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| Section | Weight | Objectives |
|---|---|---|
| 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 |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Identify types of NLP solutions - Describe capabilities of Azure Translator - Describe capabilities of Azure Speech - Describe capabilities of Azure Language |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Describe capabilities of Azure Face - Identify types of computer vision solutions - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision |
| Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe considerations for developing AI solutions - Describe responsible AI principles |
| Fundamental principles of machine learning on Azure | 15–20% | - Describe automated machine learning - Describe machine learning pipelines - Describe core concepts of machine learning - Describe capabilities of Azure Machine Learning |
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NEW QUESTION # 221
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-label-data
NEW QUESTION # 222
Match the principles of responsible AI to appropriate requirements.
To answer, drag the appropriate principles from the column on the left to its requirement on the right. Each principle may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION # 223
You need to build an app that will read recipe instructions aloud to support users who have reduced vision.
Which version service should you use?
Answer: D
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Identify features of speech capabilities in Azure Cognitive Services", the Azure Speech service provides functionality for converting text to spoken words (speech synthesis) and speech to text (speech recognition).
In this scenario, the app must read recipe instructions aloud to assist users with visual impairments. This task is achieved through speech synthesis, also known as text-to-speech (TTS). The Azure Speech service uses advanced neural network models to generate natural-sounding voices in many languages and accents, making it ideal for accessibility scenarios such as screen readers, virtual assistants, and educational tools.
Microsoft Learn defines Speech service as a unified offering that includes:
* Speech-to-text (speech recognition): Converts spoken words into text.
* Text-to-speech (speech synthesis): Converts written text into natural-sounding audio output.
* Speech translation: Translates spoken language into another language in real time.
* Speaker recognition: Identifies or verifies a person based on their voice.
The other options do not fit the requirements:
* A. Text Analytics - Performs text-based natural language analysis such as sentiment, key phrase extraction, and entity recognition, but it cannot produce audio output.
* B. Translator Text - Translates text between languages but does not generate speech output.
* D. Language Understanding (LUIS) - Interprets user intent from text or speech for conversational bots but does not read text aloud.
Therefore, based on the AI-900 curriculum and Microsoft Learn documentation, the correct service for converting recipe text to spoken audio is the Azure Speech service.
# Final answer: C. Speech
Reference:Microsoft Learn - "What is the Speech service?" (Azure Cognitive Services > Speech)
NEW QUESTION # 224
Which action can be performed by using the Azure Al Vision service?
Answer: D
NEW QUESTION # 225
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation:
According to Microsoft's Responsible AI principles, one of the key guiding values is Reliability and Safety, which ensures that AI systems operate consistently, accurately, and safely under all intended conditions. The AI-900 study materials and Microsoft Learn modules explain that an AI system must be trustworthy and dependable, meaning it should not produce results when the input data is incomplete, corrupted, or significantly outside the expected range.
In the given scenario, the AI system avoids providing predictions when important fields contain unusual or missing values. This behavior demonstrates reliability and safety because it prevents the system from making unreliable or potentially harmful decisions based on bad or insufficient data. Microsoft emphasizes that AI systems must undergo extensive validation, testing, and monitoring to ensure stable performance and predictable outcomes, even when data conditions vary.
The other options do not fit this scenario:
* Inclusiveness ensures that AI systems are accessible to and usable by all people, regardless of abilities or backgrounds.
* Privacy and Security focuses on protecting user data and ensuring it is used responsibly.
* Transparency involves making AI decisions explainable and understandable to humans.
Only Reliability and Safety directly address the concept of an AI system refusing to act or returning an error when it cannot make a trustworthy prediction. This principle helps prevent inaccurate or unsafe outputs, maintaining confidence in the system's integrity.
Therefore, ensuring an AI system does not produce predictions when input data is incomplete or unusual aligns directly with Microsoft's Reliability and Safety principle for responsible AI.
NEW QUESTION # 226
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