Google Cloud Generative AI Leader: 6 Practice Exams 2026

About this course

Find out whether you are ready before you pay for the real exam.

This course gives you 6 full-length practice exams, 55 questions each, 330 questions in total. Every test is built to the official blueprint: 30% Fundamentals of gen AI, 35% Google Cloud's gen AI offerings, 20% Techniques to improve model output, 15% Business strategies.

Every question explains all four options. You learn why the correct answer is right and, just as important, why each of the other three is wrong. That is where the real learning happens, because on this exam the wrong answers are usually real Google products placed in the wrong situation.

What the questions actually cover

Fundamentals: structured vs unstructured and labelled vs unlabelled data, data quality and accessibility, supervised, unsupervised and reinforcement learning, the ML lifecycle, the five landscape layers, choosing a foundation model, and the strengths of Gemini, Gemma, Imagen and Veo.

Google Cloud offerings: Gemini Enterprise and Agent Search, Agent Platform and Model Garden, the Gemini app and Gems, Google Workspace with Gemini, Gemini for Google Cloud, Gemini Notebook, the Customer Engagement Suite (Agent Assist, Conversational Agents, Conversational Insights, CCaaS), Google AI Studio vs Agent Studio, pre-built APIs, TPUs and AI infrastructure.

Improving output: grounding and RAG, prompt engineering from zero-shot to few-shot, role prompting, chain-of-thought and ReAct, temperature, top-p and output length, fine-tuning vs grounding, model limitations such as hallucinations and knowledge cutoff, human-in-the-loop review, and model monitoring.

Business strategy: the Secure AI Framework (SAIF), IAM and Security Command Center, responsible AI, bias and fairness, privacy including anonymisation and pseudonymisation, measuring ROI, and driving adoption.

Written for the 2026 exam.

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