How to Register For Exam AI-900: Microsoft Azure AI Fundamentals?
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
Certification Path
The Azure AI Fundamentals certification might not be a prerequisite for any other certification levels, however, it can still be used to prepare for multiple Azure-related qualifications including the Microsoft Certified: Azure Data Scientist Associate and the Microsoft Certified: Azure AI Engineer Associate.
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Describing AI-900 Exam Facts and Topics
In general, AI-900 is a computer-based exam that’s available in English, Chinese, Japanese, Spanish, French, German, and Korean languages. It costs $99 for every attempt and can be scheduled with Certiport or Pearson VUE. Recently, the AI-900 exam curriculum has been updated to reflect the following skills as contained in the official study guide:
- Describing fundamental principles of machine learning on Azure (30-35%);
- Defining features of conversational AI workloads on Azure (15-20%).
- Detailing Artificial Intelligence considerations and workloads (15-20%);
- Explaining features of computer vision workloads on Azure (15-20%);
- Designing features of NLP (Natural Language Processing) workloads on Azure (15-20%);
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Microsoft AI-900日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Fundamental principles of machine learning on Azure | 15–20% | - Describe core concepts of machine learning - Describe machine learning pipelines - Describe automated machine learning - Describe capabilities of Azure Machine Learning |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Speech - Describe capabilities of Azure Language - Identify types of NLP solutions - Describe capabilities of Azure Translator |
| Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe responsible AI principles - Describe considerations for developing AI solutions |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Custom Vision |
| Features of generative AI workloads on Azure | 20–25% | - Describe generative AI concepts - Describe responsible AI practices for generative AI - Describe capabilities of Azure OpenAI Service - Describe use cases for generative AI |
Microsoft Azure AI Fundamentals (AI-900日本語版) Sample Questions:
Question #1
Azure OpenAI GPT-3.5 モデルを使用するチャット ソリューションからの応答で、より多様な範囲のトークンを生成するには、どのパラメーターを構成する必要がありますか?
A. 過去のメッセージが含まれています
B. シーケンスを停止
C. 最大応答
D. プレゼンスペナルティ
Question #2
次の各ステートメントについて、ステートメントがtrueの場合は、[はい]を選択します。それ以外の場合は、[いいえ]を選択します。
注:正しい選択はそれぞれ1ポイントの価値があります。
Question #3
機械学習のタイプを適切なシナリオに一致させます。
答えるには、適切な機械学習タイプを左側の列から右側のシナリオにドラッグします。
各機械学習タイプは、1回使用することも、複数回使用することも、まったく使用しないこともできます。
注:正しい選択はそれぞれ1ポイントの価値があります。
Question #4
許可なく取得したデータを使用して作成された自然言語処理 (NIP) モデルがあります。
これは Microsoft の責任ある Al のどの原則に違反しますか?
A. 透明度
B. 信頼性と安全性
C. プライバシーとセキュリティ
D. 包括性
Question #5
電子メール、Microsoft Teams、Webチャットなどの複数のチャネルを介してユーザーと通信する会話型AIソリューションを開発しています。
どのサービスを使うべきですか?
A. フォーム認識機能
B. Azureボットサービス
C. テキスト分析
D. Translator
Solutions:
| Question #1 Correct Answer: D | Question #2 Correct Answer: Only visible for members | Question #3 Correct Answer: Only visible for members | Question #4 Correct Answer: C | Question #5 Correct Answer: B |


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