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Vertex AI: Qwik Start

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Use an Incognito or private browser window to run this lab. This prevents any conflicts between your personal account and the student account, which may cause extra charges incurred to your personal account.
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Vertex AI: Qwik Start

Lab 45 minutes universal_currency_alt 1 Credit show_chart Introductory
info This lab may incorporate AI tools to support your learning.
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GSP917

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Overview

In this lab, you use BigQuery for data processing and exploratory data analysis and the Vertex AI platform to train and deploy a custom TensorFlow Regressor model to predict customer lifetime value. The goal of the lab is to introduce to Vertex AI through a high value real world use case - predictive CLV. You start with a local BigQuery and TensorFlow workflow that you may already be familiar with and progress toward training and deploying your model in the cloud with Vertex AI.

vertex-ai-overview.png

Objectives

In this lab, you will:

Setup and requirements

Before you click the Start Lab button

Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources are made available to you.

This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials you use to sign in and access Google Cloud for the duration of the lab.

To complete this lab, you need:

  • Access to a standard internet browser (Chrome browser recommended).
Note: Use an Incognito (recommended) or private browser window to run this lab. This prevents conflicts between your personal account and the student account, which may cause extra charges incurred to your personal account.
  • Time to complete the lab—remember, once you start, you cannot pause a lab.
Note: Use only the student account for this lab. If you use a different Google Cloud account, you may incur charges to that account.

How to start your lab and sign in to the Google Cloud console

  1. Click the Start Lab button. If you need to pay for the lab, a dialog opens for you to select your payment method. On the left is the Lab Details pane with the following:

    • The Open Google Cloud console button
    • Time remaining
    • The temporary credentials that you must use for this lab
    • Other information, if needed, to step through this lab

  2. Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).

    The lab spins up resources, and then opens another tab that shows the Sign in page.

    Tip: Arrange the tabs in separate windows, side-by-side.

    Note: If you see the Choose an account dialog, click Use Another Account.

  3. If necessary, copy the Username below and paste it into the Sign in dialog.

    {{{user_0.username | "Username"}}}

    You can also find the Username in the Lab Details pane.

  4. Click Next.

  5. Copy the Password below and paste it into the Welcome dialog.

    {{{user_0.password | "Password"}}}

    You can also find the Password in the Lab Details pane.

  6. Click Next.

    Important: You must use the credentials the lab provides you. Do not use your Google Cloud account credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.

  7. Click through the subsequent pages:

    • Accept the terms and conditions.
    • Do not add recovery options or two-factor authentication (because this is a temporary account).
    • Do not sign up for free trials.

After a few moments, the Google Cloud console opens in this tab.

Note: To access Google Cloud products and services, click the Navigation menu or type the service or product name in the Search field. Navigation menu icon and Search field

Activate Cloud Shell

Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.

  1. Click Activate Cloud Shell Activate Cloud Shell icon at the top of the Google Cloud console.

  2. Click through the following windows:

    • Continue through the Cloud Shell information window.
    • Authorize Cloud Shell to use your credentials to make Google Cloud API calls.

When you are connected, you are already authenticated, and the project is set to your Project_ID, . The output contains a line that declares the Project_ID for this session:

Your Cloud Platform project in this session is set to {{{project_0.project_id | "PROJECT_ID"}}}

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

  1. (Optional) You can list the active account name with this command:
gcloud auth list
  1. Click Authorize.

Output:

ACTIVE: * ACCOUNT: {{{user_0.username | "ACCOUNT"}}} To set the active account, run: $ gcloud config set account `ACCOUNT`
  1. (Optional) You can list the project ID with this command:
gcloud config list project

Output:

[core] project = {{{project_0.project_id | "PROJECT_ID"}}} Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Task 1. Enable Google Cloud services

  1. Open a new Cloud Shell terminal by clicking the Cloud Shell icon in the top right corner of the Google Cloud Console.

  2. In your Cloud Shell terminal, use gcloud to enable the services used in the lab:

gcloud services enable \ compute.googleapis.com \ iam.googleapis.com \ iamcredentials.googleapis.com \ monitoring.googleapis.com \ logging.googleapis.com \ notebooks.googleapis.com \ aiplatform.googleapis.com \ bigquery.googleapis.com \ artifactregistry.googleapis.com \ cloudbuild.googleapis.com \ container.googleapis.com

Click Check my progress to verify the objective. Enable Google Cloud services.

Task 2. Open a Vertex AI Workbench instance

  1. In the Google Cloud console, from the Navigation menu (Navigation menu), select Vertex AI.

  2. Click Enable All Recommended APIs.

  3. On the left-hand side, click Workbench.

  4. At the top of the Workbench page, ensure you are in the Instances view.

  5. Click Open JupyterLab next to the instance name to launch the JupyterLab interface. This will open a new tab in your browser.

Workbench Instance

  1. Click the Terminal icon to open a terminal window.

Open Terminal

Your terminal window will open in a new tab. You can now run commands in the terminal to interact with your Workbench instance.

terminal window opened

Click Check my progress to verify the objective. Open a Vertex AI Workbench instance.

Task 3. Install lab dependencies

  1. In the open terminal, run the following command to install the lab dependencies:
pip3 install --user -r requirements.txt sudo apt -y install python3-pandas sudo apt -y install graphviz pip uninstall openpyxl pip install openpyxl
  1. When prompted, type y and press Enter to confirm the installation.

Task 4. Run the lab notebook

  1. In the file browser, open .

  2. When prompted, select the Python 3 kernel.

  3. Continue the lab in the notebook, and run each cell by clicking the Run icon at the top of the screen.

Alternatively, you can execute the code in a cell with SHIFT + ENTER.

Read the narrative and make sure you understand what's happening in each cell.

Click Check my progress to verify the objective. Run the lab notebook.

Congratulations!

In this lab, you ran a machine learning experimentation workflow using Google Cloud BigQuery for data storage and analysis and Vertex AI machine learning services to train and deploy a TensorFlow model to predict customer lifetime value.

Next steps / learn more

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Manual Last Updated October 7, 2024

Lab Last Tested October 7, 2024

Copyright 2025 Google LLC All rights reserved. Google and the Google logo are trademarks of Google LLC. All other company and product names may be trademarks of the respective companies with which they are associated.

Before you begin

  1. Labs create a Google Cloud project and resources for a fixed time
  2. Labs have a time limit and no pause feature. If you end the lab, you'll have to restart from the beginning.
  3. On the top left of your screen, click Start lab to begin

Use private browsing

  1. Copy the provided Username and Password for the lab
  2. Click Open console in private mode

Sign in to the Console

  1. Sign in using your lab credentials. Using other credentials might cause errors or incur charges.
  2. Accept the terms, and skip the recovery resource page
  3. Don't click End lab unless you've finished the lab or want to restart it, as it will clear your work and remove the project

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Setup your console before you begin

Use an Incognito or private browser window to run this lab. This prevents any conflicts between your personal account and the Student account, which may cause extra charges incurred to your personal account.