Question 479 of 500
Fundamentals of Generative AIhardMultiple ChoiceObjective-mapped

Quick Answer

The correct answer is that Alice can deploy pre-trained models while Bob can create and manage custom model code. This is because the IAM policy binds specific roles to each user: Alice receives a role containing the `aiplatform.models.get` permission, which allows her to view and deploy existing pre-trained models, while Bob receives a role with `aiplatform.models.create` and `aiplatform.models.update` permissions, enabling him to build and modify custom model code. On the Google Cloud Generative AI Leader exam, this question tests your ability to interpret a Vertex AI IAM policy for models by mapping individual permissions to real-world actions, often appearing as a multi-user scenario to assess granular access control. A common trap is confusing `get` with `create`—remember that `get` is read-only and supports deployment, whereas `create` and `update` are write operations for custom development. For a quick memory tip: “Get to deploy, Create to code.”

Generative AI Leader Fundamentals of Generative AI Practice Question

This Generative AI Leader practice question tests your understanding of fundamentals of generative ai. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

{
  "bindings": [
    {
      "role": "roles/aiplatform.user",
      "members": ["user:alice@example.com"]
    },
    {
      "role": "roles/aiplatform.customCodeModelAdmin",
      "members": ["user:bob@example.com"]
    }
  ]
}

Refer to the exhibit. An administrator creates this IAM policy for a Vertex AI project. What is the effect of this policy?

Question 1hardmultiple choice
Full question →

Exhibit

{
  "bindings": [
    {
      "role": "roles/aiplatform.user",
      "members": ["user:alice@example.com"]
    },
    {
      "role": "roles/aiplatform.customCodeModelAdmin",
      "members": ["user:bob@example.com"]
    }
  ]
}

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Alice can deploy pre-trained models; Bob can create and manage custom model code

Option B is correct because the IAM policy grants Alice the `aiplatform.models.get` permission (allowing her to view and deploy pre-trained models) and grants Bob the `aiplatform.models.create` and `aiplatform.models.update` permissions (allowing him to create and manage custom model code). The policy uses separate bindings for each user, with specific roles that align with these actions.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

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

  • Alice can view models; Bob can delete models

    Why it's wrong here

    aiplatform.user includes more than view; delete is not granted by customCodeModelAdmin.

  • Alice can deploy pre-trained models; Bob can create and manage custom model code

    Why this is correct

    aiplatform.user includes deployment permissions; customCodeModelAdmin covers custom code management.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Both have full access to all Vertex AI resources

    Why it's wrong here

    Neither role grants full access; aiplatform.user is limited, customCodeModelAdmin is specific.

  • Alice can train models; Bob can deploy models

    Why it's wrong here

    Training is not typically part of aiplatform.user; customCodeModelAdmin includes deployment of custom models, but not necessarily all models.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the distinction between specific IAM permissions (e.g., `get` vs. `create` vs. `delete`) and the common misconception that viewing a model implies full access or that creating a model implies the ability to deploy it.

Detailed technical explanation

How to think about this question

In Vertex AI, IAM roles are composed of granular permissions like `aiplatform.models.get`, `aiplatform.models.create`, and `aiplatform.models.update`. The `aiplatform.models.get` permission is necessary for deploying a pre-trained model because the deployment process requires reading the model resource. Bob's `create` and `update` permissions allow him to upload new model versions and modify model metadata, which is essential for custom model code management. Note that deleting models requires the `aiplatform.models.delete` permission, which is not granted to either user.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Related practice questions

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FAQ

Questions learners often ask

What does this Generative AI Leader question test?

Fundamentals of Generative AI — This question tests Fundamentals of Generative AI — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Alice can deploy pre-trained models; Bob can create and manage custom model code — Option B is correct because the IAM policy grants Alice the `aiplatform.models.get` permission (allowing her to view and deploy pre-trained models) and grants Bob the `aiplatform.models.create` and `aiplatform.models.update` permissions (allowing him to create and manage custom model code). The policy uses separate bindings for each user, with specific roles that align with these actions.

What should I do if I get this Generative AI Leader question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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This Generative AI Leader practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Generative AI Leader exam.