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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Describe features of Generative AI workloads on Azure | 15-20% | - Identify responsible AI considerations for generative AI - Describe Azure OpenAI Service capabilities - Describe generative AI concepts |
| Topic 2: Describe fundamental principles of machine learning on Azure | 30-35% | - Describe Azure Machine Learning capabilities - Identify common machine learning tasks - Describe features of no-code automated ML - Describe core machine learning concepts |
| Topic 3: Describe features of Natural Language Processing (NLP) workloads on Azure | 15-20% | - Identify common NLP tasks - Identify Azure AI services for NLP - Describe Azure capabilities for NLP |
| Topic 4: Describe AI workloads and considerations | 15-20% | - Identify features of common AI workloads - Identify guiding principles for responsible AI |
| Topic 5: Describe features of computer vision workloads on Azure | 15-20% | - Identify Azure AI services for computer vision - Describe Azure capabilities for computer vision - Identify common computer vision tasks |
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NEW QUESTION # 180
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The Azure OpenAI Service provides access to advanced Generative Pre-trained Transformer (GPT) models developed by OpenAI, such as GPT-3, GPT-3.5, and GPT-4. These models are capable of performing a wide range of natural language processing (NLP) and generative AI tasks - including text completion, summarization, translation, question answering, content creation, and code generation.
According to the Microsoft Azure AI Fundamentals (AI-900) study guide and Microsoft Learn documentation for Azure OpenAI, this managed service allows developers to deploy and integrate GPT-based models within their own applications using REST APIs or the Azure SDK. The service handles scalability, performance, and infrastructure automatically, meaning users do not need to manage servers or computational resources manually.
Option review:
* Supports the deployment of GPT-based models - # Correct. Azure OpenAI is specifically designed for deploying and operationalizing GPT models and similar transformer-based architectures.
* Provides capabilities exclusively for vision-related tasks - # Incorrect. Vision tasks (like image classification or object detection) are part of Azure AI Vision.
* Provides capabilities exclusively for speech-related tasks - # Incorrect. Speech processing (speech-to- text, text-to-speech, translation) belongs to Azure AI Speech Services, not Azure OpenAI.
* Requires manual infrastructure management for scalability - # Incorrect. Azure OpenAI is a fully managed service; scalability and performance are handled automatically by Azure.
Therefore, the correct completion of the sentence is:
"Azure OpenAI Service supports the deployment of GPT-based models."
NEW QUESTION # 181
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Yes
Azure Machine Learning designer lets you visually connect datasets and modules on an interactive canvas to create machine learning models.
Box 2: Yes
With the designer you can connect the modules to create a pipeline draft.
As you edit a pipeline in the designer, your progress is saved as a pipeline draft.
Box 3: No
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer
NEW QUESTION # 182
In which two scenarios can you use a speech synthesis solution? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: C,D
Explanation:
According to the Microsoft Learn module "Explore speech capabilities of Azure AI" and the AI-900 Official Study Guide, speech synthesis (also known as text-to-speech) is the process of converting written text into spoken audio output. Azure's Speech service provides this functionality, allowing applications to produce human-like voices dynamically.
Let's evaluate each scenario:
* A. Automated voice that reads back a credit card number entered into a telephone keypad # YesThis is a classic text-to-speech (TTS) use case. The application converts numeric or textual input (such as a credit card number) into audio output that the caller hears. Azure Speech service can handle such voice responses in automated phone systems or IVR (Interactive Voice Response) setups.
* B. Generating live captions for a news broadcast # NoThis is a speech-to-text scenario (speech recognition), not speech synthesis. It involves converting audio speech into written text.
* C. Extracting key phrases from an audio recording of a meeting # NoThis involves speech-to-text followed by text analytics, not speech synthesis.
* D. An AI character in a computer game that speaks audibly to a player # YesThis is a direct example of speech synthesis, where the character's dialog text is converted into realistic spoken output for immersive interaction.
Therefore, based on Microsoft's AI-900 curriculum, speech synthesis is used in applications that convert text into audible speech, such as automated voice systems or interactive digital characters.
NEW QUESTION # 183
What are two tasks that can be performed by using computer vision? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,B
Explanation:
Section: Describe features of computer vision workloads on Azure
Explanation/Reference:
Explanation:
B: Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.
E: Computer Vision includes Optical Character Recognition (OCR) capabilities. You can use the new Read API to extract printed and handwritten text from images and documents. It uses the latest models and works with text on a variety of surfaces and backgrounds. These include receipts, posters, business cards, letters, and whiteboards. The two OCR APIs support extracting printed text in several languages.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview
NEW QUESTION # 184
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/architecture/reference-architectures/ai/conversational-bot
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-webchat-overview?view=azure-bot-service-4.0
NEW QUESTION # 185
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