AI-901 Valid Test Online | AI-901 Exam Preview

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Microsoft AI-901 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals
Exam Number:AI-900
Passing Score:700 / 1000
Exam Format:Scenario-based, Match the service to use case, Drag and drop, Multiple select, Multiple choice
Exam Duration:45-60
Available Languages:Korean, English, Chinese (Traditional), Portuguese (Brazil), Indonesian (Indonesia), German, Japanese, Russian, Arabic (Saudi Arabia), Italian, Spanish, Chinese (Simplified), French
Exam Price:USD 99
Related Certifications:Microsoft Certified: Azure AI Fundamentals
Real Exam Qty:40-60
Certificate Validity Period:1 year (renewable via free online assessment on Microsoft Learn)
Sample Questions:Microsoft AI-901 Sample Questions
Exam Way:Online (remote proctored via Pearson VUE) or at a Pearson VUE test center
Pre Condition:No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial.
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900

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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.

Microsoft Azure AI Fundamentals Sample Questions (Q99-Q104):

NEW QUESTION # 99
Which Azure Machine Learning capability should you use to quickly build and deploy a predictive model without extensive coding?

Answer: C

Explanation:
To easily build and deploy a predictive model using Azure Machine Learning, start by selecting the appropriate tools for your task, such as Azure Machine Learning Studio or AutoML, and follow a streamlined process of data preparation, model training, and deployment.
AutoML stands for Automated Machine Learning. It's a process that automates the various tasks involved in building machine learning models, including data preparation, feature selection, model training, hyperparameter tuning, and model evaluation, according to IBM. This automation makes machine learning more accessible to a wider range of users, including those without extensive machine learning expertise.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/concept-automated-ml?view=azureml-api-2


NEW QUESTION # 100
You have a Microsoft Foundry project that contains an agent named Agent1.
You need to ensure that Agent1 always calls an Azure function when the agent responds to user input.
To what should you set tool_choice for Agent1?

Answer: A

Explanation:
Microsoft's Foundry Agent Service documentation states that tool_choice provides deterministic control over tool calling:
auto means the model decides whether to call tools.
required means the model must call one or more tools.
none means the model does not call tools.
Therefore:
A . auto = Incorrect, because the model may or may not call the Azure function.
B . none = Incorrect, because this prevents tool/function calls.
C . required = Correct, because it forces the agent to call a tool.
The Azure OpenAI function-calling documentation also confirms that tool_choice="auto" lets the model decide whether to call a function, while tool_choice="none" forces a user-facing response without a tool call.


NEW QUESTION # 101
You are developing a simple application that uses the Microsoft Foundry SDK to send chat prompts to a model.
Which three elements should you provide in the code to run the application? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: B,C,D


NEW QUESTION # 102
Capturing text from images is an example of which type of Al capability?

Answer: A

Explanation:
Capturing or reading text from images is optical character recognition (OCR) . OCR is used to detect and extract printed or handwritten text from images, scanned documents, and other visual content.


NEW QUESTION # 103
You have an Azure subscription.
You need to use Azure Content Understanding in Foundry Tools to extract structured data from invoices.
What should you provision?

Answer: B

Explanation:
To extract structured data from invoices using Azure Content Understanding in Foundry Tools, you must provision a Microsoft Foundry resource (often referred to as an Azure AI services resource configured within a supported region).
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/tutorial/create-custom-analyzer


NEW QUESTION # 104
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