語版) questions, and decide with confidence. Purchases include 365 days of free updates, with new versions announced by email; after expiry, renew at 50% off.

                                                            No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. Rules like these do change — confirm the current criteria on the official exam page (official AI-901日本語 exam page) before registering.

                                                            Microsoft Azure AI Fundamentals (AI-901日本語版) Sample Questions:

                                                            以下の各記述について、正しい場合は「はい」を選択してください。そうでない場合は「いいえ」を選択してください。
                                                            注:接続選択1つにつき1ポイントが加算されます。

                                                            Reveal Solution  Discussion  0

                                                            Correct Answer:


                                                            Explanation:

                                                            Statement 1: Using Azure Speech in Foundry Tools for batch transcription requires live audio input from a microphone. = No Batch transcription is used to process stored audio files, not live microphone input. Live microphone input is used for real-time speech recognition scenarios.
                                                            Statement 2: Azure Speech in Foundry Tools can analyze video frames to detect and label objects while transcribing audio. = No Azure Speech is for speech capabilities such as speech recognition, speech synthesis, and speech translation.
                                                            Detecting and labeling objects in video frames is a computer vision/video analysis capability, not an Azure Speech capability.
                                                            Statement 3: Speech translation in Azure Speech in Foundry Tools can translate spoken audio into text in another language. = Yes Speech translation converts spoken input in one language into translated text in another language.

                                                            顧客への書面による通知を、電話システムで再生できる自然な音声に変換する必要があります。
                                                            Foundry ToolsのAzure Speech機能のうち、どれを使用すべきでしょうか?

                                                            • A. 音声翻訳
                                                            • B. 音声合成
                                                            • C. 音声認識
                                                            • D. 話者認識
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: B  🗳️

                                                            Explanation: Only visible for ITCertMagic members. You can sign-up / login (it's free).

                                                            ユーザーへの応答時に特定の役割と動作に従うAIエージェントをMicrosoft Foundryで作成する必要があります。
                                                            何を設定すればよいですか?

                                                            • A. システム手順
                                                            • B. 最大完了トークン
                                                            • C. 温度
                                                            • D. 1分あたりのトークン数(TPM)
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: A  🗳️

                                                            Explanation: Only visible for ITCertMagic members. You can sign-up / login (it's free).

                                                            文を正しく完成させる選択肢を選びなさい。

                                                            Reveal Solution  Discussion  0

                                                            Correct Answer:


                                                            Explanation:

                                                            When content is submitted to Azure Content Understanding in Foundry Tools, the analysis is asynchronous .
                                                            This means the service does not return results immediately within the same HTTP request. Instead, it uses the standard Azure long-running operation (LRO) pattern - you call begin_analyze() to submit the content, which immediately returns a poller object, and then call poller.result() to wait for processing to complete and retrieve the structured extraction results.
                                                            Why the other options are wrong:
                                                            * Synchronous is incorrect - the analysis pipeline involves multiple AI steps (OCR, speech transcription, schema mapping) that take time; a blocking synchronous call is not supported.
                                                            * Returned only as unstructured plain text is incorrect - Azure Content Understanding returns richly structured JSON output with named fields mapped to your defined schema, not plain unstructured text.
                                                            * Limited to OCR-only processing is incorrect - Content Understanding goes far beyond OCR; it supports document, audio, image, and video analyzers, and performs semantic field extraction using AI, not just character recognition.
                                                            This asynchronous design is consistent across all Azure AI services that perform complex, multi-step content processing.

                                                            ビジョン機能が有効になっているモデルのデプロイメントを含む Microsoft Foundry プロジェクトがあります。
                                                            Azure OpenAI Responses API を使用して、モデルにプロンプ​​トを送信します。
                                                            分析のために画像を提供する必要があります。
                                                            リクエストにはどのコンテンツ項目を含めるべきですか?

                                                            • A. 入力画像
                                                            • B. 出力画像
                                                            • C. 画像生成
                                                            • D. image_base64
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: A  🗳️

                                                            Explanation: Only visible for ITCertMagic members. You can sign-up / login (it's free).

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