GenAI-Leader Practice Tests

Google Cloud Generative AI Leader

Prepare for the Google Cloud Generative AI Leader exam with practice for gen AI fundamentals, Google Cloud offerings, output improvement techniques, and business strategy for responsible adoption.

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Duration

90 minutes

Questions

50-60 questions

Cost

$99 USD

Where to register

Google Cloud

Issued by Google Cloud. Delivered via Online-proctored or onsite-proctored exam. Designed for business-level generative AI knowledge. Google lists no prerequisites.

01·Overview

Certification overview

The format, prerequisites, and what to expect on exam day.

Exam details

Exam Code
Generative AI Leader
Duration
90 minutes
Questions
50-60 questions
Format
Multiple choice
Passing Score
Not disclosed
Cost
$99 USD
Validity
3 years

Prerequisites

No formal prerequisites
Business-level understanding of generative AI opportunities, risks, and adoption patterns
Familiarity with Google Cloud gen AI offerings such as Gemini, Vertex AI, Agent Builder, and Workspace AI experiences
Understanding of responsible AI, security, privacy, and value measurement concepts

02·Domains

Exam domains

Topics on the official blueprint, with their relative weight.

Fundamentals of gen AI

30%

Foundation models, multimodal models, diffusion, and prompt tuning
ML lifecycle and Google Cloud tooling
Model selection for business use cases
Data quality and accessibility

Google Cloud's gen AI offerings

35%

Gemini app and Gemini Enterprise
Gemini for Workspace
Vertex AI and Model Garden
Vertex AI Agent Builder and customer engagement offerings

Techniques to improve gen AI model output

20%

Grounding, RAG, prompt engineering, fine-tuning, and human-in-the-loop
Sampling parameters and safety settings
Continuous monitoring and evaluation

Business strategies for a successful gen AI solution

15%

Choose the right gen AI solution
Integrate gen AI into the organization
Secure AI with SAIF
Apply responsible AI practices

03·Key topics

What you actually study

Service families and concept clusters that show up across questions.

Google AI Offerings

Gemini
Gemma
Imagen
Veo
Vertex AI
Model Garden

Business Use Cases

Employee productivity
customer experience
search and knowledge discovery
content workflows

Output Improvement

Prompt engineering
RAG
grounding
fine-tuning
human review

Governance

SAIF
privacy
bias
fairness
accountability
explainability

04·Study tips

How to actually pass it

Practical strategies for the weeks before, and the morning of.

Preparation strategy

Study Google Cloud gen AI products from a business fit perspective, not only a technical feature list.
Practice mapping use cases to Gemini, Vertex AI, Agent Builder, Model Garden, Workspace, and customer engagement offerings.
Understand how grounding, RAG, prompting, fine-tuning, safety settings, and monitoring improve outputs.
Review SAIF and responsible AI concepts as part of every adoption decision.

Exam day

Identify the product family first, then match the answer to the service or platform named in the scenario.
Watch for requirements around cost, latency, governance, and operational ownership.
Use elimination on answers that ignore security, monitoring, or responsible AI requirements.
Flag long architecture questions and return after completing faster recall questions.
Choose managed services when the question emphasizes speed, governance, and reduced operations.

Lead generative AI adoption with sharper judgment.

Practice business, product, output quality, and governance scenarios. Start free, no card required.

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