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6) To make your code compatible with Vertex AI, there are three basic steps that must be completed in a specific order:
          i) Upload data to Google Cloud Storage,
          ii) Move code into a trainer Python package,
          iii) Submit your training job with gcloud to train on Vertex AI.

5) Navigation menu > APIs Services, Billing, IAM Admin, Marketplace, Compute Engine, Kubernetes Engine, Cloud Storage, BigQuery, VPC network, Cloud Run, SQL, Security, Google Maps Platform:
              

4) Models for ML can be trained by using cloud infrastructure through Google Cloud Training Service.

3) Shows "401 error" (401. That's an error.) after click "Open JupyterLab".
          Troubleshooting from Google workbench at link.

2) Navigation menu > View all products > Locate "Vertex AI" > "Workbench" > "User-Managed Notebooks":
          2.a) Click "View all products":
              
          2.b) CTL + C to search "Vertex AI".
              
          2.c) Click "Vertex AI".
              
            
          2.d) Click "NEW NOTEBOOK" > "TensorFlow Enterprise" > "TensorFlow Enterprise 2.9" > "Without GPUs" or "With 1 NVIDIA Tesla T4":
              

1) "Open JupyterLab" button appears and is enabled after the "NEW NOTEBOOK" has run for a necessary time frame:
          1.a) It does not show yet immediately after the creation of "NEW NOTEBOOK":
              
          1.b) It shows up after the creation of "NEW NOTEBOOK" has run for more than 20 min, namely when the instance is ready to use, Vertex AI Workbench activates an Open JupyterLab link (see on Google):
              

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