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Microsoft AI-200 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Topic 2: Develop containerized solutions on Azure | - Implement containerized applications
|
| Topic 3: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Topic 4: Connect to and consume Azure services | - Integrate Azure services
|
Microsoft Developing AI Cloud Solutions on Azure Sample Questions:
A RAG application ' s retrieval step is returning documents that are topically related but not precisely relevant to the user ' s question.
You need to improve retrieval precision without retraining any model.
What should you do?
- A. Increase the embedding model ' s dimensionality only
- B. Enable semantic ranking (re-ranking) in Azure AI Search
- C. Reduce the number of indexed documents
- D. Disable vector search and use only keyword search
Correct Answer: B 🗳️
Explanation: Only visible for CertkingdomPDF members. You can sign-up / login (it's free).
You are implementing an Azure solution that uses Azure Cosmos DB and the latest Azure Cosmos DB SDK.
You add a change feed processor to a new container instance.
You attempt to read a batch of 100 documents. The process fails when reading one of the documents. The solution must monitor the progress of the change feed processor instance on the new container as the change feed is read. You must prevent the change feed processor from retrying the entire batch when one document cannot be read.
You need to implement the change feed processor to read the documents.
Which features should you use? To answer, move the appropriate features to the correct requirements. Each feature may be used 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:
Explanation:
You plan to deploy a container to an Azure App Service API app named api1. You host the source code for api1 in a GitHub repository. The container uses the API key at runtime to connect to a backend service.
The container must be able to retrieve the API key at runtime without exposing it in the source repository or Git commit history. The API key must not be stored in application configuration directly. The API key must be accessed securely from Azure Key Vault.
You need to ensure that the API key is stored securely in Azure Key Vault and is available to the container at runtime without being exposed in source control or Git commit history.
Solution: Store the API key as an App Service application setting configured through the Azure Portal.
Does the solution meet the goal?
- A. Yes
- B. No
Correct Answer: B 🗳️
You are reviewing secret access patterns used by an AI application that retrieves credentials from Key Vault.
You need to evaluate the security impact of each implementation approach.
What is the outcome of each approach? To answer, move the appropriate outcomes to the correct implementations. You may use each outcome 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:
Explanation:
An Azure Storage Blob upload must trigger backend processing.
The solution must:
* Avoid polling.
* Minimize latency.
* Trigger automatically when the upload occurs.
You need to ensure that processing starts as soon as a file is uploaded.
Which trigger should you implement?
- A. Timer
- B. Queue storage
- C. Event Grid
- D. HTTP
Correct Answer: C 🗳️
Explanation: Only visible for CertkingdomPDF members. You can sign-up / login (it's free).
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