[Jan-2026] Pass Microsoft AI-900 Tests Engine pdf - All Free Dumps [Q74-Q91]

[Jan-2026] Pass Microsoft AI-900 Tests Engine pdf - All Free Dumps

Microsoft Azure AI Fundamentals Practice Tests 2026 | Pass AI-900 with confidence!

Explain Conversational Artificial Intelligence Workloads Features on Azure (15-20%)

In the last section, you will face with the following subtopics:

Establish Azure services for Conversational Artificial Intelligence – The potential candidates for the Microsoft AI-900 exam should have the capacity to identify the capabilities of Azure Bot Service and QnA Maker service.
Identify the basic use cases for Conversational Artificial Intelligence (AI) – The students should be able to identify the features and usage for a range of elements. These include personal digital assistants, webchat bots, and telephone voice menus. It also covers the skills in identifying the basic features of conversational Artificial Intelligence solutions.

NEW QUESTION # 74
Match the principles of responsible AI to appropriate requirements.
To answer, drag the appropriate principles from the column on the left to its requirement on the right. Each principle 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.

Answer:

Explanation:

Explanation
Graphical user interface, text, application, email Description automatically generated

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

NEW QUESTION # 75
Select the answer that correctly completes the sentence.

Answer:

Explanation:

NEW QUESTION # 76
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-science-process/create-features

NEW QUESTION # 77
Your company manufactures widgets.
You have 1.000 digital photos of the widgets.
You need to identify the location of the widgets within the photos.
What should you use?

A. Custom Vision object detection
B. Computer Vision Image Analysis
C. Custom Vision classification
D. Computer Vision Spatial Analysis

Answer: A

Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore computer vision in Microsoft Azure," object detection is a computer vision technique used to locate and identify objects within an image. It not only determines what objects are present but also where they appear in the image by returning bounding box coordinates around each detected item.
In this scenario, the goal is to identify the location of widgets within digital photos. This requires both recognition (knowing that the object is a widget) and localization (determining its position). The Custom Vision service in Azure allows you to train a model specifically for your own images, making it ideal for recognizing company-specific products such as widgets. By selecting the Object Detection domain in Custom Vision, you can label regions of interest in your training images. The model then learns to detect and locate those objects in new photos.
Let's examine the other options:
* A. Computer Vision Spatial Analysis: Used for people tracking, movement detection, and occupancy analytics in video streams - not for locating products in still images.
* C. Custom Vision classification: This model categorizes an image as a whole (e.g., "contains a widget" or "does not contain a widget") but does not locate objects within the image.
* D. Computer Vision Image Analysis: Provides general image tagging, description, and OCR capabilities but does not pinpoint object locations.

NEW QUESTION # 78
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/create-features

NEW QUESTION # 79
Match the principles of responsible AI to appropriate requirements.
To answer, drag the appropriate principles from the column on the left to its requirement on the right. Each principle 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.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

NEW QUESTION # 80
Which two tools can you use to call the Azure OpenAI service? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.

A. Azure SDK for JavaScript
B. Azure SDK for Python
C. Azure REST API
D. Azure Command-Line Interface (CLI)

Answer: C,D

NEW QUESTION # 81
Match the machine learning tasks to the appropriate scenarios.
To answer, drag the appropriate task from the column on the left to its scenario on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml

NEW QUESTION # 82
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
Explanation

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/create-features

NEW QUESTION # 83
You plan to deploy an Azure Machine Learning model as a service that will be used by client applications.
Which three processes should you perform in sequence before you deploy the model? To answer, move the appropriate processes from the list of processes to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - data preparation
2 - model training
3 - model evaluation
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-ml-pipelines

NEW QUESTION # 84
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/algorithm-module-reference/linear-regression
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize-model-clustering Regression is a form of machine learning that is used to predict a numeric label based on an item's features.
https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer/introduction

NEW QUESTION # 85
You use Azure Machine Learning designer to publish an inference pipeline.
Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. the model name
B. the authentication key
C. the REST endpoint
D. the training endpoint

Answer: B,C

Explanation:
Section: Describe fundamental principles of machine learning on Azure
Explanation:
You can consume a published pipeline in the Published pipelines page. Select a published pipeline and find the REST endpoint of it.
To consume the pipeline, you need:
* The REST endpoint for your service
* The Primary Key for your service
Reference:
https://docs.microsoft.com/en-in/learn/modules/create-regression-model-azure-machine-learning-designer/ deploy-service

NEW QUESTION # 86
brectly completes the sentence.

Answer:

Explanation:

Explanation:

NEW QUESTION # 87
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/bot-service/bot-service-overview-introduction?view=azure-bot-service-4.0

NEW QUESTION # 88
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-science-process/create-features

NEW QUESTION # 89
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/machine-learning/concept-designer

NEW QUESTION # 90
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing