AI-300: Operationalizing Machine Learning and Generative AI Solutions

A team deploys a machine learning model to a managed online endpoint. The team monitors model performance and data quality metrics in production.

When monitoring thresholds are exceeded, the team requires an automated operational response that notifies downstream systems.

You need to configure the monitoring solution to meet the requirements.

Which configuration should you associate with each requirement as a first step? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Correct answer: To work with this question, an Exam Simulator is required.

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.

You work in Microsoft Foundry with a prompt flow.

You must manually evaluate prompts and compare results across prompt variants.

You need to capture the inputs, outputs, token usage, and latencies for each flow run for the evaluation.

Solution: Create prompt variants and compare their outputs in the Evaluation experience.

Does the solution meet the goal?

Yes
No

Correct answer: B

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.

You work in Microsoft Foundry with a prompt flow.

You must manually evaluate prompts and compare results across prompt variants.

You need to capture the inputs, outputs, token usage, and latencies for each flow run for the evaluation.

Solution: In Microsoft Foundry, turn on Tracing for the prompt flow of the project and execute test runs to produce trace data.

Does the solution meet the goal?

Yes
No

Correct answer: A

A team deploys a generative AI application that uses a model deployed in Microsoft Foundry. The application must support latency monitoring under production load.

You need to enable performance observability.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Correct answer: To work with this question, an Exam Simulator is required.

An organization operates a generative AI application in production by using Microsoft Foundry. The application serves live user traffic and is updated by a data scientist team regularly as prompts and models evolve.

The application intermittently times out during production use, which requires ongoing visibility into runtime behavior.

The team must also validate model quality and safety before releasing new updates to avoid introducing regressions.

You need to apply the correct mechanisms for continuous runtime monitoring and for release time validation.

Which mechanisms should you use for each requirement? To answer, move the appropriate mechanisms to the correct requirements. You may use each mechanism once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Correct answer: To work with this question, an Exam Simulator is required.

An organization is deploying several generative AI workloads by using Microsoft Foundry. Each workload must meet different requirements related to data governance, task specialization, and operational cost control.

The organization requires models that meet the following requirements:

Model behavior aligns with the task being performed.

Data handling aligns with internal governance policies.

Operational complexity and cost are justified by workload needs.

You need to select the foundation model options that meet the requirements.

Which three models can you select? Each correct answer presents a complete solution. Choose three.

NOTE: Each correct selection is worth one point.

A model that is optimized for conversational reasoning when deploying an interactive assistant
The largest available model to simplify operational management
The smallest available model to minimize the usage cost
A model that supports multiple input types when workloads require combined text and image analysis
A model that offers enterprise governance controls when workloads process regulated business data

Correct answer: B, C, E

A team is building a generative AI agent by using Retrieval-Augmented Generation (RAG) in Microsoft Foundry.

The team frequently updates prompt content. The team must be able to track changes across contributors while avoiding full application redeployments.

You need to enable rapid prompt iteration with traceability. Applications consuming the agent must be able to use updated prompts without requiring redeployment.

What should you configure for each requirement? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Correct answer: To work with this question, an Exam Simulator is required.

A company is creating an internal tool that summarizes long meeting transcripts and extracts action items.

The model must:

Process text inputs up to 200k tokens long.

Generate concise summaries in seconds.

Support interactive testing before integration into the app.

You need to select, deploy, and test a model that supports summarization with low latency.

How should you complete the configuration plan? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Correct answer: To work with this question, an Exam Simulator is required.

You are reviewing a dataset that will be used for an advanced fine-tuning job in Microsoft Foundry.

The fine-tuning job uses preference comparison data.

You review the following dataset excerpt.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Correct answer: To work with this question, an Exam Simulator is required.

You train a model in Azure Machine Learning.

You plan to capture experiment details for later comparison. The training code must log parameters and metrics for each run.

You review the following training script.

You need to verify whether the training script meets the experiment tracking requirement. For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Correct answer: To work with this question, an Exam Simulator is required.

Vendor:	Microsoft
Exam Code:	AI-300
Exam Name:	Operationalizing Machine Learning and Generative AI Solutions
Date:	May 06, 2026
File Size:	2 MB

Download Operationalizing Machine Learning and Generative AI Solutions.AI-300.ExamTopics.2026-05-06.20q.tqb

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