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Generative AI Leader Certification Exam (Generative AI Leader Certification) - Google Cloud Exam Questions

Last updated on June 20, 2026

97% Exam Compliance
74 Total Questions
1
Question
A large company is creating their generative AI (gen AI) solution by using Google Cloud's offerings. They want to ensure that their mid-level managers contribute to a successful gen AI rollout by following Google-recommended practices. What should the mid-level managers do?
Options
A Secure funding and resources for AI initiatives by demonstrating the potential return on investment to the chief financial officer (CFO).
B Drive gen AI adoption by identifying high-impact, feasible solutions that address specific challenges within their workflows.
C Create a robust data strategy to ensure teams can access high-quality, relevant data that is appropriate for training and fine-tuning gen AI models.
D Perform continuous testing, measurement, and refinement based on user feedback and real- world performance data.
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2
Question
A data science team needs a centralized and organized location to store its various model versions, track their metadata, and easily deploy them to the respective applications. What Google Cloud
service should they use?
Options
A BigQuery
B Vertex AI Pipelines
C Cloud Storage
D Model Registry
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3
Question
A company is developing a generative AI-powered customer support chatbot. They want to ensure the chatbot can answer a wide range of customer questions accurately, even those related to recently updated product information not present in the model's original training dat
Options
A RAG will enable the chatbot to fine-tune its underlying language model on the fly based on customer interactions.
B RAG will significantly reduce the computational resources required to run the generative AI model.
C RAG will primarily help the chatbot generate more creative and engaging conversational responses.
D RAG will enable the chatbot to access and utilize external, up-to-date knowledge sources to provide more accurate and relevant answers.
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4
Question
A company’s large learning model (LLM) is producing hallucinations that are a result of the Knowledge cutoff. How does retrieval-augmented generation (RAG) overcome this limitation?
Options
A RAG enables the LLM to retrieve relevant and up-to-date information from knowledge sources.
B RAG fine-tunes the LLM on specific customer query patterns to improve the speed and efficiency of response generation.
C RAG enhances the creative writing capabilities of the LLM to generate more engaging and informative responses.
D RAG uses human oversight to ensure accuracy before presenting information to the customer.
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5
Question
What does a diffusion model do?
Options
A Facilitates the storage and management of structured data.
B Analyzes data and predicts future trends and patterns.
C Optimizes business processes and resource allocation.
D Generates high-quality content by refining noise into structured data.
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