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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement AI solutions by using Microsoft Foundry | 55-60% | - Work with models in Microsoft Foundry
|
| Topic 2: Identify AI concepts and responsibilities | 40-45% | - Describe principles of responsible AI
|
This format enables you to assess your AI-901 test preparation with a AI-901 practice exam. You can also customize your time and the kinds of questions of the Microsoft AI-901 Practice Test. This Microsoft Azure AI Fundamentals AI-901 practice test imitates the Microsoft AI-901 real exam pattern. Thus, it helps you kill Microsoft Azure AI Fundamentals exam anxiety.
NEW QUESTION # 106
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 107
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The Model catalog is used for comparing and deploying a wide range of models for generative AI development.
Microsoft states that the model catalog in Foundry portal is the hub for discovering and using a wide range of models to build generative AI applications. Microsoft training also states that the model catalog is used to compare models by benchmark metrics and deploy models to endpoints.
NEW QUESTION # 108
You are authoring a Conversational Language Understanding application to support a music festival.
You want users to be able to ask questions about scheduled shows, such as: "Which act is playing on the main stage?" The question "Which act is playing on the main stage?" is an example of which type of element?
Answer: A
NEW QUESTION # 109
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Speech
The correct answer is speech . The scenario specifically describes converting spoken customer requests into written text , which is a speech-to-text , or speech recognition, capability. Microsoft classifies speech as one of the common AI workloads in the current Azure AI Fundamentals study guide. The guide explicitly requires candidates to identify scenarios involving speech and to understand the capabilities of speech recognition and speech synthesis .
Microsoft Azure Speech in Foundry Tools provides speech-to-text functionality that converts audio streams into textual transcriptions. It supports real-time transcription, fast transcription, and batch transcription depending on the workload.
Key phrase extraction analyzes existing text to identify important words or concepts; it does not perform audio transcription. Text analysis covers operations such as sentiment analysis, entity recognition, summarization, and key phrase extraction after text already exists. Natural Language Understanding (NLU) interprets the meaning or intent of language, but the conversion from audio into written words itself is specifically a speech recognition workload .
Study Guide Reference: Identify AI concepts and capabilities # Identify AI workloads # Identify features and capabilities of speech recognition and speech synthesis.
NEW QUESTION # 110
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You are developing an application that sends images to the model.
You need to ensure that the model can analyze the images.
In which two formats can you provide the images? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: B,C
Explanation:
For vision-enabled Azure OpenAI / Microsoft Foundry model requests, image input can be provided by using an image URL or base64-encoded image data. Microsoft's Azure OpenAI REST API reference states that the image content part URL field can contain either a URL of the image or the base64 encoded image data. It also states that the Responses API input_image.image_url value can be a fully qualified URL or a base64 encoded image in a data URL.
NEW QUESTION # 111
......
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