<h1 dir="ltr" style="color: rgb(85, 85, 85);">Lab Details</h1><ol><li dir="ltr">In this lab we will walk through the steps&nbsp;to deploy cognitive search using an ARM template.</li><li dir="ltr">Duration:&nbsp;30 minutes.</li></ol><h1 dir="ltr" style="color: rgb(85, 85, 85);">Introduction</h1><h2 dir="ltr" style="color: rgb(85, 85, 85);">What is Azure Cognitive Search?</h2><ul><li dir="ltr">Azure Cognitive Search is a cloud-based search and AI platform offered by Microsoft Azure.</li><li dir="ltr">It provides a set of APIs and tools for building scalable and intelligent search solutions.</li><li dir="ltr">Developers can use Azure Cognitive Search to create search experiences that enable users to find relevant information and insights from a wide range of data sources.</li><li dir="ltr">Azure Cognitive Search supports natural language processing, machine learning, and other advanced features that can help improve search accuracy and relevance.</li><li dir="ltr">It provides tools for data ingestion, indexing, and querying, making it easy to manage large volumes of data and make it available for search.</li><li dir="ltr">Azure Cognitive Search integrates with other Azure services such as Azure Functions, Azure Active Directory, and Azure DevOps.</li><li dir="ltr">With Azure Cognitive Search, developers can easily incorporate search into existing workflows and applications.</li></ul><h2 dir="ltr" style="color: rgb(85, 85, 85);">What is an ARM template?</h2><ul><li dir="ltr">An ARM template is a JSON file that defines one or more resources to be deployed to Azure.</li><li dir="ltr">ARM templates use a declarative syntax, meaning you define the desired end state of your resources rather than the specific steps required to create them.</li><li dir="ltr">ARM templates can be used to deploy a wide variety of Azure resources, including virtual machines, storage accounts, virtual networks, and more.</li><li dir="ltr">They can also be used to deploy resources from the Azure Marketplace, such as SaaS applications and IaaS offerings.</li><li dir="ltr">ARM templates are an important part of the Azure DevOps process, as they can be used to automate the deployment of resources as part of a CI/CD pipeline.</li><li dir="ltr">They can be used in conjunction with Azure Automation to automate the deployment and management of resources on a scheduled basis.</li></ul><h1 dir="ltr" style="color: rgb(85, 85, 85);">Architecture Diagram <img src="https://labresources.whizlabs.com/0fa11418b6e3b1dd9940b5ab59b65cc1/cognitive%20search_53_39.png" style="height: 466px; margin-left: 0px; margin-top: 0px; width: 800px;"></h1><h1 dir="ltr" style="color: rgb(85, 85, 85);">Task Details</h1><ol><li dir="ltr">Launching Lab Environment</li><li dir="ltr">Explore the ARM template</li><li dir="ltr">Deploy the ARM template</li><li dir="ltr">Verify your deployment</li></ol>

<h1 dir="ltr" style="margin-top: 0pt; margin-bottom: 0pt; color: rgb(85, 85, 85);"><span style="color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; text-decoration-line: underline; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap; font-family: Arial;">Lab Details</h1><ol style="margin-bottom: 0px; padding-inline-start: 48px;"><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">In this lab we will use Bicep to deploy Azure Cognitive Search resource in the Azure portal.</li><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Duration: <span style="background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;">30 minutes. </li></ol><h1 dir="ltr" style="margin-top: 0pt; margin-bottom: 0pt; color: rgb(85, 85, 85);">Introduction</h1><h2 dir="ltr" style="line-height: 1.2; color: rgb(85, 85, 85); margin-top: 0pt; margin-bottom: 0pt;"></h2><h2 style="color: rgb(85, 85, 85);"><span style="font-size: 16pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; text-decoration-line: underline; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;">What is Azure Cognitive Search?
</h2><ul style="margin-bottom: 0px; padding-inline-start: 48px;"><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Azure Cognitive Search is a cloud-based search service provided by Microsoft Azure.</li><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">It uses artificial intelligence and natural language processing to provide advanced search capabilities to applications.</li><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">It supports multiple languages, features, and search modes, including fuzzy search, synonym search, and geospatial search.</li><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Azure Cognitive Search is highly scalable and can handle large amounts of data, including structured, unstructured, and semi-structured data.</li><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">It can be easily integrated with other Azure services, such as Azure Storage and Azure Cosmos DB.</li><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Azure Cognitive Search provides powerful analytical tools for gaining insights into search usage and performance.</li><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">It enables developers to quickly create and deploy search solutions without having to write complex search algorithms from scratch.</li><li dir="ltr" aria-level="1" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Azure Cognitive Search is an excellent choice for developers who want to add sophisticated search capabilities to their applications without the need for building and maintaining a custom search infrastructure.</li></ul><h2 dir="ltr" style="color: rgb(85, 85, 85); margin-top: 0pt; margin-bottom: 0pt;">What is a Bicep file? </h2><ul style="margin-bottom: 0px; padding-inline-start: 48px;"><li aria-level="1" dir="ltr" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Bicep (short for "Bicep is a declarative language for describing Azure resources") is a domain-specific language (DSL) for Azure Resource Manager (ARM) templates.&nbsp;	</li><li aria-level="1" dir="ltr" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">A Bicep file is a file written in the Bicep language that defines the infrastructure and resources that make up an Azure deployment.	</li><li aria-level="1" dir="ltr" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Bicep files are used to create, deploy, and manage Azure resources using Infrastructure as Code (IaC) principles.&nbsp;	</li><li aria-level="1" dir="ltr" style="list-style-type: disc; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Bicep files are easier to read and maintain than ARM templates, as they use a more intuitive syntax and allow for modularization and reuse of code. </li></ul><h1 dir="ltr" style="margin-top: 0pt; margin-bottom: 0pt; color: rgb(85, 85, 85);"><span style="color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; text-decoration-line: underline; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;">Architecture Diagram <img src="https://labresources.whizlabs.com/807ff9358ed1e3e30c3be368480c5017/cognitive%20search%20bicep_13_17.png" width="25%" style="width: 816.2px; height: 505.492px;"> </h1> Task Details

<ol style="margin-bottom: 0px; padding-inline-start: 48px;"><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Sign in to Azure Portal	</li><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Explore the Bicep file	</li><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Deploy the Bicep file	</li><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Verify your deployment	</li></ol><h1 dir="ltr" style="margin-top: 20pt; margin-bottom: 6pt; line-height: 1.38; color: rgb(85, 85, 85);">Launching Lab Environment</h1><ol style="margin-bottom: 0px; padding-inline-start: 48px;"><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">To launch the lab environment, click on the <img alt="" src="https://labresources.whizlabs.com/3b2db94926f069a4e5058b17aea458e1/image11_05_10.png" style="width: 253px; height: 38px;"><span style="font-family: arial, helvetica, sans-serif; background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;"> button.	</li><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Please wait until the cloud environment is provisioned.	</li><li aria-level="1" dir="ltr" style="list-style-type: decimal; font-size: 12pt; font-family: Arial; color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre;">Once the lab is started, you will be provided with a <span style="font-family: arial, helvetica, sans-serif; background-color: transparent; font-weight: 700; font-style: italic; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;">username<span style="font-family: arial, helvetica, sans-serif; background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;"> and <span style="font-family: arial, helvetica, sans-serif; background-color: transparent; font-weight: 700; font-style: italic; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;">password<span style="font-family: arial, helvetica, sans-serif; background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;">. 	</li></ol><span style="color: rgb(0, 0, 0); background-color: transparent; font-weight: 700; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;">&nbsp;&nbsp;&nbsp;&nbsp;Note<span style="color: rgb(0, 0, 0); background-color: transparent; font-variant-numeric: normal; font-variant-east-asian: normal; font-variant-alternates: normal; vertical-align: baseline; white-space: pre-wrap;"> : You can only start one lab at a time.

<h1 style="color: rgb(85, 85, 85);">Lab Details&nbsp;</h1><ol><li>In this lab we will walk through the steps to Translate Text with Azure AI Translator.&nbsp;</li><li>Duration:&nbsp;30 minutes&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Introduction&nbsp;</h1><h2 style="color: rgb(85, 85, 85);">What is an Azure AI Translator?&nbsp;</h2><ul><li>Azure AI Translator is a service provided by Microsoft Azure that allows users to translate text between various languages.&nbsp;&nbsp;</li><li>It can automatically detect the source language and translate it into the desired target language using REST API calls.&nbsp;&nbsp;</li><li>The service can be integrated into applications to enable real-time translation and is particularly useful for multilingual support and content localization.&nbsp;</li></ul><h1 style="color: rgb(85, 85, 85);">Architecture Diagram&nbsp;</h1><img src="https://labresources.whizlabs.com/77700f4c553b1efa1c5f7b6c7cf1d328/1_28_30.jpg" style="border-width: 1px; border-style: solid; width: 796.958px; height: 600.4px;"><h1 style="color: rgb(85, 85, 85);">Task Details&nbsp;</h1><ol><li>Sign in to Azure Portal&nbsp;</li><li>Clone the repo into your Azure Cloud Shell&nbsp;</li><li>Provision an Azure AI Translator resource&nbsp;</li><li>Prepare to use Azure AI Translator&nbsp;</li><li>Detect language&nbsp;</li><li>Translate text&nbsp;</li><li>Validation test&nbsp;</li><li>Delete the Resources&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Launching Lab Environment&nbsp;</h1><ol><li>To launch the lab environment, click on the&nbsp;Start Lab&nbsp;button.&nbsp;</li><li>Please wait until the cloud environment is provisioned.&nbsp;</li><li>Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.&nbsp;</li></ol><blockquote>Note:&nbsp;You can only start one lab at a time.</blockquote>

<h1 style="color: rgb(85, 85, 85);">Lab Details&nbsp;</h1><h1 style="color: rgb(85, 85, 85);"><ol style="font-family: &quot;Source Sans Pro&quot;, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px;"><li>In this lab we will walk through the steps to Read Text in Images using Azure AI services multi-service account.&nbsp;</li><li>Duration:&nbsp;30 minutes&nbsp;</li></ol></h1><h1 style="color: rgb(85, 85, 85);">Introduction&nbsp;</h1><h2 style="color: rgb(85, 85, 85);">What is an Azure AI services multi-service account?&nbsp;</h2><h1 style="color: rgb(85, 85, 85);"><ul style="font-family: &quot;Source Sans Pro&quot;, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px;"><li>Centralizes management of Azure AI services like Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service.&nbsp;</li><li>Consolidates billing and resource allocation into a single account for cost efficiency.&nbsp;</li><li>Facilitates seamless scalability with easy addition or removal of AI services.&nbsp;</li><li>Provides integrated security with Azure Active Directory integration and role-based access control for enhanced governance and compliance.&nbsp;</li></ul></h1><h1 style="color: rgb(85, 85, 85);">Architecture Diagram&nbsp;</h1><h1 style="color: rgb(85, 85, 85);"><img src="https://labresources.whizlabs.com/330eb26e3d1959cc0489afbe5d37ddca/1_26_34.png" style="border-width: 1px; border-style: solid; width: 795.365px; height: 599.2px;"></h1><h1 style="color: rgb(85, 85, 85);">Task Details&nbsp;</h1><h1 style="color: rgb(85, 85, 85);"><ol style="font-family: &quot;Source Sans Pro&quot;, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px;"><li>Sign in to Azure Portal&nbsp;</li><li>Clone the repo into your Azure Cloud Shell&nbsp;</li><li>Provision an Azure AI Services resource&nbsp;</li><li>Prepare to use the Azure AI Vision SDK&nbsp;</li><li>Use the Read API to read text from an image&nbsp;</li><li>Use the Read API to read text from a document&nbsp;</li><li>Read handwritten text&nbsp;</li><li>Validation test&nbsp;</li><li>Delete the Resources&nbsp;</li></ol></h1><h1 style="color: rgb(85, 85, 85);">Launching Lab Environment&nbsp;</h1><h1 style="color: rgb(85, 85, 85);"><ol style="font-family: &quot;Source Sans Pro&quot;, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif; font-size: 14px;"><li>To launch the lab environment, click on the&nbsp;Start Lab&nbsp;button.&nbsp;</li><li>Please wait until the cloud environment is provisioned.&nbsp;</li><li>Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.&nbsp;</li></ol><blockquote style="font-family: &quot;Source Sans Pro&quot;, &quot;Helvetica Neue&quot;, Helvetica, Arial, sans-serif;">Note:&nbsp;You can only start one lab at a time.</blockquote></h1>

<h1 style="color: rgb(85, 85, 85);">Lab Details&nbsp;</h1><ol><li>In this lab we will walk through the steps to use an Azure AI Services Container.&nbsp;</li><li>Duration:&nbsp;30 minutes&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Prerequisites&nbsp;</h1><ul><li>VS Code&nbsp;</li><li>Docker Desktop&nbsp;</li></ul><h1 style="color: rgb(85, 85, 85);">Introduction&nbsp;</h1><h2 style="color: rgb(85, 85, 85);">What is an Azure AI services multi-service account?&nbsp;</h2><ul><li>Centralizes management of Azure AI services like Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service.&nbsp;</li><li>Consolidates billing and resource allocation into a single account for cost efficiency.&nbsp;</li><li>Facilitates seamless scalability with easy addition or removal of AI services.&nbsp;</li><li>Provides integrated security with Azure Active Directory integration and role-based access control for enhanced governance and compliance.&nbsp;</li></ul><h2 style="color: rgb(85, 85, 85);">What is an Azure Container Instance?&nbsp;</h2><ul><li>Azure Container Instances (ACI) allows organizations to deploy containerized Azure AI services on their own infrastructure.&nbsp;</li><li>ACI provides a way to host Azure AI services locally on Docker servers, Azure Container Instances, or Azure Kubernetes Services clusters.&nbsp;</li><li>Containerized Azure AI services in ACI require communication with an Azure-based Azure AI services account for billing purposes.&nbsp;</li><li>ACI grants organizations greater control over deployment configurations, allowing for custom solutions in authentication, scalability, and other areas.&nbsp;</li><li>ACI enables organizations to maintain more control over service infrastructure and data handling compared to fully managed Azure AI services.&nbsp;</li></ul><h1 style="color: rgb(85, 85, 85);">Architecture Diagram&nbsp;</h1><img src="https://labresources.whizlabs.com/433c317641c1fd359aab5e38cce82e9e/1_19_14.png" style="border-width: 1px; border-style: solid; width: 743.855px; height: 357.6px;"><h1 style="color: rgb(85, 85, 85);">Task Details&nbsp;</h1><ol><li>Sign in to Azure Portal&nbsp;</li><li>Clone the repository&nbsp;</li><li>Provision an Azure AI Services resource&nbsp;</li><li>Deploy and run a Text Analytics container&nbsp;</li><li>Use the container&nbsp;</li><li>Validation test&nbsp;</li><li>Delete the Resources&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Launching Lab Environment&nbsp;</h1><ol><li>To launch the lab environment, click on the&nbsp;Start Lab&nbsp;button.&nbsp;</li><li>Please wait until the cloud environment is provisioned.&nbsp;</li><li>Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.&nbsp;</li></ol><blockquote>Note:&nbsp;You can only start one lab at a time.</blockquote>

<h1>Lab Details</h1>

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&nbsp; &nbsp;1. In this lab, you will learn and test the capabilities of the Face service using a simple command-line application that runs in a cloud shell.

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&nbsp; &nbsp;2. Duration:&nbsp;45 minutes

<h1>Introduction</h1>

<h2>What is Azure Cognitive Services?</h2>

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<h1>Architecture Diagram 
<img src="https://play.whizlabs.com/frontend/web/media/task_id_11019/exploring_optical_character_recognition_51_04.png" style="height:396.17px; width:25%px" /></h1>

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<h1>Lab Details</h1>
&nbsp; &nbsp;1. In this lab, you will learn and test the capabilities of the Read API using a simple command-line application that runs in a cloud shell.
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<h1>Lab Details</h1>

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	In this lab, you will learn and test the capabilities of the Form recognizer service using a simple command-line application that runs in a cloud shell.
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<h1>Introduction</h1>

<h2>What is Azure Cognitive Services?</h2>

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	Azure Cognitive Services is a collection of helpful, sophisticated open APIs for cloud-based programs from Microsoft.&nbsp;
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	Azure Cognitive Services are related to intelligence related to the computer and the way humans behave with these computers. For example, these services allow humans to interact with the machines as if they have the intellectual ability to talk, think and respond to events accordingly.
	</li>
	<li>
	These services are very easy and convenient to use once you have a basic understanding of working with APIs. You don&rsquo;t need to be an expert in Machine Learning or Artificial Intelligence in order to consume these.&nbsp;
	</li>
	<li>
	Azure also offers client SDK in multiple programming languages such as C#, JavaScript, Python, etc. so that you can integrate these with your existing applications at ease.
	</li>
	<li>
	There are five main categories for Azure Cognitive Services that offer multiple services in each of the categories. These services are as follows:

	<ul>
		<li>
		Vision&nbsp;&ndash; Used mostly for image recognition
		</li>
		<li>
		Language&nbsp;&ndash; Used to identify natural language and learn from human interactions
		</li>
		<li>
		Speech&nbsp;&ndash; Used to recognize and convert speech to text and vice versa
		</li>
		<li>
		Decision&nbsp;&ndash; Used to identify patterns in data and take necessary actions
		</li>
		<li>
		Search&nbsp;&ndash; Used to integrate web search APIs with your existing applications
		</li>
	</ul>
	</li>
</ul>

<h1>Architecture Diagram 
<img src="https://play.whizlabs.com/frontend/web/media/task_id_11020/exploring_form_recognition.png" /></h1>

<h1>Task Details</h1>

<ol>
	<li>
	Launching Lab Environment
	</li>
	<li>
	Create a Cognitive Services resource
	</li>
	<li>
	Run Cloud Shell
	</li>
	<li>
	Configure and run a client application
	</li>
</ol>

<h1 dir="ltr" style="color: rgb(85, 85, 85);">Lab Details</h1><ol><li dir="ltr">In this lab,&nbsp;you will learn how to use a simple command-line application to see the Computer Vision service in action.</li><li dir="ltr">Duration:&nbsp;45 minutes</li></ol><h1 dir="ltr" style="color: rgb(85, 85, 85);">Introduction</h1><h2 dir="ltr" style="color: rgb(85, 85, 85);">What is Computer Vision?</h2><ul><li dir="ltr">Azure's Computer Vision services are a collection of cloud-based AI services that allow developers to add advanced computer vision capabilities to their applications without requiring expertise in machine learning or computer vision algorithms.</li><li dir="ltr">These services use machine learning algorithms to analyze and interpret visual data from images and videos, allowing developers to extract insights and valuable information from their data.</li><li dir="ltr">Azure's Computer Vision services include capabilities such as object detection, image classification, facial recognition, and optical character recognition (OCR), among others.</li><li dir="ltr">These services can be used to build a variety of applications, such as content moderation, visual search, fraud detection, and more.</li><li dir="ltr">Azure's Computer Vision services are designed to be easy to use and integrate into existing applications.</li><li dir="ltr">Developers can access these services through a simple REST API, which can be called from any programming language or platform.</li><li dir="ltr">Azure provides pre-built models and custom training options for developers who want to create their own models.</li><li dir="ltr">Azure's Computer Vision services are powered by Microsoft's world-class AI research and development, ensuring that they are always up-to-date with the latest advancements in computer vision and machine learning.</li><li dir="ltr">Overall, Azure's Computer Vision services provide developers with powerful tools for analyzing and interpreting visual data, enabling them to build innovative and intelligent applications with ease.</li></ul><h2 dir="ltr" style="color: rgb(85, 85, 85);">&nbsp;</h2><h1 dir="ltr" style="color: rgb(85, 85, 85);">Architecture Diagram</h1><img src="https://labresources.whizlabs.com/a10f25e7a0f4cc9ecfebb4695525a7dc/explore%20custom%20vision_33_11.png" style="height: 414px; margin-left: 0px; margin-top: 0px; width: 800px;"><h1 dir="ltr" style="color: rgb(85, 85, 85);">Task Details</h1><ol><li dir="ltr">Sign in to Azure Portal</li><li dir="ltr">Create a Cognitive Services resource</li><li dir="ltr">Run Cloud Shell</li><li dir="ltr">Configure and run a client application</li></ol><h1 dir="ltr" style="color: rgb(85, 85, 85);">Launching Lab Environment</h1><ol><li dir="ltr">To launch the lab environment, click on the&nbsp;<img src="https://labresources.whizlabs.com/f7549455ea3ff1fb5e9db1de2460ad4b/start%20lab_06_07.png" style="height: 35.9782px; width: 238.012px;">&nbsp;button.</li><li dir="ltr">Please wait until the cloud environment is provisioned.</li><li dir="ltr">Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.</li></ol><div style="background: rgb(238, 238, 238); border: 1px solid rgb(204, 204, 204); padding: 5px 10px;">Note&nbsp;: You can only start one lab at a time.</div>

<h1 style="color: rgb(85, 85, 85);">Lab Details</h1><ol><li>In this lab we will walk through the steps to Set up semantic ranker.</li><li>Duration:&nbsp;30 minutes</li></ol><h1 style="color: rgb(85, 85, 85);">Introduction</h1><h2 style="color: rgb(85, 85, 85);">What is Semantic Ranker?</h2><ul><li>Semantic ranker utilizes deep neural networks to provide search results based on contextual meaning, surpassing traditional lexical analysis.</li><li>It comprehends the underlying intent of queries, offering more relevant results by delving into the contextual nuances of language.</li><li>Semantic ranker enhances user satisfaction by delivering results closely aligned with their search intent, thereby improving the overall user experience.</li><li>The advanced capabilities of semantic ranker may lead to additional charges, reflecting the investment in cutting-edge technology and computational resources.</li></ul><h1 style="color: rgb(85, 85, 85);">Architecture Diagram</h1><img src="https://labresources.whizlabs.com/203e000730981611b804b6c094d03e11/1_43_25.jpg" style="border-width: 1px; border-style: solid; width: 744.38px; height: 495.2px;"><h1 style="color: rgb(85, 85, 85);">Task Details</h1><ol><li>Sign in to Azure Portal</li><li>Enable semantic ranker</li><li>Import a sample index</li><li>Configure semantic ranking</li><li>Validation test</li><li>Delete the Resources</li></ol><h1 style="color: rgb(85, 85, 85);">Launching Lab Environment</h1><ol><li>To launch the lab environment, click on the&nbsp;Start Lab&nbsp;button.</li><li>Please wait until the cloud environment is provisioned.</li><li>Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.</li></ol><blockquote>Note:&nbsp;You can only start one lab at a time.</blockquote>

<h1 dir="ltr" style="color: rgb(85, 85, 85);">Lab Details</h1><ol><li dir="ltr">In this lab we will walk through the steps&nbsp;to create an Ubuntu Data Science Virtual Machine using an Azure Resource Manager template.</li><li dir="ltr">Duration:&nbsp;45&nbsp;minutes.</li></ol><h1 dir="ltr" style="color: rgb(85, 85, 85);">Introduction</h1><h2 dir="ltr" style="color: rgb(85, 85, 85);">What is Ubuntu Data Science VM?</h2><ul><li dir="ltr">The Ubuntu DSVM is a pre-configured virtual machine image provided by Microsoft Azure.</li><li dir="ltr">It is designed for data scientists and developers to quickly set up a working environment for data science and machine learning projects.</li><li dir="ltr">The DSVM comes with a suite of popular data science tools pre-installed and pre-configured, including Jupyter notebooks, RStudio, Python, TensorFlow, PyTorch, and more.</li><li dir="ltr">It also includes pre-installed GPU drivers and libraries for users who need to train deep learning models on GPUs.</li><li dir="ltr">The DSVM includes Ubuntu Linux and a variety of other system-level tools for managing and deploying data science workloads, including Docker, Kubernetes, and Azure Machine Learning.</li><li dir="ltr">The DSVM provides a convenient and easy-to-use environment for data scientists and developers to quickly get started with data science projects in Azure.</li></ul><h2 dir="ltr" style="color: rgb(85, 85, 85);">What is an ARM template?</h2><ul><li dir="ltr">An ARM template is a JSON file that defines one or more resources to be deployed to Azure.</li><li dir="ltr">ARM templates use a declarative syntax, meaning you define the desired end state of your resources rather than the specific steps required to create them.</li><li dir="ltr">ARM templates can be used to deploy a wide variety of Azure resources, including virtual machines, storage accounts, virtual networks, and more.</li><li dir="ltr">They can also be used to deploy resources from the Azure Marketplace, such as SaaS applications and IaaS offerings.</li><li dir="ltr">ARM templates are an important part of the Azure DevOps process, as they can be used to automate the deployment of resources as part of a CI/CD pipeline.</li><li dir="ltr">They can be used in conjunction with Azure Automation to automate the deployment and management of resources on a scheduled basis.</li></ul><h1 dir="ltr" style="color: rgb(85, 85, 85);">Architecture Diagram <img src="https://labresources.whizlabs.com/cde676c587a2c499c660f1479efb3821/ubuntun%20dsvm_13_26.png" style="height: 466px; margin-left: 0px; margin-top: 0px; width: 800px;"></h1><h1 dir="ltr" style="color: rgb(85, 85, 85);">Task Details</h1><ol><li dir="ltr">Launching Lab Environment</li><li dir="ltr">Explore the ARM template</li><li dir="ltr">Deploy the ARM template</li><li dir="ltr">Verify your deployment</li></ol>

<h1 style="color: rgb(85, 85, 85);">Lab Details&nbsp;</h1><ol><li>In this lab we will walk through the steps to analyze text content with Azure AI Content Safety services.&nbsp;</li><li>Duration:&nbsp;30 minutes&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Introduction&nbsp;</h1><h2 style="color: rgb(85, 85, 85);">What is a Content Safety resource?&nbsp;</h2><ul><li>Automatically identifies and removes harmful content like hate speech and violence.&nbsp;</li><li>Provides clear rules on acceptable content for creators and consumers.&nbsp;</li><li>Allows users to report inappropriate content for review and action.&nbsp;</li><li>Offers tips and information on online safety and responsible content creation.&nbsp;</li><li>Regularly updates tools and policies to address evolving online threats.&nbsp;</li></ul><h1 style="color: rgb(85, 85, 85);">Architecture Diagram&nbsp;</h1><img alt="" data-cke-saved-src="https://labresources.whizlabs.com/70c2e98c94585d03f8b27ca6e451e186/content_safety_22_13.jpeg" src="https://labresources.whizlabs.com/70c2e98c94585d03f8b27ca6e451e186/content_safety_22_13.jpeg" style="border-width: 1px; border-style: solid; cursor: default; color: rgb(51, 51, 51); font-family: sans-serif, Arial, Verdana, &quot;Trebuchet MS&quot;; font-size: 13px; width: 800px; height: 603px;"> <h1 style="color: rgb(85, 85, 85);">Task Details&nbsp;</h1><ol><li>Sign in to Azure Portal&nbsp;</li><li>Create a Content Safety resource&nbsp;</li><li>Create environment variables&nbsp;</li><li>Analyze text content&nbsp;</li><li>Validation test&nbsp;</li><li>Delete the Resources&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Launching Lab Environment&nbsp;</h1><ol><li>To launch the lab environment, click on the&nbsp;Start Lab&nbsp;button.&nbsp;</li><li>Please wait until the cloud environment is provisioned.&nbsp;</li><li>Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.&nbsp;</li></ol><blockquote>Note :&nbsp;You can only start one lab at a time.</blockquote>

<h1 style="color: rgb(85, 85, 85);">Lab Details&nbsp;</h1><ol><li>In this lab we will walk through the steps to analyze image content with Azure AI Content Safety services.&nbsp;</li><li>Duration:&nbsp;30 minutes&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Introduction&nbsp;</h1><h2 style="color: rgb(85, 85, 85);">What is a Content Safety resource?&nbsp;</h2><ol><li>Automatically identifies and removes harmful content like hate speech and violence.&nbsp;</li><li>Provides clear rules on acceptable content for creators and consumers.&nbsp;</li><li>Allows users to report inappropriate content for review and action.&nbsp;</li><li>Offers tips and information on online safety and responsible content creation.&nbsp;</li><li>Regularly updates tools and policies to address evolving online threats.&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Architecture Diagram&nbsp;</h1><h1 style="color: rgb(85, 85, 85); text-align: center;"><img alt="" data-cke-saved-src="https://labresources.whizlabs.com/70c2e98c94585d03f8b27ca6e451e186/content_safety_22_13.jpeg" src="https://labresources.whizlabs.com/70c2e98c94585d03f8b27ca6e451e186/content_safety_22_13.jpeg" style="border-width: 1px; border-style: solid; cursor: default; color: rgb(51, 51, 51); font-family: sans-serif, Arial, Verdana, &quot;Trebuchet MS&quot;; font-size: 13px; width: 800px; height: 603px;"> </h1><h1 style="color: rgb(85, 85, 85);">Task Details&nbsp;</h1><ol><li>Sign in to Azure Portal&nbsp;</li><li>Create a Content Safety resource&nbsp;</li><li>Create environment variables&nbsp;</li><li>Analyze image content&nbsp;</li><li>Validation test&nbsp;</li><li>Delete the Resources&nbsp;</li></ol><h1 style="color: rgb(85, 85, 85);">Launching Lab Environment&nbsp;</h1><ol><li>To launch the lab environment, click on the&nbsp;Start Lab&nbsp;button.&nbsp;</li><li>Please wait until the cloud environment is provisioned.&nbsp;</li><li>Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.&nbsp;</li></ol><blockquote>Note :&nbsp;You can only start one lab at a time.&nbsp;</blockquote>

<h1 dir="ltr" style="color: rgb(85, 85, 85);">Prerequisites</h1><ol><li dir="ltr">Knowledge of the listed Azure services:<ul><li dir="ltr">Azure Cognitive Services</li></ul></li><li dir="ltr">Laptop</li><li dir="ltr">Internet Browser</li><li dir="ltr">Internet Connection</li></ol><h1 dir="ltr" style="color: rgb(85, 85, 85);">Challenge Instructions</h1><ol><li dir="ltr">Region: Make sure to use the&nbsp;East US&nbsp;region to create all the resources.</li><li dir="ltr">You will be provided with the requirements of the challenge. If you are new to Azure Cloud, we recommend you to go through our hands-on Labs before taking this challenge. If you couldn't complete this challenge successfully, you can try performing this&nbsp;<a href="https://www.whizlabs.com/labs/exploring-form-recognition">guided lab</a>&nbsp;then try again.</li><li dir="ltr">Challenge Duration:&nbsp;45 minutes</li></ol><h1 dir="ltr" style="color: rgb(85, 85, 85);">Launching Challenge&nbsp;Environment</h1><ol><li dir="ltr">To launch the challenge environment, click on the&nbsp;Start Challenge&nbsp;button.</li><li dir="ltr">Please wait until the cloud environment is provisioned.</li><li dir="ltr">Once the challenge&nbsp;creation process is completed, you will be provided a&nbsp;username&nbsp;and&nbsp;password.</li></ol><div style="background: rgb(238, 238, 238); border: 1px solid rgb(204, 204, 204); padding: 5px 10px;">Note&nbsp;: You can only start one challenge at a time.</div>

<h2 dir="ltr">What is the AI 900 Course?</h2>
AI-900: Microsoft Azure AI Fundamentals course would help you to learn Machine Learning on (ML) and Artificial Intelligence (AI). It prepares you to pass the AI 900 certification on the first attempt. We provide 130+ high-quality practice test questions with detailed explanations. In addition, there are 40+ video lectures and 16+ hands-on labs that help you to practice in a real-time environment.&nbsp;
We cover all the essential Azure AI solutions you need.
<ul>
<li dir="ltr" aria-level="1">
Getting started with Azure AI solutions
</li>
<li dir="ltr" aria-level="1">
Explore visual tools for Machine Learning (ML)
</li>
<li dir="ltr" aria-level="1">
Explore Computer Vision
</li>
<li dir="ltr" aria-level="1">
Explore Natural Language Processing (NLP)
</li>
<li dir="ltr" aria-level="1">
Generative AI Workloads
</li>
</ul>

Microsoft Azure Exam AI-900 Certification

AI 900 Cloud Sandbox is a real time Azuure environment. This sandbox provisioned with the Azure services that are required to pass the AI 900 certification exam. This is unlimited access to practice, test and experiment your ideas to prepare for Azure AI Fundamentals exam.
If you find any services that are not supported in our Sandbox, please send a e-mail to <a href="mailto:support@whizlabs.com">support@whizlabs.com</a>.&nbsp;

AI 900 Practice Tests are created by Azure AI Certified Experts. The questions in these practices tests are close to the real exam questions. These questions will guarantee you to pass the AI 900 exam in the first attempt.

Practice Tests

Millions of aspirants have become certified with our practice tests. Give your preparation a new edge with Whizlabs Microsoft Azure AI-900 Practice Tests.

Microsoft Azure AI-900 Practice Tests - Whizlabs

AI 900 Video Lectures are created by Azure AI Certified Experts.&nbsp;You can use these videos to learn every concepts that are covered in the AI 900 exam syllabus.

Online Course

Have helped over 1.5 million Azure professionals in their certification exam preparation. Enrol now for Microsoft Azure Exam AI-900 Online Course.

Microsoft Azure AI-900 Online Course - Whizlabs

These hands-on labs or guided labs are created by Azure AI Certified Experts. These labs would provide a good learning experience and teach you on how to implement Azure AI solutions in real time that are covered in the AI 900 exam. Hands-on labs are step-by-step guide to perform any tasks in the Azure real-time environment.

Free Test

Preparing for Microsoft Azure Exam AI-900 certification exam? Check your current preparation level with Microsoft Azure Exam AI-900 free test. Try now!

Microsoft Azure Exam AI-900 Free Test - Whizlabs

AI-900 Certification : Microsoft Azure AI Fundamentals

The Microsoft Azure AI Fundamentals course validates your machine learning and artificial intelligence skills to pass your AI -900 Certification on the first attempt!

<div>
AI-900: Microsoft Azure AI Fundamentals course would help you to learn Machine Learning (ML) and Artificial Intelligence (AI). This training prepare you to pass the AI 900 certification in first attempt by providing 130+ high-quality practice test questions with detailed explanations, 40+ videos lectures and 16+ hands-on-labs that helps you to practice in real-time environment.&nbsp;
Whizlabs course covers all the essentials of Azure AI solutions that are required for the exam. The following are the essential services that have very detailed coverage in this course:
<ul>
<li>Getting started with Azure AI solutions</li>
<li>Explore visual tools for Machine Learning (ML)</li>
<li>Explore Computer Vision</li>
<li>Explore Natural Language Processing (NLP)</li>
<li>Generative AI Workloads</li>
</ul>
Updated with latest changes on the AI 900 Certification exam!!!
This exam has minor updates to it's objectives on April 24, 2024.
</div>

Practice Questions,  Videos & Labs

2 Full-length Mock Exams (100+ unique Microsoft Azure AI-900 Certification Exam practice questions)

6+ hours of Training Videos for all the certification exam objectives. Our easy-to-understand explanation, even for the difficult concepts

Our support team consists of Azure Experts, ready to clarify all your questions.

Get to know from our learners in, AI-900: Microsoft Azure AI Fundamentals Exam Feedback from Our Customers.

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adamo bosco

Nice course

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Sanket Terdal

Practice test and handson Labs are very helpful

Very Helpful

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krishna mishra

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Comprehensive and Effective

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I've recently joined Whizlab, I've been very impressed with its features. The platform is exceptional in providing content that is both extensive and engaging.

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Shyamala 

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I took a course on Udemy and it helped me get an idea of the material. Bought these practice exams and it greatly help narrow down my studies. I took each exam twice. Read through the material on Microsoft Learn where I was lacking. Passed the exam easily.

Works

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I bought AI 900 Practice tests and practiced all tests twice. 25% of questions in exam came from these tests. I passed exam today with 900+ score.. Thanks Whizlab team.

Excellent Practice Tests

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I only purchased the practice tests. They were helpful. Its hard to gauge how helpful they were. I also used the Microsoft Enterprise practice tests and took the online course.. I ended up with a 90% on the exam.

Decent

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jimmy  Modi

Purchased AI-900 Videos .Awesome presentation. Very specific to the core concept

Awesome product-AI-900

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Bruce McCormack

Whizlabs team - great job with these practice tests. Passed w/90% on the first try. Good encyclopedic mix of questions creating foundational knowledge for the exam.