Set up a project and a development environment

This guide describes how to set up a Google Cloud project to start using Vertex AI. It also describes how to set up the Google Cloud CLI in your local development environment. You can use the gcloud CLI to perform custom training and interact with Model and Endpoint resources.

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Go to project selector

3. Make sure that billing is enabled for your Google Cloud project.

4. Enable the Vertex AI API.

   Enable the API

5. Install the Google Cloud CLI.

6. To initialize the gcloud CLI, run the following command:

   gcloud init

7. Update and install gcloud components:

   gcloud components update
   gcloud components install beta

8. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Go to project selector

9. Make sure that billing is enabled for your Google Cloud project.

10. Enable the Vertex AI API.

    Enable the API

11. Install the Google Cloud CLI.

12. To initialize the gcloud CLI, run the following command:

    gcloud init

13. Update and install gcloud components:

    gcloud components update
    gcloud components install beta

Note: Certain tasks in Vertex AI require that you use additional Google Cloud products besides Vertex AI. For example, in most cases, you must use Cloud Storage and Artifact Registry when you create a custom training pipeline. You might need to perform additional setup tasks to use other Google Cloud products.

What's next

• Read an overview of Vertex AI.

• Walk through one of the tutorials for using Vertex AI.

• Learn how to use the Vertex AI SDK for Python, which provides another way to interact with Vertex AI.