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AI-102: How to Create an Azure AI Resource for Customer Service Integration?

By: Author Alex Lim

Posted on

Categories Exam

Struggling with AI-102 exam questions on Azure AI deployment? Learn why creating an Azure AI resource (Option D) is the first step to integrate AI models into customer service platforms. Master exam strategies with actionable tips and scenario-based solutions.

Table of Contents

Question

You are an Azure developer at Nutex Inc. Your organization plans to integrate AI capabilities into its customer service platform to enhance user interactions. You want to use Azure AI services to enable you to deploy various AI models and services in customer service platforms.

What should you do first?

A. Use the REST API.
B. Install the Software Development Kit (SDK).
C. Identify endpoints and keys.
D. Create an Azure AI resource.

Answer

D. Create an Azure AI resource.

Explanation

Creating an Azure AI resource is the first step in utilizing Azure AI services. This resource is the foundational element that allows you to deploy and manage various AI models and services. Without this resource, you cannot proceed with other actions such as identifying endpoints and keys or using SDKs and APIs.

You would follow the below-outlined steps to create an Azure AI resource:

  1. Log in to the Azure portal.
  2. Click the Create a resource button in the upper-left corner (refer to the exhibit). Click the Create a resource button in the upper-left corner (refer to the exhibit).
  3. In the search bar, type the AI service resource you want to create, and select the specific AI service.
  4. Configure the resource by providing required details such as Subscription, Resource Group, Region, and Pricing Tier.
  5. Review the configuration, and click Create to deploy the resource.

Identifying endpoints and keys is not the first step in the given scenario. This is important for connecting your application to the Azure AI service securely and essential for making API calls and integrating the service into your application. Endpoints and keys are required for authentication and service access. However, you cannot identify these details until the Azure AI resource has been created.

Installing the SDK is not the first step in the given scenario. This is important for developing and integrating AI capabilities into your application. SDKs simplify interacting with Azure AI services by providing pre-built libraries and functions. However, this step would follow the creation of the AI resource, as the SDK will require the endpoints and keys to function correctly.

Using the REST API is not the first step in the given scenario. The REST API provides direct access to Azure AI services, allowing for custom integration and automation. It allows for programmatic access to Azure AI services. However, this step also requires the endpoints and keys, which means it cannot be done before the resource has been created.

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