microsoft · eedorenko · Nov 26, 2019 · Nov 26, 2019 · Nov 26, 2019 · Nov 26, 2019
diff --git a/docs/getting_started.md b/docs/getting_started.md
@@ -32,14 +32,13 @@ permissions. Normally a subscription admin can create a Service principal and
 can provide you the details.
 
 ## Create an Azure DevOps Azure ML Workspace Service Connection
-You need to create a service connection to your ML workspace so the Azure DevOps Azure ML task can execute the Azure ML training pipeline. To get there, go to your Azure DevOps project settings page (by clicking on the cog wheel to the bottom left of the screen), and then click on **Service connections** under the **Pipelines** section:
-
-**Note:** Creating service connection using Azure Machine Learning extension requires 'Owner' or 'User Access Administrator' permissions on the Workspace.
-
-This is how your service connection looks like. Make sure to pick your resource group and type AML workspace.  The connection name specified here needs to be used for the value of the `WORKSPACE_SVC_CONNECTION` set in the variable group below.
+Install the **Azure Machine Learning** extension to your organization from the
+[marketplace](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml),
+so that you can set up a service connection to your AML workspace.
 
-![](./images/svc-connection.png)
+Create a service connection to your ML workspace via the [Azure DevOps Azure ML task instructions](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml) to be able to execute the Azure ML training pipeline. The connection name specified here needs to be used for the value of the `WORKSPACE_SVC_CONNECTION` set in the variable group below.
 
+**Note:** Creating service connection using Azure Machine Learning extension requires 'Owner' or 'User Access Administrator' permissions on the Workspace.
 
 ## Create a Variable Group for your Pipelines
 
@@ -221,20 +220,6 @@ The pipeline consumes two artifacts:
 1. the result of the **Build Pipeline** as it contains configuration files
 1. the **model** trained and registered by the ML training pipeline
 
-Install the **Azure Machine Learning** extension to your organization from the
-[marketplace](https://marketplace.visualstudio.com/items?itemName=ms-air-aiagility.vss-services-azureml),
-so that you can set up a service connection to your AML workspace.
-
-To configure a model artifact, there should be a service connection to
-**mlops-AML-WS** workspace. To get there, go to the project settings (by
-clicking on the cog wheel to the bottom left of the screen), and then click on
-**Service connections** under the **Pipelines** section:
-
-**Note:** Creating service connection using Azure Machine Learning extension
-requires 'Owner' or 'User Access Administrator' permissions on the Workspace.
-
-![workspace connection](./images/workspace-connection.png)
-
 Add an artifact to the pipeline and select **AzureML Model Artifact** source
 type. Select the **Service Endpoint** and **Model Names** from the drop down
 lists. **Service Endpoint** refers to the **Service connection** created in

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