You are currently here!
  • Home
  • Microsoft AI-901 AI-901 Dumps PDF – AI-901 Real Exam Questions Answers [Q15-Q34]

AI-901 Dumps PDF – AI-901 Real Exam Questions Answers [Q15-Q34]

August 24, 2026 latestexam 0 Comments
5/5 - (1 vote)

AI-901 Dumps PDF – AI-901 Real Exam Questions Answers

Get Started: AI-901 Exam [year] Dumps Microsoft PDF Questions

Microsoft AI-901 Exam Syllabus Topics:

Section Weight Objectives
Topic 1: Describe fundamental principles of machine learning on Azure (15-20%) 15-20% – Identify common machine learning techniques

  • 1. Identify clustering machine learning scenarios
  • 2. Identify regression machine learning scenarios
  • 3. Identify classification machine learning scenarios
  • 4. Identify features of deep learning techniques

– Describe core machine learning concepts

  • 1. Identify features and labels for training data in machine learning
  • 2. Describe how training and validation datasets are used in machine learning

– Describe Azure Machine Learning capabilities

  • 1. Describe model management and deployment capabilities in Azure Machine Learning
  • 2. Describe data and compute services for data science and machine learning
  • 3. Describe capabilities of automated machine learning
Topic 2: Describe features of generative AI workloads on Azure (20-25%) 20-25% – Identify features of generative AI solutions

  • 1. Identify features of generative AI models
  • 2. Identify responsible AI considerations for generative AI
  • 3. Identify common scenarios for generative AI

– Identify generative AI services and capabilities in Microsoft Azure

  • 1. Describe features and capabilities of Azure AI Foundry model catalog
  • 2. Describe features and capabilities of Azure OpenAI service
  • 3. Describe features and capabilities of Azure AI Foundry
Topic 3: Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%) 15-20% – Identify features of common NLP workload scenarios

  • 1. Identify features and uses for language modeling
  • 2. Identify features and uses for speech recognition and synthesis
  • 3. Identify features and uses for translation
  • 4. Identify features and uses for entity recognition
  • 5. Identify features and uses for key phrase extraction
  • 6. Identify features and uses for sentiment analysis

– Identify Azure tools and services for NLP workloads

  • 1. Describe capabilities of the Azure AI Speech service
  • 2. Describe capabilities of the Azure AI Language service
Topic 4: Describe Artificial Intelligence workloads and considerations (15-20%) 15-20% – Identify features of common AI workloads

  • 1. Identify features of knowledge mining workloads
  • 2. Identify features of computer vision workloads
  • 3. Identify features of Natural Language Processing (NLP) workloads
  • 4. Identify features of document intelligence workloads
  • 5. Identify features of content moderation and moderation workloads
  • 6. Identify features of generative AI workloads

– Identify guiding principles for responsible AI

  • 1. Describe considerations for transparency in an AI solution
  • 2. Describe considerations for accountability in an AI solution
  • 3. Describe considerations for fairness in an AI solution
  • 4. Describe considerations for privacy and security in an AI solution
  • 5. Describe considerations for inclusiveness in an AI solution
  • 6. Describe considerations for reliability and safety in an AI solution
Topic 5: Describe features of computer vision workloads on Azure (15-20%) 15-20% – Identify common types of computer vision solution

  • 1. Identify features of image classification solutions
  • 2. Identify features of image analysis solutions
  • 3. Identify features of semantic segmentation solutions
  • 4. Identify features of optical character recognition (OCR) solutions
  • 5. Identify features of object detection solutions
  • 6. Identify features of face detection and identification solutions

– Identify Azure tools and services for computer vision tasks

  • 1. Describe capabilities of the Azure AI Vision service
  • 2. Describe capabilities of the Azure AI Face detection service

 

Q15. You have a Microsoft Foundry project that has a generative AI model deployment.
You need to ensure that responses generated by the model minimize costs and remain within a defined length.
Which parameter should you configure?

 
 
 
 

Q16. Hotspot Question
Select the answer that correctly completes the sentence.

Q17. Your company processes customer support emails.
You need to implement an AI solution that automatically identifies mentions of people, organizations, and locations in the emails.
Which text analysis technique should you use?

 
 
 
 

Q18. You are developing an application that extracts fields from PDFs by using Azure Content Understanding in Foundry Tools.
You need to use the Python SDK to submit a PDF for analysis and retrieve the extraction results.
What should you do?

 
 
 
 

Q19. You need to convert written customer notifications into natural-sounding spoken audio that can be played over a phone system. Which Azure Speech in Foundry Tools capability should you use?

 
 
 
 

Q20. You are developing an application that analyzes voicemail recordings by using Azure Content Understanding in Foundry Tools.
You need to extract a transcript and structured information from the recordings.
Which type of analyzer should you use?

 
 
 
 

Q21. Select the answer that correctly completes the sentence.

Q22. You have a Microsoft Foundry project that contains a generative AI model deployment.
You test the model by using the Foundry playground.
You need to develop an application that sends requests to the deployed model.
Which information must the application include to call the model?

 
 
 
 

Q23. You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You need to develop an application that sends a message containing text and an image URL. The solution must ensure the quickest response time.
Which message structure should you include in the request?

 
 
 
 

Q24. You are developing an application that processes voicemail recordings by using Azure Content Understanding in Foundry Tools. Which feature does Azure Content Understanding use to convert audio to text?

 
 
 
 

Q25. What is an example of a Microsoft responsible AI principle?

 
 
 
 

Q26. Hotspot Question
Select the answer that correctly completes the sentence.

Q27. Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Q28. You are developing a web app that processes invoices to calculate expenses.
You need to extract structured fields, including nested values, from the invoices by using a defined schema.
What should you use?

 
 
 
 

Q29. What should you use to identify similar faces in a set of images?

 
 
 
 

Q30. You are developing an application that extracts structured information from different types of content by using Azure Content Understanding in Foundry Tools.
You need to extract scanned invoices in the PDF format and voicemail recordings in the WAV format.
Which type of analyzer should you use for each content type? To answer, drag the appropriate analyzer types to the correct content types. Each analyzer type 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.

Q31. You have a Microsoft Foundry project that contains a generative AI model deployment.
You test the model by using the Foundry playground.
You need to develop an application that sends requests to the deployed model.
Which information must the application include to call the model?

 
 
 
 

Q32. Hotspot Question
You are developing an application that analyze invoices by using Azure Content Understanding in Foundry Tools.
You need to ensure that the application retrieves the analysis results after processing completes.
How should you complete the Python code? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.

Q33. You are developing a web app that processes invoices to calculate expenses.
You need to extract structured fields, including nested values, from the invoices by using a defined schema.
What should you use?

 
 
 
 

Q34. You are developing an application that processes voicemail recordings by using Azure Content Understanding in Foundry Tools.
Which feature does Azure Content Understanding use to convert audio to text?

 
 
 
 

AI-901 Premium Exam Engine pdf Download: https://www.latestcram.com/AI-901-exam-cram-questions.html

Related Links: www.stes.tyc.edu.tw www.stes.tyc.edu.tw www.stes.tyc.edu.tw fakescam.net www.stes.tyc.edu.tw www.stes.tyc.edu.tw

leave a comment

Enter the text from the image below