AI-200 Practice Test 4 — 25 Questions

Question 1

When configuring an Azure AI Search vector index, which TWO parameters can be adjusted within the HNSW algorithm configuration to trade off between search speed, memory usage, and recall accuracy? (Choose two)

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

efSearch. In HNSW, parameters like m (links per node) and efSearch (size of candidate list during search) allow tuning between recall accuracy and query performance.

Answer

replicaCount

Answer

partitionCount

Answer

maxTextLength

Question 2

Which THREE of the following are components of a standard Dockerfile for an AI application?

Accepted Answer

RUN (Installation of libraries/tools).. Base image, dependency installation, and the application entrypoint are core components.

Answer

CLUSTER_CREATE.

Answer

AZURE_LOGIN (Manual login).

Question 3

Which distance metric in Azure Cosmos DB vector search calculates the shortest straight-line segment between two points in a multi-dimensional space?

Accepted Answer

euclidean. Euclidean distance measures the straight-line distance between two points in Euclidean space.

Answer

dotproduct

Answer

hamming

Answer

cosine

Question 4

Which Azure service provides a fully managed NoSQL database with native vector search capabilities and turnkey multi-region replication?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB provides managed NoSQL capabilities with built-in vector search and global distribution.

Answer

Azure Table Storage

Answer

Azure Blob Storage

Answer

Azure SQL Database

Question 5

Which Azure AI Search API parameter allows you to specify a vector query alongside traditional keyword search terms when executing a hybrid search?

Accepted Answer

vectorQueries. In Azure AI Search queries, the vectorQueries parameter is used to pass vector embedding query objects during search requests.

Answer

embeddingQuery

Answer

knnQuery

Answer

vectorSearchParam

Question 6

You are designing a high-availability RAG architecture where search queries must succeed even if an entire Azure region experiences an outage. You deploy Azure AI Search in a primary region and a secondary region. How should client applications handle failover?

Accepted Answer

Use Azure Traffic Manager or Azure Front Door in front of regional search service endpoints with health probes. Applications implement traffic routing via Azure Traffic Manager or Azure Front Door pointing to both search service regional endpoints, combined with geo-replication of search indexes.

Answer

Hardcode the secondary search IP address in client application configuration files

Answer

Rely on Cosmos DB automatic failover to replicate search indices

Answer

Configure SQL replication between search indexes

Question 7

In Azure Cosmos DB for NoSQL, which property in the container definition specifies the path to the property containing the vector array within each document?

Accepted Answer

path. The vector embedding policy defines paths (e.g., /vectorProperty) to locate the vector array inside items.

Answer

propertyLocation

Answer

field

Answer

jsonPath

Question 8

Which REST API HTTP method is used to create or update an index definition in Azure AI Search?

Accepted Answer

PUT. Azure AI Search REST API uses HTTP PUT to create or fully update an index definition.

Answer

GET

Answer

PATCH

Answer

DELETE

Question 9

When configuring vector search in Azure Cosmos DB for NoSQL, which TWO data types are valid for storing vector embeddings within the vector embedding policy? (Choose two)

Accepted Answer

float32. Cosmos DB vector embedding policy supports float32 and float16 (or int8 depending on quantization) for vector properties.

Answer

boolean

Answer

guid

Answer

string

Question 10

Which Azure AI Search capability allows you to extract text from images and PDF documents during indexer execution using AI cognitive skills?

Accepted Answer

Skillsets. Skillsets in Azure AI Search enable cognitive enrichment, allowing tasks like OCR and entity extraction during ingestion.

Answer

Semantic configurations

Answer

Scoring profiles

Answer

Vector profiles

Question 11

You are managing an Azure AI Search index that uses integrated vectorization with Azure OpenAI. When a user sends a query string, you want Azure AI Search to automatically vectorize the query text before performing the vector search. Which feature must you configure in the index schema?

Accepted Answer

A custom Web API skillset. Integrated vectorization in Azure AI Search uses a vectorizer configuration connected to Azure OpenAI to automatically convert plain text queries into vector embeddings.

Answer

A cognitive services attachment on the storage account

Answer

An Azure Logic App trigger

Question 12

You are designing a multi-tenant AI application using Azure Cosmos DB for NoSQL. Each tenant has their own set of embeddings, and you need to filter vector search results strictly by tenantId while maintaining high query performance. How should you structure your vector index definition?

Accepted Answer

Include tenantId in the container's standard indexing policy with a range index, and filter using a WHERE clause alongside ORDER BY VectorDistance(). When configuring vector embeddings in Azure Cosmos DB for NoSQL, you must specify the dataType, dimensions, distanceFunction, and similarity metric. To filter efficiently, you combine VectorDistance() with a traditional WHERE clause on tenantId, ensuring the property is indexed.

Answer

Store tenantId inside the vector array as the first element

Answer

Use spatial indexes on tenantId

Answer

Create a separate container for every tenant automatically

Question 13

Which tool in Azure Portal allows you to test search queries, inspect index schemas, and view JSON responses for Azure AI Search?

Accepted Answer

Search explorer. The Search Explorer in the Azure Portal provides a built-in UI interface for testing queries and inspecting indices in Azure AI Search.

Answer

Metrics Advisor

Answer

Data Explorer

Answer

Log Analytics

Question 14

You are evaluating data layer architectures for an enterprise AI application that requires both vector search and structured transactional data management. Which THREE criteria favor choosing Azure Cosmos DB over Azure AI Search as the primary database? (Choose three)

Accepted Answer

Need for sub-10 millisecond point reads and writes on operational business records. Azure Cosmos DB is preferred when you need ACID transactions, low-latency point reads/writes on transactional records, and native NoSQL document storage alongside vector search.

Answer

Requirement for advanced BM25 keyword search and neural semantic re-ranking

Answer

Requirement to generate automatic PDF text extraction and document chunking via indexers

Question 15

You are optimizing an Azure Cosmos DB for NoSQL vector search container. Which THREE properties must be correctly configured inside the vectorEmbeddingPolicy JSON object? (Choose three)

Accepted Answer

path. The vectorEmbeddingPolicy in Cosmos DB requires defining paths, dataTypes, distanceFunctions, and dimensions for each vector property.

Answer

httpPort

Answer

sslEnabled

Question 16

You are writing a query in Azure Cosmos DB for NoSQL that sorts results by vector similarity and also filters results by a category property. How must you order the clauses in your SQL statement?

Accepted Answer

The WHERE clause must come before the ORDER BY VectorDistance() clause. In Azure Cosmos DB, when using VectorDistance in an ORDER BY clause along with a WHERE filter, the WHERE clause must precede the ORDER BY clause.

Answer

VectorDistance must be placed in the SELECT clause instead of ORDER BY

Answer

WHERE and ORDER BY clauses cannot be used in the same query when using vectors

Answer

The ORDER BY clause must come before the WHERE clause

Question 17

You are building a chat application with memory using Azure AI Search. You want to retrieve previous conversation turns that are semantically similar to the current user prompt. What search mode should you use if you want to execute both a vector search and a keyword search simultaneously and combine their results?

Accepted Answer

Hybrid search. Executing vector and keyword search simultaneously in Azure AI Search is known as hybrid search.

Answer

Exhaustive k-NN search

Answer

Wildcard search

Answer

Fuzzy search only

Question 18

Which Azure portal blade allows you to view and manage access keys and connection strings for an Azure AI Search service?

Accepted Answer

Keys. The 'Keys' blade in the Azure Portal provides admin and query API keys for Azure AI Search.

Answer

Data source

Answer

Certificates

Answer

Scale

Question 19

When configuring vector search in Azure AI Search, which TWO components are required to successfully define and execute a vector search query? (Choose two)

Accepted Answer

A vector query payload specifying the query vector and target field. Executing a vector search query requires a vector-typed field in the index and a query request specifying the vector query vector values and target field.

Answer

A Cosmos DB container partition key

Answer

An Azure SQL Server database connection string

Answer

An HDInsight Hadoop cluster endpoint

Question 20

You are managing an Azure AI Search index with millions of high-dimensional vectors. Users experience intermittent timeout errors during peak query hours. Upon investigation, you find that the search service CPU utilization is at 100%. What is the most effective architectural mitigation?

Accepted Answer

Scale out the search service by adding search units (replicas). Scaling out search units (adding replicas) increases query throughput and distributes CPU load across multiple nodes.

Answer

Increase the embedding dimension size from 1536 to 3072

Answer

Switch the index from HNSW to exhaustive k-NN search

Answer

Decrease the number of replicas to reduce network chatter