Cloud Digital Leader Google Cloud Products and Services Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Cloud Functions

  Why it's wrong here

  Cloud Functions is a serverless, event-driven compute service that runs stateless functions in response to triggers, with maximum execution timeouts and resource limits that make it unsuitable for ML training. It lacks built-in support for GPUs/TPUs, distributed training, and model versioning. For training a custom model, you need a managed ML platform like Vertex AI, not a general-purpose function service.

• ✓

  Vertex AI

  Why this is correct

  Vertex AI is the correct choice because it is Google Cloud's unified platform for building, training, and deploying ML models at scale. It provides a custom training service where you can launch training jobs with your own code, containers, and hardware accelerator configurations, and it manages compute clusters and automatically handles node provisioning. It also offers persistent online prediction endpoints, batch prediction, and integration with Vertex AI Pipelines for orchestration, making it ideal for a data scientist who needs full control.

• ✗

  AutoML

  Why it's wrong here

  AutoML is a part of Vertex AI that automates model development, using techniques like neural architecture search and transfer learning to train models from labeled data without requiring custom code. While it could handle many tabular, image, or text tasks, the scenario specifically says 'custom machine learning model,' implying the data scientist wants to write their own training code and define a custom architecture. AutoML does not allow you to modify the underlying training algorithm or bring your own training scripts, so it lacks the flexibility needed for truly custom training.

• ✗

  AI Platform (Unified)

  Why it's wrong here

  AI Platform (Unified) is the former name for Vertex AI; Google Cloud renamed the service to Vertex AI in 2021. Since it refers to the same underlying product, it is not a distinct alternative. In a current exam or documentation, the correct name is Vertex AI, so selecting the old name is inaccurate, even though the functionality would be identical. Thus, if 'Vertex AI' is listed as an option, it should be chosen over the outdated alias.

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