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Foundational · Generative AI LeaderPrep available

Google Cloud Certified Generative AI Leader (Generative AI Leader) practice exam and study path

A free, timed 60-question Generative AI Leader practice exam in 90 minutes, scored by domain, with every option explained after you submit. Also 135 practice questions you can check one at a time, a page for every task in the exam guide, and a study path. No sign-up.

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Generative AI Leader exam pack:

$5for 12 months

The business-level generative AI exam: core gen AI concepts, what each of Google Cloud's gen AI offerings is for, how to improve model output, and how to run a secure, responsible gen AI initiative.

The exam

Exam code
Generative AI Leader
Questions
Not yet published
Time
90 minutes
Passing score
Not published
Exam fee
$99 (USD)
Question types
multiple choice

50-60 multiple-choice questions in 90 minutes, $99 plus tax, online or at a test center, in English, Japanese, Spanish and Portuguese; no prerequisites; valid for 3 years. Google does not publish a passing score.

From Google Cloud's certification page and exam guide, checked Oct 18, 2026.

Domains and weights

  • Domain 1: Fundamentals of gen AI

    30%

  • Domain 2: Google Cloud's gen AI offerings

    35%

  • Domain 3: Techniques to improve gen AI model output

    20%

  • Domain 4: Business strategies for a successful gen AI solution

    15%

Practice

135 original practice questions, every option explained with the Google Cloud documentation page that proves it. Free, no sign-up; progress stays on this device.

Your results on this device →

More practice exams

The lessons, the sample questions on every task page and the first full practice exam are free and stay free. A pack adds the further timed Generative AI Leader practice exams.

Generative AI Leader exam pack

$5for 12 months

  • Every paid Generative AI Leader practice exam, timed, with every option explained
  • The next version of this exam included when it changes within your 12 months
  • 12 months of access. One payment, nothing renews by itself.
  • 14-day refund, no conditions
  • 14-day refund, no conditions: ask within 14 days of buying and you get the whole payment back.
  • No pass guarantee. These are practice exams written by us from the exam guide and the Google Cloud documentation; a score here does not predict your result on the real exam.

Study path

One module per exam domain. Lessons that already exist on BytePatterns are linked; the rest are being written.

  1. Module 1: Fundamentals of gen AI

    1. 1AI, machine learning, generative AI, foundation models and LLMs: how the terms nestTask 1.1

      Partly covered by: What Is Machine Learning, What Is an LLM

    2. 2Supervised, unsupervised and reinforcement learningTask 1.1

      Partly covered by: What Is Machine Learning

    3. 3Transformers, diffusion models and multimodal foundation modelsTask 1.1

      Partly covered by: Attention, Intuitively, Transformers: Big Picture

    4. 4The machine learning lifecycle and the Google Cloud tool for each stageTask 1.1

      Partly covered by: Training vs Inference

    5. 5Choosing a foundation model: modality, context window, security, availability, cost, performance, customizationTask 1.1

      Partly covered by: Context Windows, Model Routing and Fallbacks

    6. 6Create, summarize, discover, automate: business use cases for gen AITask 1.1

      Lesson coming

    7. 7Structured and unstructured, labeled and unlabeled dataTask 1.2

      Partly covered by: Data Readiness for AI, What Is Machine Learning

    8. 8Data quality and accessibility: completeness, consistency, relevance, availability, cost, formatTask 1.2

      Partly covered by: Data Readiness for AI

    9. 9The five layers: infrastructure, models, platforms, agents, applicationsTask 1.3

      Lesson coming

    10. 10Gemini, Gemma, Gemini image models and Veo: which model for which jobTask 1.4

      Lesson coming

  2. Module 2: Google Cloud's gen AI offerings

    1. 11Why Google Cloud for gen AI: AI-first, enterprise-ready, open, and an integrated ecosystemTask 2.1

      Lesson coming

    2. 12AI-optimized infrastructure: AI Hypercomputer, TPUs and GPUsTask 2.1

      Lesson coming

    3. 13Control over your data and low-code AI for more peopleTask 2.1

      Lesson coming

    4. 14The Gemini app and GemsTask 2.2

      Lesson coming

    5. 15Gemini Enterprise: enterprise search, the assistant, agents, and Gemini Notebook EnterpriseTask 2.2

      Lesson coming

    6. 16Gemini in Gmail, Docs, Sheets, Slides, Meet and DriveTask 2.2

      Lesson coming

    7. 17Search for customers: Agent Search and Grounding with Google SearchTask 2.3

      Partly covered by: Retrieval-Augmented Generation

    8. 18Gemini Enterprise for Customer Experience: CX Agent Studio, Agent Assist, Customer Experience Insights, CCaaSTask 2.3

      Lesson coming

    9. 19Gemini Enterprise Agent Platform: Model Garden, Agent Studio and AutoMLTask 2.4

      Lesson coming

    10. 20RAG on Google Cloud: Agent Search and RAG EngineTask 2.4

      Partly covered by: Retrieval-Augmented Generation, Vector Databases, Chunking and Reranking

    11. 21Building and running custom agents: ADK, Agent Runtime, Agent GardenTask 2.4

      Partly covered by: Agents and Tools

    12. 22How agents use tools: extensions, functions, data stores and pluginsTask 2.5

      Partly covered by: Agents and Tools, The Tool-Use Loop

    13. 23Pre-built AI APIs and Google Cloud services as agent toolsTask 2.5

      Lesson coming

    14. 24Google AI Studio or Agent StudioTask 2.5

      Lesson coming

  3. Module 3: Techniques to improve gen AI model output

    1. 25Limitations of foundation models: knowledge cutoff, hallucinations, bias, edge casesTask 3.1

      Partly covered by: What Is an LLM, Retrieval-Augmented Generation

    2. 26Fixing a limitation: grounding, RAG, prompting, fine-tuning or a human in the loopTask 3.1

      Partly covered by: Fine-Tuning vs Prompting, Adapters and LoRA, Guardrails

    3. 27Monitoring and evaluating gen AI over timeTask 3.1

      Partly covered by: Evaluating LLMs, LLM as a Judge

    4. 28Zero-shot, one-shot, few-shot, role prompting and prompt chainingTask 3.2

      Partly covered by: Fine-Tuning vs Prompting

    5. 29Chain-of-thought and ReActTask 3.2

      Partly covered by: The Tool-Use Loop

    6. 30Grounding in enterprise, third-party and world data, and what RAG changesTask 3.3

      Partly covered by: Retrieval-Augmented Generation, Embeddings

    7. 31Sampling settings: tokens, temperature, top-p, safety settings and output lengthTask 3.3

      Partly covered by: Temperature and Sampling, Tokenization

  4. Module 4: Business strategies for a successful gen AI solution

    1. 32Matching a gen AI solution to the business need and its constraintsTask 4.1

      Lesson coming

    2. 33Bringing gen AI into an organization: vision, use cases, people, changeTask 4.1

      Partly covered by: From Pilot to Production, AI Teams and the Center of Excellence, Change Management for AI

    3. 34Measuring the impact of gen AITask 4.1

      Partly covered by: Measuring AI Value

    4. 35Security across the ML lifecycle and Google's Secure AI Framework (SAIF)Task 4.2

      Partly covered by: Guardrails

    5. 36Google Cloud security tools for AI: IAM, Security Command Center, Model ArmorTask 4.2

      Lesson coming

    6. 37Responsible AI: transparency, accountability, explainability and Google's AI PrinciplesTask 4.3

      Lesson coming

    7. 38Privacy, anonymization and pseudonymizationTask 4.3

      Partly covered by: Finding and Masking PII

    8. 39Data quality, bias and fairnessTask 4.3

      Partly covered by: Data Readiness for AI

Every task in the exam guide

The exam guide splits each domain into task statements. Each one has a page with a short summary, the lessons that teach it and open sample questions.

Domain 1: Fundamentals of gen AI

Domain 2: Google Cloud's gen AI offerings

Domain 3: Techniques to improve gen AI model output

Domain 4: Business strategies for a successful gen AI solution

How these questions are made

  • Written by us from the exam guide's task statements and the Google Cloud documentation — never from real exam content.
  • Every option carries its own explanation and a link to the Google Cloud page that proves it.
  • A question enters a timed exam only after an independent check; until then it is a practice question.
  • Results are a plain percentage, per domain too — not an imitation of Google Cloud's scaled score.

Questions about the Generative AI Leader practice exam

Is the Generative AI Leader practice exam free?
Yes. The full practice exam (60 questions, 90 minutes) is free with no sign-up, and so are the 135 practice questions, the task pages and the study path. Your attempts are saved in this browser, on this device.
How many questions does it have, and is it timed?
60 questions in 90 minutes: the real Generative AI Leader pace, scaled to this form. When the time runs out, the exam is submitted as it stands.
Are the answers explained?
After you submit, not during: like the real exam, the timed exam gives no feedback until the end. Then you get your score overall and per exam domain, and every question with each option explained and a link to the Google Cloud documentation page behind it. In practice mode an answer is explained as soon as you check it.
What does the Generative AI Leader exam pack add?
3 more timed practice exams (Practice exam 1: 60 questions, 90 minutes; Practice exam 2: 60 questions, 90 minutes; Practice exam 3: 60 questions, 90 minutes), each scored and explained the same way, and the next version of this exam if it changes within your 12 months. 12 months of access. One payment, nothing renews by itself. Everything above stays free. See the pack.
Can I get a refund?
Yes, with no conditions: ask within 14 days of buying and you get the whole payment back. The details are in the terms.
Is this an official Google Cloud practice exam?
No. BytePatterns is not affiliated with, endorsed or sponsored by Google Cloud. Every question is written by us from the public exam guide and the Google Cloud documentation, never from real exam content, and a score here does not predict your result on the real exam. Google Cloud lists its own preparation resources on its certification page.