Fix 'this Learning Path' link terminology

Copilot · jasonrandrews · Copilot · commit 133caf7034e1 · 2025-12-18T21:42:10.000Z
Co-authored-by: jasonrandrews &lt;4744588+jasonrandrews@users.noreply.github.com&gt;
diff --git a/content/learning-paths/laptops-and-desktops/win_aws_iot_dynamodb/how-to-1.md b/content/learning-paths/laptops-and-desktops/win_aws_iot_dynamodb/how-to-1.md
@@ -7,7 +7,7 @@ weight: 3
 layout: "learningpathall"
 ---
 ## Before you begin
-Before you begin, prepare the weather station emulator and connect it to AWS IoT Core by completing this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot). 
+Before you begin, prepare the weather station emulator and connect it to AWS IoT Core by completing [Create IoT applications with Windows on Arm and AWS IoT Core](/learning-paths/laptops-and-desktops/win_aws_iot). 
 ## Create the rule
 Start by creating the rule: 
 
diff --git a/content/learning-paths/laptops-and-desktops/win_aws_iot_lambda/create-rule.md b/content/learning-paths/laptops-and-desktops/win_aws_iot_lambda/create-rule.md
@@ -7,7 +7,7 @@ weight: 4
 layout: "learningpathall"
 ---
 ## Before you begin
-Before you begin, prepare the weather station emulator and connect it to AWS IoT Core by completing this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot). Note that this Learning Path also includes the rule created in the [Learning Path about Amazon DynamoDB for IoT applications running on Arm64](/learning-paths/laptops-and-desktops/win_aws_iot_dynamodb).
+Before you begin, prepare the weather station emulator and connect it to AWS IoT Core by completing [Create IoT applications with Windows on Arm and AWS IoT Core](/learning-paths/laptops-and-desktops/win_aws_iot). Note that this Learning Path also includes the rule created in [Use Amazon DynamoDB for your IoT applications running on Arm64](/learning-paths/laptops-and-desktops/win_aws_iot_dynamodb).
 
 ## Create the rule
 Start by creating the rule: 
diff --git a/content/learning-paths/laptops-and-desktops/win_aws_iot_lambda/implement-lambda.md b/content/learning-paths/laptops-and-desktops/win_aws_iot_lambda/implement-lambda.md
@@ -262,7 +262,7 @@ Click the *Confirm subscription* link. Then, invoke the *temperature-high-level*
 
 ![fig21](figures/21.webp)
 
-Now, you can start the weather station emulator you created in this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot/). Observe the values generated by the emulator. When the temperature exceeds the threshold of 35, you will receive an email notification:
+Now, you can start the weather station emulator you created in [Create IoT applications with Windows on Arm and AWS IoT Core](/learning-paths/laptops-and-desktops/win_aws_iot/). Observe the values generated by the emulator. When the temperature exceeds the threshold of 35, you will receive an email notification:
 
 ![fig22](figures/22.webp)
 
diff --git a/content/learning-paths/laptops-and-desktops/win_aws_iot_s3/add-lambda.md b/content/learning-paths/laptops-and-desktops/win_aws_iot_s3/add-lambda.md
@@ -9,7 +9,7 @@ layout: "learningpathall"
 
 ### AWS Lambda
 
-You will now use the AWS Lambda console to retrieve the AWS Lambda endpoint for the static website. Before you begin make sure to prepare the `GetAverageTemperature` AWS Lambda function as explained in this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb/). Then proceed as follows:
+You will now use the AWS Lambda console to retrieve the AWS Lambda endpoint for the static website. Before you begin make sure to prepare the `GetAverageTemperature` AWS Lambda function as explained in [Integrate AWS Lambda with DynamoDB for IoT applications running Windows on Arm](/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb/). Then proceed as follows:
 1. Go to the AWS Lambda console, and click the `GetAverageTemperature` Lambda function.
 2. In the Lambda function dashboard, click the **Configuration** tab and then the **Function URL** as shown below:
 
diff --git a/content/learning-paths/laptops-and-desktops/win_aws_iot_s3/background.md b/content/learning-paths/laptops-and-desktops/win_aws_iot_s3/background.md
@@ -14,4 +14,4 @@ In addition to its core storage capabilities, Amazon S3 can also be used for sta
 
 Amazon S3 provides Software Development Kits (SDKs) that simplify the integration of S3 into applications by providing comprehensive APIs that facilitate file uploads, downloads, and management directly from the codebase. The AWS CLI allows developers and administrators to interact with S3 from the command line, accelerating many programming and administrative tasks. 
 
-In this Learning Path, you will learn how to use Amazon S3 to host a static website that interacts with AWS Lambda. Specifically, the Lambda function will consume data from a DynamoDB table, which is populated by a hypothetical IoT device streaming data to the cloud as explained in this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot_lambda/). This setup not only demonstrates the seamless connectivity between various AWS services but also serves as a foundation for building an efficient dashboard for IoT solutions, providing real-time insights and data visualization.
+In this Learning Path, you will learn how to use Amazon S3 to host a static website that interacts with AWS Lambda. Specifically, the Lambda function will consume data from a DynamoDB table, which is populated by a hypothetical IoT device streaming data to the cloud as explained in [Use AWS Lambda for IoT applications running on Arm64](/learning-paths/laptops-and-desktops/win_aws_iot_lambda/). This setup not only demonstrates the seamless connectivity between various AWS services but also serves as a foundation for building an efficient dashboard for IoT solutions, providing real-time insights and data visualization.
diff --git a/content/learning-paths/mobile-graphics-and-gaming/best-practices-for-hwrt-lumen-performance/1-ray-tracing.md b/content/learning-paths/mobile-graphics-and-gaming/best-practices-for-hwrt-lumen-performance/1-ray-tracing.md
@@ -8,7 +8,7 @@ layout: learningpathall
 
 ## Overview
 
-In 2023, Arm developed a demo to showcase the new frontier of next-generation graphics technologies of the **Immortalis** GPU via the Unreal Lumen rendering system. If you are not familiar with Lumen and global illumination, please review this [learning path](/learning-paths/mobile-graphics-and-gaming/how-to-enable-hwrt-on-lumen-for-android-devices/) before proceeding.
+In 2023, Arm developed a demo to showcase the new frontier of next-generation graphics technologies of the **Immortalis** GPU via the Unreal Lumen rendering system. If you are not familiar with Lumen and global illumination, please review [How to Enable Hardware Ray Tracing on Lumen for Android Devices](/learning-paths/mobile-graphics-and-gaming/how-to-enable-hwrt-on-lumen-for-android-devices/) before proceeding.
 
 The demo is named **Steel Arms**. Created with Unreal Engine 5.3, Steel Arms brings desktop-level Bloom, Motion Blur, and Depth of Field (DOF) effects, alongside Physically Based Rendering (PBR), to smartphones.
 
diff --git a/content/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/_index.md b/content/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/_index.md
@@ -12,7 +12,7 @@ learning_objectives:
 prerequisites:
     - A Windows on Arm computer such as the Lenovo Thinkpad X13s running Windows 11 or a Windows on Arm [virtual machine](/learning-paths/cross-platform/woa_azure/).   
     - Any code editor. [Visual Studio Code for Arm64](https://code.visualstudio.com/docs/?dv=win32arm64user) is suitable.
-    - Completion of this [Learning Path](/learning-paths/servers-and-cloud-computing/serverless-framework-aws-intro/).
+    - Completion of [Deploy AWS services using the Serverless Framework](/learning-paths/servers-and-cloud-computing/serverless-framework-aws-intro/).
 
 author: Dawid Borycki
 
diff --git a/content/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/objective.md b/content/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/objective.md
@@ -16,4 +16,4 @@ In the previous [Learning Path](/learning-paths/servers-and-cloud-computing/serv
 
 While manual resource provisioning has its benefits, it can become increasingly problematic as you start deploying your applications to the cloud. As your solutions grow and become more complex, the challenges associated with manual provisioning escalate. This is where the Serverless Framework comes into play, offering a streamlined and efficient way to manage your cloud resources.
 
-In this learning path, you will learn how to automatically deploy a multi-resource serverless solution to AWS. By leveraging the Serverless Framework, you can simplify the deployment process, enhance scalability, and reduce the operational overhead associated with managing cloud infrastructure manually. Specifically, you will create a solution composed of the DynamoDB table and the AWS Lambda function. The latter will consume the data from the table. The function will calculate the average of numerical values in the selected column. This is similar to what you learned in this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb).
+In this learning path, you will learn how to automatically deploy a multi-resource serverless solution to AWS. By leveraging the Serverless Framework, you can simplify the deployment process, enhance scalability, and reduce the operational overhead associated with managing cloud infrastructure manually. Specifically, you will create a solution composed of the DynamoDB table and the AWS Lambda function. The latter will consume the data from the table. The function will calculate the average of numerical values in the selected column. This is similar to what you learned in [Integrate AWS Lambda with DynamoDB for IoT applications running Windows on Arm](/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb).
diff --git a/content/learning-paths/servers-and-cloud-computing/serverless-framework-aws-s3/configuration.md b/content/learning-paths/servers-and-cloud-computing/serverless-framework-aws-s3/configuration.md
@@ -275,6 +275,6 @@ The code defines the two AWS Lambda functions that interact with a DynamoDB tabl
  1. `writeTemperatures` - writes a batch of random temperature records to the DynamoDB table.
  2. `getAverageTemperature` - retrieves the last N temperature records from the table, calculates the average, and returns it.
 
-They are the same as in this [Learning Path](/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/). The only difference is that you now have a helper function, **createResponse**, which is a utility function used to standardize HTTP responses for AWS Lambda functions. This function formats the response to ensure it includes the necessary HTTP status code, headers, and body, making it easier to handle CORS (Cross-Origin Resource Sharing) and JSON responses consistently across different Lambda functions. CORS is configured because the S3 bucket domain might differ from the AWS Lambda function endpoints.
+They are the same as in [Deploy and integrate AWS Lambda with DynamoDB using the Serverless Framework](/learning-paths/servers-and-cloud-computing/serverless-framework-aws-lambda-dynamodb/). The only difference is that you now have a helper function, **createResponse**, which is a utility function used to standardize HTTP responses for AWS Lambda functions. This function formats the response to ensure it includes the necessary HTTP status code, headers, and body, making it easier to handle CORS (Cross-Origin Resource Sharing) and JSON responses consistently across different Lambda functions. CORS is configured because the S3 bucket domain might differ from the AWS Lambda function endpoints.
 
 The service configuration is now ready, and you can move on to prepare the website and supporting files.

Original file line number	Diff line number	Diff line change
`@@ -14,4 +14,4 @@ In addition to its core storage capabilities, Amazon S3 can also be used for sta`
`14`	`14`
`15`	`15`	`Amazon S3 provides Software Development Kits (SDKs) that simplify the integration of S3 into applications by providing comprehensive APIs that facilitate file uploads, downloads, and management directly from the codebase. The AWS CLI allows developers and administrators to interact with S3 from the command line, accelerating many programming and administrative tasks.`
`16`	`16`
`17`		-In this Learning Path, you will learn how to use Amazon S3 to host a static website that interacts with AWS Lambda. Specifically, the Lambda function will consume data from a DynamoDB table, which is populated by a hypothetical IoT device streaming data to the cloud as explained in this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot_lambda/). This setup not only demonstrates the seamless connectivity between various AWS services but also serves as a foundation for building an efficient dashboard for IoT solutions, providing real-time insights and data visualization.
	`17`	+In this Learning Path, you will learn how to use Amazon S3 to host a static website that interacts with AWS Lambda. Specifically, the Lambda function will consume data from a DynamoDB table, which is populated by a hypothetical IoT device streaming data to the cloud as explained in [Use AWS Lambda for IoT applications running on Arm64](/learning-paths/laptops-and-desktops/win_aws_iot_lambda/). This setup not only demonstrates the seamless connectivity between various AWS services but also serves as a foundation for building an efficient dashboard for IoT solutions, providing real-time insights and data visualization.
Original file line number	Diff line number	Diff line change
`@@ -16,4 +16,4 @@ In the previous [Learning Path](/learning-paths/servers-and-cloud-computing/serv`
`16`	`16`
`17`	`17`	`While manual resource provisioning has its benefits, it can become increasingly problematic as you start deploying your applications to the cloud. As your solutions grow and become more complex, the challenges associated with manual provisioning escalate. This is where the Serverless Framework comes into play, offering a streamlined and efficient way to manage your cloud resources.`
`18`	`18`
`19`		-In this learning path, you will learn how to automatically deploy a multi-resource serverless solution to AWS. By leveraging the Serverless Framework, you can simplify the deployment process, enhance scalability, and reduce the operational overhead associated with managing cloud infrastructure manually. Specifically, you will create a solution composed of the DynamoDB table and the AWS Lambda function. The latter will consume the data from the table. The function will calculate the average of numerical values in the selected column. This is similar to what you learned in this [Learning Path](/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb).
	`19`	+In this learning path, you will learn how to automatically deploy a multi-resource serverless solution to AWS. By leveraging the Serverless Framework, you can simplify the deployment process, enhance scalability, and reduce the operational overhead associated with managing cloud infrastructure manually. Specifically, you will create a solution composed of the DynamoDB table and the AWS Lambda function. The latter will consume the data from the table. The function will calculate the average of numerical values in the selected column. This is similar to what you learned in [Integrate AWS Lambda with DynamoDB for IoT applications running Windows on Arm](/learning-paths/laptops-and-desktops/win_aws_iot_lambda_dynamodb).