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Google Generative-AI-Leader Exam Syllabus Topics:

TopicDetails
Topic 1
  • Google Cloud’s Generative AI Offerings: This section of the exam measures the skills of Cloud Architects and highlights Google Cloud’s strengths in generative AI. It emphasizes Google’s AI-first approach, enterprise-ready platform, and open ecosystem. Candidates will learn about Google’s AI infrastructure, including TPUs, GPUs, and data centers, and how the platform provides secure, scalable, and privacy-conscious solutions. The section also explores prebuilt AI tools such as Gemini, Workspace integrations, and Agentspace, while demonstrating how these offerings enhance customer experience and empower developers to build with Vertex AI, RAG capabilities, and agent tooling.
Topic 2
  • Business Strategies for a Successful Generative AI Solution: This section of the exam measures the skills of Cloud Architects and evaluates the ability to design, implement, and manage enterprise-level generative AI solutions. It covers the decision-making process for selecting the right solution, integrating AI into an organization, and measuring business impact. A strong emphasis is placed on secure AI practices, highlighting Google’s Secure AI Framework and cloud security tools, as well as the importance of responsible AI, including fairness, transparency, privacy, and accountability.
Topic 3
  • Techniques to Improve Generative AI Model Output: This section of the exam measures the skills of AI Engineers and focuses on improving model reliability and performance. It introduces best practices to address common foundation model limitations such as bias, hallucinations, and data dependency, using methods like retrieval-augmented generation, prompt engineering, and human-in-the-loop systems. Candidates are also tested on different prompting techniques, grounding approaches, and the ability to configure model settings such as temperature and token count to optimize results.
Topic 4
  • Fundamentals of Generative AI: This section of the exam measures the skills of AI Engineers and focuses on the foundational concepts of generative AI. It covers the basics of artificial intelligence, natural language processing, machine learning approaches, and the role of foundation models. Candidates are expected to understand the machine learning lifecycle, data quality, and the use of structured and unstructured data. The section also evaluates knowledge of business use cases such as text, image, code, and video generation, along with the ability to identify when and how to select the right model for specific organizational needs.

Reference: https://cloud.google.com/developers/generative-ai-leader

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Google Cloud Certified - Generative AI Leader Sample Questions:

A human resources team is implementing a new generative AI application to assist the department in screening a large volume of job applications. They want to ensure fairness and build trust with potential candidates. What should the team prioritize?

  • A. Ensuring that the AI application can automatically rank all candidates without requiring human review.
  • B. Ensuring AI operates transparently, especially regarding application evaluation and data usage.
  • C. Integrating the AI application with various job boards to maximize candidate reach.
  • D. Focusing on minimizing the processing time for each application to improve efficiency.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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An organization wants to use generative AI to create a marketing campaign. They need to ensure that the AI model generates text that is appropriate for the target audience. What should the organization do?

  • A. Use few-shot prompting.
  • B. Use prompt chaining.
  • C. Adjust the temperature parameter.
  • D. Use role prompting.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Explanation: Only visible for PrepAwayExam members. You can sign-up / login (it's free).

A company has launched a new generative AI-powered chatbot on its customer service portal to handle frequently asked questions. They want to monitor the new chatbot's performance over time to ensure it continues to perform well. What Google-recommended practice should they use?

  • A. Defining and tracking key performance indicators (KPIs).
  • B. A/B testing of different chatbot conversation flows.
  • C. Prompting the chatbot to rate its performance.
  • D. Using a human-in-the-loop (HITL) review process for chatbot interactions.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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A company is evaluating different generative AI (gen AI) platforms and wants to understand the role of the infrastructure layer in supporting the development and deployment of gen AI models. What is the function of the infrastructure layer in the gen AI landscape?

  • A. To provide a user-friendly interface for interacting with gen AI models.
  • B. To provide the compute resources needed to run and train AI models and store training data.
  • C. To provide access to pre-trained gen AI models.
  • D. To provide tools and resources for building and deploying gen AI applications.
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Explanation: Only visible for PrepAwayExam members. You can sign-up / login (it's free).

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 a. What is a key benefit of implementing retrieval-augmented generation (RAG) in this chatbot?

  • A. RAG will primarily help the chatbot generate more creative and engaging conversational responses.
  • B. RAG will significantly reduce the computational resources required to run the generative AI model.
  • C. RAG will enable the chatbot to access and utilize external, up-to-date knowledge sources to provide more accurate and relevant answers.
  • D. RAG will enable the chatbot to fine-tune its underlying language model on the fly based on customer interactions.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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