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Microsoft AI-900 Exam (page: 6)
Microsoft Azure AI Fundamentals
Updated on: 25-Aug-2025

Viewing Page 6 of 36
AI-900 PDF 273 Questions

Which Azure service can use the prebuilt receipt model in Azure AI Document Intelligence?

  1. Azure AI Services
  2. Azure Machine Learning
  3. Azure AI Vision
  4. Azure AI Custom Vision

Answer(s): A

Explanation:

Azure AI Services, Document Intelligence Document Intelligence receipt model
The Document Intelligence receipt model combines powerful Optical Character Recognition (OCR) capabilities with deep learning models to analyze and extract key information from sales receipts. Receipts can be of various formats and quality including printed and handwritten receipts.


Reference:

https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/concept-receipt



HOTSPOT (Drag and Drop is not supported)
Select the answer that correctly completes the sentence.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box: obtain approval based on their intended usage
As part of the Microsoft responsible AI principles, customers must       before they can use Azure OpenAI.
Microsoft legal resources, Limited access to Azure OpenAI Service Registration process
Azure OpenAI requires registration and is currently only available to approved enterprise customers and partners. Customers who wish to use Azure OpenAI are required to submit a registration form.
Customers must attest to any and all use cases for which they will use the service (the use cases from which customers may select will populate in the form after selection of the desired model(s) in Question 22 in the initial registration form). Customers who wish to add additional use cases after initial onboarding must submit the additional use cases using this form. The use of Azure OpenAI is limited to use cases that have been selected in a registration form. Microsoft may require customers to re-verify this information. Read more about example use cases and use cases to avoid here.


Reference:

https://learn.microsoft.com/en-us/legal/cognitive-services/openai/limited-access



What is an example of a Microsoft responsible AI principle?

  1. AI systems should protect the interests of developers.
  2. AI systems should be in the public domain.
  3. AI systems should be secure and respect privacy.
  4. AI systems should make personal details accessible.

Answer(s): C

Explanation:

Responsible AI principles
* Fairness: AI systems should treat all people fairly. Reliability and safety: AI systems should perform reliably and safely. Privacy and security: AI systems should be secure and respect privacy. Inclusiveness: AI systems should empower everyone and engage people.
Etc.


Reference:

https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai



What should you do to reduce the number of false positives produced by a machine learning classification model?

  1. Include test data in the training data.
  2. Increase the number of training iterations.
  3. Modify the threshold value in favor of false positives.
  4. Modify the threshold value in favor of false negatives.

Answer(s): D

Explanation:

If you have a classifier which calculates a real values score and then a threshold is applied to define what is classified as positive or negative. By changing this threshold you can decrease the number of false positives at the expense of increasing the number of false negatives.


Reference:

https://www.quora.com/Why-does-my-artificial-neural-network-predict-too-many-false-positives-FP



HOTSPOT (Drag and Drop is not supported)
Select the answer that correctly completes the sentence.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box: numeric
When building a K-means clustering model, all features must have a data type of    . K-means is one of the simplest and the best known unsupervised learning algorithms.
Select the Normalize features option if you want to normalize features before training.
If you apply normalization, before training, the data points are normalized to [0,1] by MinMaxNormalizer.


Reference:

https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/k-means-clustering



You are building an AI-based loan approval app.
You need to ensure that the app documents why a loan is approved or rejected and makes the report available to the applicant.
This is an example of which Microsoft responsible AI principle?

  1. transparency
  2. inclusiveness
  3. fairness
  4. accountability

Answer(s): A

Explanation:

Transparency: AI systems should be transparent and understandable. AI systems might help inform decisions that have great impact on people's lives, so it's important that people understand how these decisions are made.


Reference:

https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai



HOTSPOT (Drag and Drop is not supported)
Select the answer that correctly completes the sentence.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box: fairness
Fairness: AI systems should treat all people fairly. The same recommendations should be made to everyone. Fairness is important to ensure that AI systems don't discriminate against people based on their personal characteristics.
Note: Design your bot so that it respects relevant cultural norms and guards against misuse.
Since bots may have human-like personas, it is especially important that they interact respectfully and safely with users and have built-in safeguards and protocols to handle misuse and abuse.
Limit the surface area for norms violations where possible.
* Where appropriate, point to a relevant “code of conduct” for users.
*-> Apply machine learning techniques and keyword filtering mechanisms to enable your bot to detect and — critically — respond appropriately to sensitive or offensive input from users.


Reference:

https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai https://www.microsoft.com/en-us/research/uploads/prod/2018/11/Bot_Guidelines_Nov_2018.pdf



DRAG DROP (Drag and Drop is not supported)
Match the AI workload to the appropriate task.
To answer, drag the appropriate AI workload from the column on the left to its task on the right. Each workload may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Select and Place:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Azure AI Document Intelligence - Extract data from medical admission forms for import into a patient tracking database.
Azure AI Document Intelligence specializes in extracting structured information from documents, such as forms, invoices, or medical records.
Generative AI - Analyze aerial photos to identify flooded areas.
Computer vision is used to analyze and interpret images or videos, making it suitable for identifying features like flooded areas in aerial photos.
Computer Vision - Analyze aerial photos to identify flooded areas.
Computer vision is used to analyze and interpret images or videos, making it suitable for identifying features like flooded areas in aerial photos.



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