Hello tabular data: Set up your project and environment

This tutorial walks you through the required steps to train and get predictions from your tabular data model in the Google Cloud console. If you plan to use the Vertex AI SDK for Python, make sure that the service account initializing the client has the Vertex AI Service Agent (roles/aiplatform.serviceAgent) IAM role.

For this part of the tutorial, you set up your Google Cloud project to use Vertex AI and a Cloud Storage bucket that contains the documents for training your AutoML model.

Set up your project and environment

1. In the Google Cloud console, go to the project selector page.

   Go to project selector

2. Select or create a Google Cloud project.

   Roles required to select or create a project

   • Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
   • Create a project: To create a project, you need the Project Creator (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

3. Verify that billing is enabled for your Google Cloud project.

4. Open Cloud Shell. Cloud Shell is an interactive shell environment for Google Cloud that lets you manage your projects and resources from your web browser.
Go to Cloud Shell
5. In the Cloud Shell, set the current project to your Google Cloud project ID and store it in the projectid shell variable:

     gcloud config set project PROJECT_ID &&
     projectid=PROJECT_ID &&
     echo $projectid

   Replace PROJECT_ID with your project ID. You can locate your project ID in the Google Cloud console. For more information, see Find your project ID.

6. Enable the IAM, Compute Engine, Notebooks, Cloud Storage, and Vertex AI APIs.

   Roles required to enable APIs

   To enable APIs, you need the Service Usage Admin IAM role (roles/serviceusage.serviceUsageAdmin), which contains the serviceusage.services.enable permission. Learn how to grant roles.

   Enable the APIs

7. Make sure that you have the following role or roles on the project: roles/aiplatform.user, roles/storage.admin

   Check for the roles

   1. In the Google Cloud console, go to the IAM page.

      Go to IAM
   2. Select the project.

   3. In the Principal column, find all rows that identify you or a group that you're included in. To learn which groups you're included in, contact your administrator.

   4. For all rows that specify or include you, check the Role column to see whether the list of roles includes the required roles.

   Grant the roles

   1. In the Google Cloud console, go to the IAM page.

      Go to IAM
   2. Select the project.
   3. Click person_add Grant access.

   4. In the New principals field, enter your user identifier. This is typically the email address for a Google Account.

   5. In the Select a role list, select a role.
   6. To grant additional roles, click add Add another role and add each additional role.
   7. Click Save.

The Vertex AI User (roles/aiplatform.user) IAM role provides access to use all resources in Vertex AI. The Storage Admin (roles/storage.admin) role lets you store the document's training dataset in Cloud Storage.

What's next

Follow the next page of this tutorial to create a tabular dataset and train a classification model.