Pass the Microsoft Azure AI Engineer Associate AI-102 Questions and answers with CertsForce

When deploying an Azure OpenAI model using the Microsoft.CognitiveServices/accounts/deployments resource in an ARM template, the throughput for a Standard deployment is set on the SKU object. Specifically:

Use the capacity field of the SKU to specify the per-deployment rate.

Provide the integer value that represents the requests per minute (RPM) you want the deployment to handle.

Therefore, to meet the requirement of 600 requests per minute , complete the template as:

" sku " : {

" name " : " Standard " ,

" capacity " : 600

}

This uses a single deployment SKU with a defined capacity. The ARM schema for accounts/deployments explicitly includes sku.capacity for resources that support scale (Azure OpenAI deployments do), and Azure OpenAI quota/rate-limit guidance confirms that rate limits are assigned per deployment.

Microsoft Azure AI Solution References

ARM template—Microsoft.CognitiveServices/accounts/deployments (2023-05-01) : property reference showing sku.capacity. Microsoft Learn

Resource type reference—latest accounts/deployments : confirms SKU usage on deployments. Microsoft Learn

Azure OpenAI quota and rate limits : explains assigning deployment-level limits (RPM/TPM). Microsoft Learn

A data analyst

The statement is:

“________ is responsible for creating visuals and charts that help a company make informed decisions.”

Let’s analyze the options:

A data analyst

Main responsibility: interpreting data, creating visuals, dashboards, and reports using tools like Power BI, Excel, or Tableau.

Helps stakeholders make business decisions from data.

Correct answer.

A data engineer

Focuses on designing, building, and maintaining data pipelines, ETL processes, and storage systems.

Not primarily responsible for creating visuals.

A data scientist

Specializes in advanced analytics, machine learning, and statistical modeling.

They may present insights but their focus is on predictions and algorithms, not routine visuals.

A database administrator (DBA)

Responsible for managing databases, ensuring security, availability, backups, and performance.

Not responsible for creating visuals or dashboards.

Correct Answer: A data analyst

Microsoft Reference

Roles in data analytics

Microsoft Learn: Data Analyst role description — responsible for creating reports and visualizations to support decision-making.

To maximize answer accuracy (reduce randomness and hallucinations) with Azure OpenAI GPT-3.5, you should lower the sampling randomness. The primary control for this is temperature :

Temperature controls how “creative” or random the model is.

Lower values → more deterministic, focused, and conservative outputs.

temperature = 0 makes the model pick the highest-probability tokens, which typically yields the most accurate and repeatable responses for transactional bots like booking/reservations.

Top P (nucleus sampling) is an alternative to temperature. Microsoft recommends using one or the other. While reducing Top P also narrows randomness, the clearest and most common approach for maximizing accuracy is setting temperature to 0. Setting Top P to 0 is generally not recommended and may be invalid depending on the SDK.

System message tuning (Option D) helps with tone, role, and policy adherence, but does not itself guarantee factual accuracy if decoding randomness remains high.

Including the travel agent’s database (Option A) would require Azure OpenAI on your data or a RAG pattern. That can improve grounding of facts, but it’s not a model parameter change and is outside the scope of simply configuring GPT-3.5; moreover, accuracy still benefits from low temperature even when using your own data.

Therefore, the best single action here is: set Temperature to 0.

Microsoft Azure AI Solution References

Azure OpenAI Service – Chat Completions parameters (Temperature and Top P): “Lower values like 0.2 will make the output more focused and deterministic… use either temperature or top_p but generally not both.”

https://learn.microsoft.com/azure/ai-services/openai/reference#chat-completions

Prompt engineering with Azure OpenAI – controlling randomness and determinism:

https://learn.microsoft.com/azure/ai-services/openai/concepts/prompt-engineering

Azure OpenAI on your data (grounding with enterprise data/RAG):

https://learn.microsoft.com/azure/ai-services/openai/concepts/use-your-data

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Box 1: Yes

http://localhost:5000/status : Also requested with GET, this verifies if the api-key used to start the container is valid without causing an endpoint query.

Box 2: Yes

The command saves container and LUIS logs to output mount at C:\output, located on container host

Box 3: Yes

http://localhost:5000/swagger : The container provides a full set of documentation for the endpoints and a Try it out feature. With this feature, you can enter your settings into a web-based HTML form and make the query without having to write any code. After the query returns, an example CURL command is provided to demonstrate the HTTP headers and body format that ' s required.

Data visualization’s primary purpose is to make data understandable and meaningful through visuals such as charts, dashboards, and graphs.

It helps to communicate significance (option A) and show patterns, correlations, and trends over time (option B).

C. Implement machine learning to predict future values → Not visualization, but rather ML/AI.

D. Enforce business logic across reports → Business logic is handled in data modeling or ETL, not visualization.

Correct Answers: A and B

Your app uses the primary admin key for index management. If it’s suspected compromised, the least-downtime rotation is:

Regenerate the secondary admin key to ensure it’s known only to you.

Switch the app to use the secondary key (no downtime—primary still works until you cut it off).

Regenerate the primary key to invalidate the compromised credential.

Query keys are read-only and cannot manage indexes, so switching to a query key would not meet the requirement. Regenerating the primary first would break the app until you update it.

References (Microsoft Azure Cognitive Search)

Admin (primary/secondary) vs. query keys and key rotation; key regeneration invalidates only the selected key.

Guidance to use the alternate admin key while rotating the other to avoid downtime.

To make a chatbot use uploaded company data from the Chat playground (“use your data”) , your code must:

Create a chat request (not a plain completion), so you need the ChatCompletionsOptions type for the request options.

This is the options class used for chat completions across Azure OpenAI SDKs and is the one that supports attaching data sources (extensions).

Configure the Azure AI Search data source as a chat extension so the model grounds answers on your indexed documents.

In the SDK, this is done by adding an AzureCognitiveSearchChatExtensionConfiguration entry under the extensions/dataSources collection and setting properties like SearchKey and IndexName . This is the specific configuration object for Azure AI Search integration with Chat Completions.

Therefore, the two dropdowns should be completed as:

First dropdown: ChatCompletionsOptions()

Second dropdown: AzureCognitiveSearchChatExtensionConfiguration

This matches how “Use your data (RAG)” is implemented in Azure OpenAI—chat request + Azure AI Search chat extension—so the bot can answer questions using your uploaded/company data. Microsoft Learn

Microsoft Azure AI Solution References

Azure OpenAI “Use your data” (concepts): how chat uses data sources like Azure AI Search. Microsoft Learn

Azure OpenAI client library for .NET (overview of chat options and extensions support). Microsoft Learn

Chat Completions Options (SDK docs, shows dataSources/extensions concept in chat options).

Examples/discussion of AzureCognitiveSearchChatExtensionConfiguration usage with SearchKey/IndexName.

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Box 1: api-nam.cognitive.microsofttranslator.com

https://docs.microsoft.com/en-us/azure/cognitive-services/translator/reference/v3-0-reference

Box 2: /translate

Scenario: All videos must have transcripts that are associated to the video and included in product descriptions.

Product descriptions, transcripts, and all text must be available in English, Spanish, and Portuguese.

Step 1: Upload the video to blob storage

Given a video or audio file, the file is first dropped into a Blob Storage. T

Step 2: Index the video by using the Video Indexer API.

When a video is indexed, Video Indexer produces the JSON content that contains details of the specified video insights. The insights include: transcripts, OCRs, faces, topics, blocks, etc.

Step 3: Extract the transcript from the Video Indexer API.

Step 4: Translate the transcript by using the Translator API.