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‎articles/ai-studio/how-to/create-projects.md

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---
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title: Create an Azure AI Studio project in Azure AI Studio
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titleSuffix: Azure AI Studio
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description: This article describes how to create an Azure AI Studio project.
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description: This article describes how to create an Azure AI Studio project from an Azure AI Studio hub that was previously created.
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manager: scottpolly
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ms.service: azure-ai-studio
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ms.custom:
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ms.reviewer: deeikele
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ms.author: sgilley
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author: sdgilley
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# customer intent: As a developer, I want to create an Azure AI Studio project so I can work with generative AI.
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---
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# Create a project in Azure AI Studio
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This article describes how to create a project in Azure AI Studio. A project is used to organize your work and save state while building customized AI apps.
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This article describes how to create an Azure AI Studio project. A project is used to organize your work and save state while building customized AI apps.
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Projects are hosted by an Azure AI Studio hub that provides enterprise-grade security and a collaborative environment. For more information about the projects and resources model, see [Azure AI Studio hubs](../concepts/ai-resources.md).
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## Create a project
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Use the following tabs to select the method you plan to use to create a project:
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# [Azure AI Studio](#tab/ai-studio)
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[!INCLUDE [Create Azure AI Studio project](../includes/create-projects.md)]
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# [Python SDK](#tab/python)
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[!INCLUDE [SDK setup](../includes/development-environment-config.md)]
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8. Use the following code to create a project from a hub you or your administrator created previously. Replace example string values with your own values:
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```Python
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from azure.ai.ml.entities import Project
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my_project_name = "myexampleproject"
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my_location = "East US"
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my_display_name = "My Example Project"
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hub_id = "" # Azure resource manager ID of the hub
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my_project = Project(name=my_hub_name,
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location=my_location,
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display_name=my_display_name,
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hub_id=created_hub.id)
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created_project = ml_client.workspaces.begin_create(workspace=my_hub).result()
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```
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# [Azure CLI](#tab/azurecli)
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1. If you don't have the Azure CLI and machine learning extension installed, follow the steps in the [Install and set up the machine learning extension](/azure/machine-learning/how-to-configure-cli) article.
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1. To authenticate to your Azure subscription from the Azure CLI, use the following command:
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```azurecli
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az login
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```
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For more information on authenticating, see [Authentication methods](/cli/azure/authenticate-azure-cli).
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1. Once the extension is installed and authenticated to your Azure subscription, use the following command to create a new Azure AI project from an existing Azure AI hub:
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```azurecli
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az ml workspace create --kind project --hub-id {my_hub_ARM_ID} --resource-group {my_resource_group} --name {my_project_name}
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```
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---
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## Project settings
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# [Azure AI Studio](#tab/ai-studio)
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On the project **Settings** page you can find information about the project, such as the project name, description, and the hub that hosts the project. You can also find the project ID, which is used to identify the project via SDK or API.
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:::image type="content" source="../media/how-to/projects/project-settings.png" alt-text="Screenshot of an AI Studio project settings page." lightbox = "../media/how-to/projects/project-settings.png":::
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Select **Manage in the Azure portal** to navigate to the project resources in the Azure portal.
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# [Python SDK](#tab/python)
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To manage or use the new project, include it in the `MLClient`:
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```python
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ml_client = MLClient(workspace_name=my_project_name, resource_group_name=my_resource_group, subscription_id=my_subscription_id,credential=DefaultAzureCredential())
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```
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# [Azure CLI](#tab/azurecli)
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To view settings for the project, use the `az ml workspace show` command. For example:
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```azurecli
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az ml workspace show --name {my_project_name} --resource-group {my_resource_group}
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```
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---
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## Next steps
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- [Deploy an enterprise chat web app](../tutorials/deploy-chat-web-app.md)

‎articles/ai-studio/how-to/develop/create-hub-project-sdk.md

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---
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title: How to create a hub and project using the Azure Machine Learning SDK
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title: How to create a hub using the Azure Machine Learning SDK/CLI
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titleSuffix: Azure AI Studio
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description: This article provides instructions on how to create an AI Studio hub and project using the Azure Machine Learning SDK.
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description: This article provides instructions on how to create an AI Studio hub using the Azure Machine Learning SDK and Azure CLI extension.
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manager: nitinme
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ms.service: azure-ai-studio
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author: eric-urban
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---
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# Create a hub and project using the Azure Machine Learning SDK
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# Create a hub using the Azure Machine Learning SDK and CLI
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[!INCLUDE [Feature preview](~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md)]
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In this article, you learn how to create the following AI Studio resources using the Azure Machine Learning SDK:
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In this article, you learn how to create the following AI Studio resources using the Azure Machine Learning SDK and Azure CLI (with machine learning extension):
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- An Azure AI Studio hub
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- An Azure AI Services connection
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- An Azure AI Studio project
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## Prerequisites
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- An Azure subscription. If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure AI Studio](https://azure.microsoft.com/free/) today.
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## Set up your environment
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Use the following tabs to select whether you're using the Python SDK or Azure CLI:
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# [Python SDK](#tab/python)
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[!INCLUDE [SDK setup](../../includes/development-environment-config.md)]
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# [Azure CLI](#tab/azurecli)
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1. If you don't have the Azure CLI and machine learning extension installed, follow the steps in the [Install and set up the machine learning extension](/azure/machine-learning/how-to-configure-cli) article.
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1. To authenticate to your Azure subscription from the Azure CLI, use the following command:
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```azurecli
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az login
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```
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For more information on authenticating, see [Authentication methods](/cli/azure/authenticate-azure-cli).
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---
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## Create the AI Studio hub and AI Services connection
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Use the following code to create a new hub and AI Services connection. Replace example string values with your own values:
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Use the following examples to create a new hub. Replace example string values with your own values:
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# [Python SDK](#tab/python)
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```Python
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from azure.ai.ml.entities import Hub
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from azure.ai.ml.entities import AzureAIServicesConnection
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my_hub_name = "myexamplehub"
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my_location = "East US"
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created_hub = ml_client.workspaces.begin_create(my_hub).result()
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```
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# [Azure CLI](#tab/azurecli)
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```azurecli
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az ml workspace create --kind hub --resource-group {my_resource_group} --name {my_hub_name}
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```
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---
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## Create an AI Services connection
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After creating your own AI Services, you can connect it to your hub:
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# [Python SDK](#tab/python)
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```python
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from azure.ai.ml.entities import AzureAIServicesConnection
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# constrict an AI Services connection
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my_connection_name = "myaiservivce"
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my_endpoint = "demo.endpoint" # this could also be called target
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my_api_keys = None # leave blank for Authentication type = AAD
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my_ai_services_resource_id = "" # ARM id required
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my_connection = AIServicesConnection(name=my_connection_name,
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my_connection = AzureAIServicesConnection(name=my_connection_name,
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endpoint=my_endpoint,
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api_key= my_api_keys,
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ai_services_resource_id=my_ai_services_resource_id)
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# Create the connection
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ml_client.connections.create_or_update(my_connection)
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```
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## Create AI Studio project
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# [Azure CLI](#tab/azurecli)
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Use the following code to create a project from the hub you created previously. Replace example string values with your own values:
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```Python
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from azure.ai.ml.entities import Project
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```azurecli
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az ml connection create --file {connection.yml} --resource-group {my_resource_group} --workspace-name {my_hub_name}
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```
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my_project_name = "myexampleproject"
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my_location = "East US"
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my_display_name = "My Example Project"
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You can use either an API key or credential-less YAML configuration file. For more information on the YAML configuration file, see the [AI Services connection YAML schema](/azure/machine-learning/reference-yaml-connection-ai-services):
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my_hub = Project(name=my_hub_name,
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location=my_location,
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display_name=my_display_name,
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hub_id=created_hub.id)
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- API Key example:
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created_project = ml_client.workspaces.begin_create(workspace=my_hub).result()
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```
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```yml
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name: myazai_ei
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type: azure_ai_services
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endpoint: https://contoso.cognitiveservices.azure.com/
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api_key: XXXXXXXXXXXXXXX
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```
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## Update the MLClient
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- Credential-less
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To use the new project, include it in the `MLClient`.
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```yml
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name: myazai_apk
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type: azure_ai_services
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endpoint: https://contoso.cognitiveservices.azure.com/
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```
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```python
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ml_client = MLClient(workspace_name=my_project_name, resource_group_name=my_resource_group, subscription_id=my_subscription_id,credential=DefaultAzureCredential())
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```
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---
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## Related content
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- [Get started building a chat app using the prompt flow SDK](../../quickstarts/get-started-code.md)
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- [Work with projects in VS Code](vscode.md)
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- [Work with projects in Visual Studio Code](vscode.md)
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- [Configure a managed network](../configure-managed-network.md?tabs=python)

‎articles/ai-studio/toc.yml

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- name: Create a hub in the Azure portal
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href: how-to/create-secure-ai-hub.md
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- name: Create a hub from template
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href: how-to/create-azure-ai-hub-template.md
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href: how-to/create-azure-ai-hub-template.md
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- name: Create a hub using the Azure Machine Learning SDK and CLI
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href: how-to/develop/create-hub-project-sdk.md
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- name: Create a project
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href: how-to/create-projects.md
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- name: Create a hub and project using the Azure Machine Learning SDK
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href: how-to/develop/create-hub-project-sdk.md
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- name: Create and manage compute
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href: how-to/create-manage-compute.md
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- name: Connect to external resources

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