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Fundamentals of Generative AI practice questions

Practise Google Cloud Generative AI Leader Generative AI Leader Fundamentals of Generative AI practice questions — original exam-style scenarios with answer choices, explanations, and analysis of common mistakes.

Courseiva uses original exam-style practice questions designed for learning and revision. The goal is to understand the concepts, recognise exam patterns, and improve through explanations — not memorise copied exam dumps.

Reviewed byJohnson Ajibi· MSc IT Security
20 questionsDomain: Fundamentals of Generative AI

What the exam tests

What to know about Fundamentals of Generative AI

Fundamentals of Generative AI questions test whether you can apply the concept in context, not just recognise a definition.

How the topic appears in realistic exam-style scenarios.

Which detail in the question changes the correct answer.

How to eliminate plausible but wrong options.

How to connect the question back to the wider exam objective.

Watch out for

Common Fundamentals of Generative AI exam traps

  • Answering from memory before reading the full scenario.
  • Missing a constraint such as cost, availability, security, scope or command context.
  • Choosing a broad answer when the question asks for the most specific fix.
  • Ignoring why the wrong options are tempting.

Practice set

Fundamentals of Generative AI questions

20 questions · select your answer, then reveal the explanation

Question 1easymultiple choice
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A startup is building a customer support chatbot using Vertex AI and wants to ground responses in their product documentation to reduce hallucinations. Which approach should they use?

A data scientist notices that a text generation model deployed on Vertex AI returns repetitive outputs after a few turns in a chat application. What is the most likely cause and the best parameter adjustment?

A financial services company wants to use generative AI to generate personalized investment advice. They must ensure responses comply with regulatory requirements (e.g., no guarantees of returns). Which Vertex AI safety feature should they primarily use?

A company is using Vertex AI to generate marketing copy. They notice that the output sometimes contains factual inaccuracies. Which parameter adjustment is most likely to improve factual accuracy?

A team is fine-tuning a large language model on custom data using Vertex AI. They find that the training loss decreases but validation loss increases. What is the best course of action?

A developer wants to generate product descriptions from a list of features using Vertex AI. Which model type is best suited for this task?

A company is using Vertex AI to generate email responses. They want to ensure sensitive customer data (PII) is not included in the output. What is the most effective approach?

Which TWO statements are true about generative AI models?

A company is deploying a generative AI model for medical diagnosis support. Which THREE considerations are critical for responsible AI?

A team is evaluating generative AI models for a content moderation system. Which THREE metrics are most important to assess?

A company wants to build a chatbot using Vertex AI that can answer customer questions based on their internal knowledge base. Which Google Cloud service should they use to store and retrieve the knowledge base efficiently?

A data scientist is fine-tuning a large language model using Vertex AI. The training job fails with an out-of-memory error. Which action should they take to resolve this issue?

Question 13hardmultiple choice
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A company is deploying a generative AI application that generates medical reports. They need to ensure the output is factual and minimizes hallucinations. Which approach is most effective?

A developer is using Vertex AI PaLM API to generate code snippets. The responses sometimes contain security vulnerabilities. What is the best practice to mitigate this?

A machine learning engineer is building a text-to-image model using Vertex AI. They want to reduce inference latency. Which strategy is most effective?

A company is using Vertex AI to generate personalized marketing emails. The model sometimes produces biased content. What is the most effective way to detect and mitigate bias?

Which TWO options are best practices for deploying generative AI models on Vertex AI? (Choose two.)

Which THREE factors should be considered when choosing between fine-tuning and prompt engineering for a generative AI task? (Choose three.)

A data scientist sees the above error when trying to deploy a model to an endpoint. What is the most likely cause?

Exhibit

Refer to the exhibit.

```
error: Vertex AI Model Registry: Model 'projects/my-project/locations/us-central1/models/123' has status 'DEPLOYING'. Cannot deploy a model that is not in 'READY' state.
```

A developer receives the above JSON response from a Vertex AI PaLM API call for a medical advice application. What should the developer be most concerned about?

Exhibit

Refer to the exhibit.

```
{
  "predictions": [
    {
      "content": "The patient's diagnosis is likely influenza, but further tests are needed.",
      "safetyAttributes": {
        "scores": [0.01],
        "blocked": false,
        "categories": ["health"]
      }
    }
  ],
  "deployedModelId": "123",
  "model": "projects/my-project/locations/us-central1/models/456"
}
```

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Frequently asked questions

What does the Generative AI Leader exam test about Fundamentals of Generative AI?
Fundamentals of Generative AI questions test whether you can apply the concept in context, not just recognise a definition.
How should I use these practice questions?
Select your answer before revealing the explanation. Then read why each option is right or wrong — this active recall approach builds retention far faster than re-reading notes.
Can I practise just Fundamentals of Generative AI questions in a focused session?
Yes — the session launcher on this page draws every question from the Fundamentals of Generative AI domain. Use a 10-question session first to gauge your baseline, then move to 20 or 30 once the weak spots are clear.
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Are these real exam questions or dumps?
These are original practice questions written to test the same concepts the Generative AI Leader exam covers. They are not copied from any real exam or dump site.