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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe capabilities of Azure OpenAI Service - Describe responsible AI practices for generative AI - Describe generative AI concepts |
| Topic 2: Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe considerations for developing AI solutions - Describe responsible AI principles |
| Topic 3: Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe core concepts of machine learning - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning |
| Topic 4: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Custom Vision - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Computer Vision |
| Topic 5: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Language - Describe capabilities of Azure Speech - Describe capabilities of Azure Translator - Identify types of NLP solutions |
The goal of a Microsoft AI-900 mock exam is to test exam readiness. Itexamguide's online Microsoft Azure AI Fundamentals AI-900 practice test can be accessed online through all major browsers such as Chrome, Firefox, Safari, and Edge. You can also download and install the offline version of Microsoft Azure AI Fundamentals AI-900 Practice Exam software on Windows-based PCs only. You can prepare for the Microsoft Azure AI Fundamentals exam without an internet connection using the offline version of the mock exam.
NEW QUESTION # 34
Which statement is an example of a Microsoft responsible AI principle?
Answer: D
Explanation:
The correct answer is C. AI systems must be understandable, which corresponds to the Transparency principle of Microsoft's Responsible AI framework.
According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Identify guiding principles for responsible AI", Microsoft defines six key principles for responsible AI:
* Fairness - AI systems should treat everyone equitably.
* Reliability and safety - AI should function as intended, even under unexpected conditions.
* Privacy and security - AI must protect personal and business data.
* Inclusiveness - AI should empower everyone and engage diverse users.
* Transparency - AI systems should be understandable.
* Accountability - People should be accountable for AI systems.
The statement "AI systems must be understandable" aligns directly with the Transparency principle, ensuring that AI decisions and behaviors can be explained and interpreted by developers, users, and stakeholders.
Microsoft emphasizes that transparent AI builds trust, allows debugging, and ensures ethical usage.
Other options are incorrect:
* A. Use only publicly available data - Not a principle of Responsible AI.
* B. Protect the interests of the company - Focused on business goals, not ethical AI.
* D. Keep personal details public - Violates the Privacy and Security principle.
# Final Answer (Q179): C. AI systems must be understandable.
NEW QUESTION # 35
Match the types of computer vision to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection
NEW QUESTION # 36
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connect-and-manage-intelligent-bots
NEW QUESTION # 37
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
NEW QUESTION # 38
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing
NEW QUESTION # 39
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