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Microsoft AI-901 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.
Topic 2
  • Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.

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Microsoft Azure AI Fundamentals Sample Questions (Q86-Q91):

NEW QUESTION # 86
Your company has thousands of recorded customer support calls in multiple languages stored as audio files in Azure Storage.
You need to generate text transcripts of all the recordings.
Which Azure Speech in Foundry Tools capability should you use?

Answer: D

Explanation:
For thousands of recorded support calls stored as audio files in Azure Storage, the correct capability is speech to text batch transcription.
Microsoft states that batch transcription is designed to transcribe a large amount of audio data in storage, including audio files in Azure Blob Storage, and that files can be processed concurrently to reduce turnaround time.
Real-time transcription is for live audio, not large stored batches. Text to speech converts text into audio. Speech translation translates speech between languages, but the requirement is to generate transcripts.


NEW QUESTION # 87
You are developing an application that continuously transcribes speech from a default microphone by using Azure Speech in Microsoft Foundry Tools.
You need to perform speech-to-text transcription from the microphone.
Which Python class should you use?

Answer: D

Explanation:
speechsdk.SpeechRecognizer is the appropriate Python class to handle continuous real-time speech-to-text transcription from a default microphone.
How to Implement It
To achieve continuous transcription (rather than transcribing a single sentence and stopping), you instantiate this class and invoke its asynchronous long-running method.speechsdk.SpeechRecognizer: Acts as the core proxy client connecting your application to the Azure Speech service.
start_continuous_recognition(): The essential method on this class that instructs the SDK to stream microphone data indefinitely and process multi-sentence conversations.
Reference:
https://stackoverflow.com/questions/67691338/continuous-speech-recognition-from-microphone-on-ms-azure


NEW QUESTION # 88
You have a Python application that extracts fields from invoices by using Azure Content Understanding in Foundry Tools You submit a PDF for analysts.
What should the application do to retrieve the results?

Answer: D

Explanation:
Azure Content Understanding analysis operations are asynchronous long-running operations. Microsoft's Python SDK documentation states that analysis starts with a begin operation, then the application polls for results until analysis completes.
Therefore, after submitting the PDF for analysis, the application should poll the operation results until the asynchronous analysis job succeeds .


NEW QUESTION # 89
You have an Azure Machine Learning model that generates a large quantity of false negatives.
You need to reduce the number of false negatives without re-training the model.
What should you do?

Answer: B

Explanation:
What are different methods to minimize False Negatives and False Positives in Binary Classification?
Threshold Line
One of the easiest methods to minimize the outcomes of a certain case is simply changing the decision boundary line from the basic 0.5 to above (when reducing False Positives) or below (when reducing False Negatives). It should be noted that by doing this, the possibility of False Positives increases. In other words, by decreasing the False Negatives we are increasing the False Positives.
Reference:
https://www.kaggle.com/discussions/general/376229


NEW QUESTION # 90
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:


NEW QUESTION # 91
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