Dumps AI-200 PDF, Exam AI-200 Practice

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Microsoft AI-200 Exam Syllabus Topics:

SectionObjectives
Plan and manage Azure AI solutions- Monitor and optimize AI solutions
- Select appropriate Azure AI services
- Plan security and compliance requirements
Implement and monitor AI workloads- Monitor performance and troubleshoot issues
- Deploy AI models and services
Implement Azure AI solutions- Implement natural language processing solutions
- Implement computer vision solutions
- Implement generative AI solutions using Azure OpenAI
- Implement knowledge mining with Azure AI Search

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Microsoft AI-200 Practice Exam Questions (Desktop & Web-based)

It is browser-based; therefore no need to install it, and you can start practicing for the Developing AI Cloud Solutions on Azure (AI-200) exam by creating the Developing AI Cloud Solutions on Azure (AI-200) practice test. Our Developing AI Cloud Solutions on Azure (AI-200) exam dumps give help to give you an idea about the actual Microsoft AI-200 Exam. You can attempt multiple Developing AI Cloud Solutions on Azure (AI-200) exam questions on the software to improve your performance.

Microsoft Developing AI Cloud Solutions on Azure Sample Questions (Q38-Q43):

NEW QUESTION # 38
You have an Azure web app that uses Azure Cosmos DB as a data store. You create a Cosmos DB container by running the following PowerShell script:

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:

Explanation:

The question maps directly to the AI-200 objective "Develop AI solutions by using Azure Cosmos DB for NoSQL," which includes running queries and optimizing query performance and Request Unit (RU) consumption.
Statement 1: No - The minimum throughput is not 400 RU/s.
The PowerShell command provisions the container with:
-AutoscaleMaxThroughput 5000
Azure Cosmos DB autoscale operates between approximately 10% and 100% of the configured maximum throughput . Microsoft documentation specifically gives the example of an autoscale container provisioned with 5,000 RU/s scaling between 500 RU/s and 5,000 RU/s . Therefore, for this container, the minimum operating autoscale throughput is 500 RU/s , not 400 RU/s.
Therefore:
"The minimum throughput for the container is 400 RU/s." # No
Statement 2: No - The first query is not an in-partition query.
The container uses:
/EmployeeId
as its partition key.
The first query is:
SELECT * FROM c WHERE c.EmployeeId > ' 12345 '
Although the query references the partition key, it uses a range predicate ( > ) , not an equality predicate.
Microsoft explicitly states that a range filter on a partition key is not scoped to a single physical partition .
To qualify as an in-partition query, the filter must identify the applicable partition, typically through an equality predicate such as:
WHERE c.EmployeeId = ' 12345 '
Microsoft ' s documentation provides essentially the same example: a query using DeviceId > ... against a container partitioned by DeviceId is not an in-partition query .
Therefore:
"The first query statement is an in-partition query." # No
Statement 3: Yes - The second query is a cross-partition query.
The second query is:
SELECT * FROM c WHERE c.UserId = ' 12345 '
The container ' s partition key is /EmployeeId, not /UserId. Because the query contains no filter on the partition key , Azure Cosmos DB cannot route it to one logical partition. It must fan out the query across the applicable physical partitions and combine the results.
Microsoft describes this behavior directly: when a query does not contain a filter on the partition key, it must execute across the partitions.
Therefore:
"The second query statement is a cross-partition query." # Yes


NEW QUESTION # 39
Your application must classify uploaded product images into one of 40 custom categories specific to your business (e.g., proprietary part numbers). What should you use?

Answer: D

Explanation:
Prebuilt Vision models recognize general objects/scenes but not business-specific categories.
Custom Vision allows you to train a classifier on your own labeled images for domain-specific categories such as proprietary part numbers.


NEW QUESTION # 40
Hotspot Question
A company uses Azure Monitor Application Insights to monitor application behavior, including incoming requests and dependencies.
You must identify failed requests from the last hour. You must also calculate the average duration of failed request dependency calls, grouped by operation name.
You need to analyze telemetry in Application Insights.
Which operators should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: where
Filter telemetry rows
The where operator filters a table to rows that satisfy a specific predicate. Both box 1 and box 2 require filtering telemetry data to the last hour (timestamp > ago(1h)).
Box 2: where
In the Kusto Query Language (KQL), the where operator filters a table to rows that satisfy a specific predicate or condition. Inside the inner subquery, you need to filter the dependencies telemetry table to only include records from the last hour (timestamp > ago(1)) Box 3: summarize Aggregate calculated data The summarize operator produces a table that aggregates the content of the input table. It is used here with the avg() aggregation function to calculate the average duration grouped by the operation_Name.
Reference:
https://tryhackme.com/room/kqlkustobasicqueries


NEW QUESTION # 41
Hotspot Question
You are reviewing the Python tracing configuration for an application that must send distributed traces to Azure Monitor.
The following code configures OpenTelemetry tracing:

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:

Explanation:
Box 1: Yes
Yes, the code configures the tracer provider before any spans are created.
While the tracer provider initialization sequence is structurally correct, no spans can be captured yet at the moment the tracer instance is fetched because the processor and exporter are attached too late in the execution flow.
Box 2: No
No, this configuration does not export traces synchronously.
The code utilizes BatchSpanProcessor, which batches completed spans and exports them asynchronously on a background thread to prevent telemetry collection from blocking your main application code.
Box 3: Yes
Yes, this configuration successfully enables the export of distributed traces to Azure Monitor.
The code provided correctly initializes and wires up the native OpenTelemetry SDK components with the official Azure Monitor exporter library.
Reference:
https://learn.microsoft.com/en-us/python/api/overview/azure/monitor-opentelemetry-exporter-readme


NEW QUESTION # 42
You are developing an AI-powered API that retrieves connection strings and API keys from Azure Key Vault.
You must configure a solution that provides the following security functionality:
* The API must authenticate to Key Vault without storing credentials in any application configuration files
* The identity used by the API must have only the minimum permissions necessary to read secrets.
* The configuration must minimize the blast radius if an identity or credential is compromised.
You need to implement a secure access strategy for the API.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.

Answer: A,B

Explanation:
Detailed Explanation: The API should use a system-assigned managed identity so no application credential is stored or rotated by the development team. That identity should receive only the permission needed to read secret values: Key Vault Secrets User at the vault scope is materially narrower than Key Vault Administrator at subscription scope. Storing a secret value in App Configuration would violate the requirement to protect secrets and increases exposure. The corrected pair therefore implements both credential-free authentication and least-privilege authorization with a limited blast radius.
Study Guide Alignment: Security and operations: Key Vault, App Configuration, managed identity, OpenTelemetry, Azure Monitor, and KQL-based troubleshooting.
Official Microsoft Learn References: AI-200 Study Guide | Azure Key Vault RBAC guide | Managed identities for Azure resources


NEW QUESTION # 43
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