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Unlock every Google Cloud Generative AI Leader mock on explainx.
Independent practice — not Anthropic's proctored certification.
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Eight timed drills on explainx — unlock all for $5 lifetime.
Balanced 25-question drill across all four domains with mixed business scenarios.
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Second full mixed mock — new shuffle from the question bank.
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Core concepts, ML lifecycle, data quality, gen AI landscape layers, and Google's foundation models.
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Gemini apps, Gemini Enterprise, customer-experience suite, developer tooling, and agent tooling.
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Grounding, RAG, prompt engineering, fine-tuning, HITL, and sampling parameters.
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Implementation steps, secure AI / SAIF, and responsible AI — privacy, accountability, explainability.
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Scenario-framed questions simulating six business contexts for a gen AI leader.
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55 questions, 90 minutes — closest pacing to the official proctored Generative AI Leader exam.
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Official weightings for the Generative AI Leader exam.
Six production scenario frames for practice questions.
The Retail Contact-Center Rollout
A VP of Customer Experience weighs deterministic Conversational Agents against a generative agent for open-ended queries, measuring success via deflection rate and CSAT.
Healthcare Compliance & Grounding
A hospital operations director wants gen AI to summarize intake notes but fears hallucinated clinical facts, and needs a conceptual grasp of grounding and RAG to ask the right questions.
Marketing Content at Scale
A CMO scaling content production hits inconsistent brand voice and factual errors, and must choose between prompt engineering, fine-tuning, and grounding.
Legal Ops Knowledge Search Rollout
A law-firm ops lead wants natural-language search across contracts and SharePoint without engineers, evaluating Gemini Enterprise and Agent Search versus a narrow point solution.
Manufacturing Data Readiness Audit
An operations executive discovers unstructured, unlabeled maintenance logs blocking a gen AI pilot, and must reason about data quality and readiness before proceeding.
Board-Level AI Investment Pitch
A CFO evaluates a seven-figure gen AI initiative — build-vs-buy, an ROI framework, and SAIF, IAM, and Security Command Center governance.
Google Cloud positions the Generative AI Leader credential for business-level, non-technical professionals who champion, evaluate, or approve gen AI initiatives. There are no prerequisites and no coding — the exam tests gen AI literacy and strategy about Gemini, Google Cloud offerings, grounding, and responsible AI, not engineering.
Summarized from Google Cloud's public Generative AI Leader exam guide — confirm on Google Cloud Certification before you schedule.
The official guide lists four weighted domains and granular task statements. explainx practice questions target these competencies — use this map to plan study time and pick focused mock tests.
1.1 Explain the fundamentals of gen AI
1.2 Describe the types of data used in gen AI
Practice questions are scenario-framed around realistic business gen AI decisions — contact centers, compliance and grounding, content at scale, knowledge search, data readiness, and board-level investment.
The Retail Contact-Center Rollout
A VP of Customer Experience must decide between deterministic Conversational Agents for known intents and a generative agent for open-ended questions. Success is measured by deflection rate and CSAT, and the exam-style judgment is knowing that Conversational Agents are hybrid deterministic-plus-generative, not 'just a chatbot.'
Domains: Business Strategy · Google Cloud Offerings
Healthcare Compliance & Grounding
A hospital operations director wants gen AI to summarize patient intake notes but fears hallucinated clinical facts. The leader does not build the system but needs enough conceptual grasp of grounding and RAG to ask vendors the right questions and set guardrails.
Domains: Model Output Techniques · Business Strategy
Marketing Content at Scale
A CMO scaling content production hits inconsistent brand voice and occasional factual errors. The decision is whether prompt engineering, fine-tuning, or grounding is the right (and most cost-effective) fix — with fine-tuning being the classic over-reached-for answer.
Domains: Model Output Techniques
Legal Ops Knowledge Search Rollout
A law-firm operations lead wants natural-language search across contracts and SharePoint without hiring engineers. The evaluation pits Gemini Enterprise with Agent Search (broad org search with connectors) against a narrow point solution and NotebookLM Enterprise (curated deep research).
Domains: Google Cloud Offerings
Independent mock exams aligned to the Generative AI Leader exam guide — not affiliated with Google Cloud's proctored certification. 452 multiple-choice questions in the bank, shuffled every attempt, instant explanations after submit.
Quick answers for candidates preparing with explainx mock exams (not Anthropic support).
Anthropic's ~301-level proctored certification for solution architects building production apps with Claude Code, the Claude Agent SDK, MCP, and structured output. The official exam has 60 multiple-choice questions in 120 minutes, four scenario frames per sitting, and a scaled pass score of 720/1000.
Five weighted areas: Agentic Architecture & Orchestration (27%), Tool Design & MCP Integration (18%), Claude Code Configuration & Workflows (20%), Prompt Engineering & Structured Output (20%), and Context Management & Reliability (15%).
No. explainx.ai offers independent practice mock tests aligned to the public Foundations Exam Guide domains, task statements, and scenarios. Official registration and proctoring are through Anthropic Academy / Skilljar.
Lifetime access to all Claude Certified Architect mock tests on explainx.ai is $5 USD (one-time). Each attempt draws a shuffled subset from a bank of 1,000+ practice questions with explanations after submit.
You can browse certification and test pages without an account. Starting a timed mock test requires signing in and purchasing lifetime practice access for that program.
Eight mock tests per program including a full exam simulation, plus 1,000+ banked multiple-choice items. Programs include Claude Certified Architect (agentic architecture, MCP, Claude Code) and AWS GenAI Developer Professional (Bedrock, RAG, agents, governance).
Questions mirror the six official production scenarios: customer support agents, Claude Code development, multi-agent research, developer productivity, CI/CD with Claude Code, and structured data extraction.
Use Anthropic's Foundations Exam Guide and Academy courses for the proctored exam. Use explainx mock tests for timed MCQ practice, domain drills, and instant feedback — especially scenario-framed items and tradeoff questions.
A business-level, non-technical Google Cloud certification. The 90-minute exam has 50-60 multiple-choice questions across four domains — gen AI fundamentals, Google Cloud's gen AI offerings, techniques to improve model output, and business strategy — with no prerequisites required.
Microsoft's Associate-level certification for Azure AI engineers building generative AI apps and agents with Microsoft Foundry and Python. The 120-minute exam covers five domains with a minimum passing score of 700/1000.
1.3 Describe the core layers of the gen AI landscape
1.4 Describe Google's foundation models
2.1 Describe Google Cloud's strengths in gen AI
2.2 Describe Google Cloud's prebuilt gen AI offerings
2.3 Describe customer experience offerings
2.4 Describe offerings that empower developers
2.5 Describe agent tooling
3.1 Describe how to overcome foundation model limitations
3.2 Describe prompt engineering techniques
3.3 Describe grounding techniques
4.1 Describe the steps to implement a gen AI solution
4.2 Describe how to secure a gen AI solution
4.3 Describe responsible AI practices
Manufacturing Data Readiness Audit
An operations executive discovers that maintenance logs are unstructured and unlabeled before a gen AI pilot can succeed. The leader must reason about data quality dimensions and readiness — and understand that unstructured data is usable, not automatically low quality.
Domains: Fundamentals
Board-Level AI Investment Pitch
A CFO evaluates a seven-figure gen AI initiative — build-vs-buy, an ROI framework that includes quality, speed, and risk reduction (not just cost savings), and governance through SAIF, IAM, and Security Command Center.
Domains: Business Strategy · Fundamentals
