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Microsoft AI-200 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure, monitor, and optimize AI solutions | 20% | - Implement observability and reliability
|
| Topic 2: Integrate backend services and build event-driven architectures | 25% | - Implement messaging and event systems
|
| Topic 3: Develop containerized AI solutions on Azure | 25% | - Implement container hosting environments
|
| Topic 4: Develop AI solutions using Azure data services | 30% | - Design and optimize data access and retrieval
|
Microsoft Developing AI Cloud Solutions on Azure Sample Questions:
You develop an application that sells Al generated images based on user input. You recently started a marketing campaign that displays unique ads every second day.
Sales data is stored in Azure Cosmos 06 with the date of each sale being stored in a property named whenFinished ' . The marketing department requires a view that shows the number of sales grouped into two- day periods You need to implement the query for the view.
How should you complete the query? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point.
Correct Answer:
Explanation:
You develop a message-processing service deployed to Azure Container Apps. The service reads messages from an Azure Service Bus queue.
The solution must minimize costs by ensuring NO compute resources are consumed when the queue is empty.
You need to configure scaling for the service.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two NOTE: Each correct selection is worth one point.
- A. Configure a Kubernetes Event-driven Autoscaler rule that monitors queue length.
- B. Increase the scaling rule to allow for the maximum running replica count.
- C. Enable HTTP ingress concurrency scaling
- D. Configure the scaling rule to allow for the termination of all active replicas.
Correct Answer: A,D 🗳️
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You need to address the known issue resulting from vector similarity queries.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
- A. Add a composite index on the vector fields and metadata properties of the container.
- B. Reduce the numeric precision of the vector embeddings where supported.
- C. Change the vector index type from flat to quantizedFlat or diskANN.
- D. Set the account consistency level to Strong.
Correct Answer: B,C 🗳️
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A semantic search application queries Azure Database for PostgreSQL and stores document embeddings and metadata in a table with the following columns:
* embedding (pgvector)
* department
* created_at
The application must return the top five most similar documents for a given query embedding only from the finance department. You need to implement semantic retrieval with metadata filtering.
Which query components should you select? To answer, move the appropriate query components to the correct requirements. You may use each query component once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
Correct Answer:
Explanation:
Verified Answer: Filter: `WHERE department = ' finance ' `. Rank/top five: `ORDER BY embedding < = > query_embedding LIMIT 5`.
Detailed Explanation: The metadata predicate must restrict the candidate rows to the Finance department, so the `WHERE department = ' finance ' ` component supplies the required filter. The pgvector cosine-distance operator ` < = > ` orders rows by vector distance to the supplied query embedding, and `LIMIT 5` keeps only the five nearest matches. Ordering by creation date would rank recency rather than semantic similarity, and a wildcard department filter would not satisfy the Finance-only requirement.
Study Guide Alignment: AI data-management workloads: Cosmos DB, PostgreSQL, caching, vector storage, vector retrieval, consistency, and connection optimization.
Official Microsoft Learn References: AI-200 Study Guide | Vector similarity search with Azure PostgreSQL
A company has an Azure Cosmos DB for NoSQL account. The account is configured for session consistency.
Data is written to a single Azure region and data can be read from three Azure regions.
An application that will access the Azure Cosmos DB for NoSQL container data using an SDK has the following requirements:
* Roads from the application must return the most recent committed version of an Item from any Azure region.
The container items should not automatically be deleted.
You need to implement the changes to the Azure Cosmos DB for NoSQL account. What should you do? To answer, select the appropriate options in the answer area.
Correct Answer:
Explanation:
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