Merge pull request #50469 from GraemeMalcolm/main

Refresh Content Understanding module

Author: JillGrant615

learn-pr/wwl-data-ai/analyze-content-ai/01-introduction.yml

@@ -1,16 +1,16 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.analyze-content-ai.introduction
-title: Introduction
-metadata:
-  title: Introduction
-  description: Introduction to analyzing content with Azure AI Content Understanding.
-  author: wwlpublish
-  ms.author: gmalc
-  ms.date: 01/13/2025
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 1
-content: |
-  [!include[](includes/01-introduction.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.analyze-content-ai.introduction
+title: Introduction
+metadata:
+  title: Introduction
+  description: Introduction to analyzing content with Azure AI Content Understanding.
+  author: wwlpublish
+  ms.author: gmalc
+  ms.date: 05/15/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 1
+content: |
+  [!include[](includes/01-introduction.md)]
+

learn-pr/wwl-data-ai/analyze-content-ai/02-content-understanding.yml

@@ -1,16 +1,16 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.analyze-content-ai.content-understanding
-title: What is Azure AI Content Understanding?
-metadata:
-  title: What is Azure AI Content Understanding?
-  description: Introduction to Azure AI Content Understanding?.
-  author: wwlpublish
-  ms.author: gmalc
-  ms.date: 01/13/2025
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 5
-content: |
-  [!include[](includes/02-content-understanding.md)]
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.analyze-content-ai.content-understanding
+title: What is Azure AI Content Understanding?
+metadata:
+  title: What is Azure AI Content Understanding?
+  description: Introduction to Azure AI Content Understanding?.
+  author: wwlpublish
+  ms.author: gmalc
+  ms.date: 05/15/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 5
+content: |
+  [!include[](includes/02-content-understanding.md)]
+

learn-pr/wwl-data-ai/analyze-content-ai/03-create-analyzer.yml

@@ -6,7 +6,7 @@ metadata:
   description: Use the Azure AI Foundry portal to create a Content Understanding analyzer.
   author: wwlpublish
   ms.author: gmalc
-  ms.date: 01/13/2025
+  ms.date: 05/15/2025
   ms.topic: unit
   ms.collection:
     - wwl-ai-copilot

learn-pr/wwl-data-ai/analyze-content-ai/04-use-api.yml

@@ -6,7 +6,7 @@ metadata:
   description: Use the REST API to create a client application for an analyzer.
   author: wwlpublish
   ms.author: gmalc
-  ms.date: 01/13/2025
+  ms.date: 05/15/2025
   ms.topic: unit
   ms.collection:
     - wwl-ai-copilot

learn-pr/wwl-data-ai/analyze-content-ai/05-exercise.yml

@@ -1,15 +1,15 @@
 ### YamlMime:ModuleUnit
 uid: learn.wwl.analyze-content-ai.exercise
-title: Exercise - Analyze content with Azure AI Content Understanding
+title: Exercise - Extract information from multimodal content
 metadata:
-  title: Exercise - Analyze content with Azure AI Content Understanding
-  description: Use Azure AI Content Understanding to build and consume an analyzer.
+  title: Exercise - Extract information from multimodal content
+  description: Use Azure AI Content Understanding to extract information from documents, images, audio files, and videos.
   author: wwlpublish
   ms.author: gmalc
-  ms.date: 01/13/2025
+  ms.date: 05/15/2025
   ms.topic: unit
   ms.collection:
     - wwl-ai-copilot
-durationInMinutes: 30
+durationInMinutes: 40
 content: |
   [!include[](includes/05-exercise.md)]

learn-pr/wwl-data-ai/analyze-content-ai/06-knowledge-check.yml

@@ -1,49 +1,49 @@
-### YamlMime:ModuleUnit
-uid: learn.wwl.analyze-content-ai.knowledge-check
-title: Module assessment
-metadata:
-  title: Module assessment
-  description: Check your knowledge.
-  author: wwlpublish
-  ms.author: gmalc
-  ms.date: 01/13/2025
-  ms.topic: unit
-  ms.collection:
-    - wwl-ai-copilot
-durationInMinutes: 3
-quiz:
-  questions:
-  - content: "What kinds of AI solution is Azure AI Content Understanding designed to help you build?"
-    choices:
-    - content: "Chatbots that automatically translate between multiple spoken and written languages."
-      isCorrect: false
-      explanation: "Incorrect. Azure AI Content Understanding is not designed to build translation chatbots."
-    - content: "Analyzers that extract information from documents, images, videos, and audio files."
-      isCorrect: true
-      explanation: "Correct. Azure AI Content Understanding is designed to build content analyzers."
-    - content: "Image generators that create visualizations based on descriptions."
-      isCorrect: false
-      explanation: "Incorrect. Azure AI Content Understanding is not designed to build image generators."
-  - content: "Which graphical tool should you use to create an Azure AI Content Understanding project?"
-    choices:
-    - content: "Microsoft Visual Studio."
-      isCorrect: false
-      explanation: "Incorrect. While you could use the REST API from Visual Studio to create a Content Understanding analyzer, it is not the best tool for creating a project."
-    - content: "Azure Machine Learning studio."
-      isCorrect: false
-      explanation: "Incorrect. Azure Machine learning studio is not a tool for working with Content Udnerstanding projects."
-    - content: "Azure AI Foundry portal."
-      isCorrect: true
-      explanation: "Correct. Azure AI Foundry portal provides a visual interface for creating Content Understanding projects."
-  - content: "After creating a Content Understanding project, what should you define for the information you want to extract from content?"
-    choices:
-    - content: "A schema."
-      isCorrect: true
-      explanation: "Correct. A schema is used to define the information your analyzer will extract."
-    - content: "An index."
-      isCorrect: false
-      explanation: "Incorrect. You do not need to create an index for a Content Understanding analyzer."
-    - content: "A cluster."
-      isCorrect: false
-      explanation: "Incorrect. You do not need to create a cluster to use Content Understanding."
-
+### YamlMime:ModuleUnit
+uid: learn.wwl.analyze-content-ai.knowledge-check
+title: Module assessment
+metadata:
+  title: Module assessment
+  description: Check your knowledge.
+  author: wwlpublish
+  ms.author: gmalc
+  ms.date: 05/15/2025
+  ms.topic: unit
+  ms.collection:
+    - wwl-ai-copilot
+durationInMinutes: 3
+quiz:
+  questions:
+  - content: "What kinds of AI solution is Azure AI Content Understanding designed to help you build?"
+    choices:
+    - content: "Chatbots that automatically translate between multiple spoken and written languages."
+      isCorrect: false
+      explanation: "Incorrect. Azure AI Content Understanding isn't designed to build translation chatbots."
+    - content: "Analyzers that extract information from documents, images, videos, and audio files."
+      isCorrect: true
+      explanation: "Correct. Azure AI Content Understanding is designed to build content analyzers."
+    - content: "Image generators that create visualizations based on descriptions."
+      isCorrect: false
+      explanation: "Incorrect. Azure AI Content Understanding is not designed to build image generators."
+  - content: "Which graphical tool should you use to create an Azure AI Content Understanding project?"
+    choices:
+    - content: "Microsoft Visual Studio."
+      isCorrect: false
+      explanation: "Incorrect. While you could use the REST API from Visual Studio to create a Content Understanding analyzer, it isn't the best tool for creating a project."
+    - content: "Azure Machine Learning studio."
+      isCorrect: false
+      explanation: "Incorrect. Azure Machine Learning studio isn't a tool for working with Content Understanding projects."
+    - content: "Azure AI Foundry portal."
+      isCorrect: true
+      explanation: "Correct. Azure AI Foundry portal provides a visual interface for creating Content Understanding projects."
+  - content: "What should you define for the information you want to extract from content?"
+    choices:
+    - content: "A schema."
+      isCorrect: true
+      explanation: "Correct. A schema is used to define the information your analyzer will extract."
+    - content: "An index."
+      isCorrect: false
+      explanation: "Incorrect. You don't need to create an index for a Content Understanding analyzer."
+    - content: "A cluster."
+      isCorrect: false
+      explanation: "Incorrect. You don't need to create a cluster to use Content Understanding."
+

learn-pr/wwl-data-ai/analyze-content-ai/07-summary.yml

@@ -6,7 +6,7 @@ metadata:
   description: Reflect on what you've learned about Azure AI Content Understanding.
   author: wwlpublish
   ms.author: gmalc
-  ms.date: 01/13/2025
+  ms.date: 05/15/2025
   ms.topic: unit
   ms.collection:
     - wwl-ai-copilot

learn-pr/wwl-data-ai/analyze-content-ai/includes/01-introduction.md

@@ -2,7 +2,9 @@ Organizations today rely on information that is often locked up in content asset
 
 Azure AI Content Understanding is a multimodal service that simplifies the creation of AI-powered analyzers that can extract information from content in practically any format.
 
-In this module, you'll explore the capabilities of Azure AI Content Understanding, and learn how to use it to build and consume analyzers.
+![Diagram of Azure AI Content Understanding extracting information from documents, audio files, videos, and images.](../media/content-understanding.png)
+
+In this module, you'll explore the capabilities of Azure AI Content Understanding, and learn how to use it to build custom analyzers.
 
 > [!NOTE]
 > Azure AI Content Understanding is currently in public preview. Details described in this module are subject to change.

learn-pr/wwl-data-ai/analyze-content-ai/includes/02-content-understanding.md

@@ -29,6 +29,6 @@ Analysis of audio enables you to automate tasks like summarizing conference call
 
 ### Video
 
-Video accounts for a large volume of the data captured today, and you can use Content Understanding to analyze and extract insights from video to support many scenarios. For example, to summarize and extract key points from presentations or to detect the presence of specific activity in security footage.
+Video accounts for a large volume of the data captured today, and you can use Content Understanding to analyze and extract insights from video to support many scenarios. For example, to extract key points from video conference recordings, to summarize presentations, or to detect the presence of specific activity in security footage.
 
 ![Screenshot of an video file being analyzed by Content Understanding.](../media/video-analysis.png)

learn-pr/wwl-data-ai/analyze-content-ai/includes/03-create-analyzer.md

@@ -4,31 +4,31 @@ The high-level process for creating a Content Understanding solution includes th
 
 ![Diagram of a sample document being used to create a schema for an analyzer that is consumed by a client application.](../media/analyzer.png)
 
-1. Provision an Azure AI services resource.
-1. Define a schema for the information to be extracted. This can be based on a content sample and an analyzer template.
+1. Create an Azure AI services resource.
+1. Define a Content Understanding schema for the information to be extracted. This can be based on a content sample and an analyzer template.
 1. Build an analyzer based on the completed schema.
-1. Use the Content Understanding REST interface to submit new content for analysis and retrieve the extracted data.
+1. Use the analyzer to extract or generate fields from new content.
 
 Numerous analyzer templates are provided to help you develop an appropriate analyzer for your needs quickly. Additionally, because of the generative AI capabilities of Content Understanding, you can use minimal training data to define a schema by example. In many cases, the service accurately identifies the data values in the sample content that map to the schema elements automatically, though you can also explicitly label fields in content such as documents to improve the performance of your analyzer.
 
 ## Creating an analyzer with Azure AI Foundry
 
-While you can provision an Azure AI services resource and develop a complete Content Understanding solution through the REST API, the preferred approach for AI development projects is to use Azure AI Foundry. Specifically, you can use the Azure AI Foundry portal to create a Content Understanding project, define a schema, and build and test an analyzer.
+While you can provision an Azure AI services resource and develop a complete Content Understanding solution through the REST API, the preferred approach for AI development projects is to use Azure AI Foundry. Specifically, you can use the Azure AI Foundry portal to create a project, define a Content Understanding schema, and build and test an analyzer.
 
 ### Creating a Content Understanding project
 
-In Azure AI Foundry, you can create a Content Understanding project in an existing AI hub, or you can create a new hub as you create the project. In addition to the AI hub itself, creating a hub provisions the Azure resources needed to support one or more projects; including an Azure AI services resource, storage, and a key vault resource to store sensitive details like credentials and keys.
+In Azure AI Foundry, you can create a project in an existing AI hub, or you can create a new hub as you create the project. In addition to the AI hub itself, creating a hub provisions the Azure resources needed to support one or more projects; including an Azure AI services resource, storage, and a key vault resource to store sensitive details like credentials and keys.
 
-![Screenshot of the Create new Content Understanding project user interface in Azure AI Foundry.](../media/new-project.png)
+![Screenshot of the Create new project user interface in Azure AI Foundry.](../media/new-project.png)
 
 > [!NOTE]
-> Content Understanding projects can only be created in Azure locations where the service is supported. When creating a new hub as part of a new Content Understanding project, only supported locations are listed. For more information, see **[Content Understanding region and language support](/azure/ai-services/content-understanding/language-region-support)**.
+> Content Understanding schemas can only be created in Azure locations where the service is supported. For more information, see **[Content Understanding region and language support](/azure/ai-services/content-understanding/language-region-support)**.
 
 ### Defining a schema
 
 After creating a project, the first step in building an analyzer is to define a schema for the content the analyzer will process, and the information it will extract. Azure AI Foundry provides a schema editor interface in which you can upload a file (document, image, audio, or video) on which the schema should be based. You can then apply an appropriate schema template and define the specific fields you want the analyzer to identify.
 
-[ ![Screenshot of the Define schema user interface in Azure AI Foundry.](../media/define-schema.png) ](../media/define-schema-large.png)
+![Screenshot of the Define schema user interface in Azure AI Foundry.](../media/define-schema.png)
 
 > [!NOTE]
 > The templates and field types available in a schema depend on the content type of the file on which the schema is based. Some content types support additional optional functionality, such as extracting barcodes and formulae from text in documents. For more information about using Content Understanding with different content types, see the following articles in the product documentation:
@@ -40,9 +40,9 @@ After creating a project, the first step in building an analyzer is to define a
 
 ### Testing
 
-You can test the analyzer schema at any time during the development process by running analysis on the sample file used to define the schema or other uploaded files. The test results include the extracted field values as well as the JSON format output returned by the analyzer to client applications.
+You can test the analyzer schema at any time during the development process by running analysis on the sample file used to define the schema or other uploaded files. The test results include the extracted field values and the JSON format output returned by the analyzer to client applications.
 
-![Screenshot of the Test analyzer user interface in Azure AI Foundry.](../media/test-analyzer.png)
+![Screenshot of the Test analyzer user interface in Azure AI Foundry.](../media/document-analysis.png)
 
 ### Building an analyzer