Generative-AI-Leader Practice Exams and Training Solutions for Certifications [Q22-Q43]

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Generative-AI-Leader Practice Exams and Training Solutions for Certifications

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Google Generative-AI-Leader Exam Syllabus Topics:

Topic	Details
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.

QUESTION 22
A company wants to choose a generative AI (gen AI) use case that will be successful and have the most impact. What key factor should they determine first according to Google Cloud- recommended practices?

The number of employees who will be trained to use the new gen AI tools.

The specific business problems the company aims to solve and the desired outcomes.

The availability of pre-trained models that are offered on various cloud computing platforms.

The frequency of updates to the underlying foundation models used by different gen AI platforms.

QUESTION 23
A company is developing an AI character for a video game. The AI character needs to learn how to navigate a complex environment and make decisions to achieve certain objectives within the game. When the AI takes actions that lead to positive outcomes, like finding a reward or overcoming an obstacle, it receives a positive score. When it takes actions that lead to negative outcomes, like hitting a wall or losing progress, it receives a negative score. Through this process of trial and error, the AI gradually improves the character’s ability to play the game effectively.
What machine learning should the company use?

Deep learning

Reinforcement learning

Supervised learning

Unsupervised learning

QUESTION 24
A research team has collected a large dataset of sensor readings from various industrial machines. This dataset includes measurements like temperature, pressure, vibration levels, and electrical current, recorded at regular intervals. The team has not yet assigned any labels or categories to these readings and wants to identify potential anomalies, malfunctions, or natural groupings of machine behavior based on the sensor data alone. What type of machine learning should they use?

Reinforcement learning

Unsupervised learning

Deep learning

Supervised learning

QUESTION 25
A data analyst at MetroVoyage tests a foundation model by writing the prompt “Translate the phrase ‘good evening’ into Italian.” The instruction is given directly and no example translations are included. Which prompting technique is being applied?

Few-shot prompting

Role prompting

Zero-shot prompting

One-shot prompting

QUESTION 26
A company wants to choose a generative AI (gen AI) use case that will be successful and have the most impact. What key factor should they determine first according to Google Cloud-recommended practices?

The number of employees who will be trained to use the new gen AI tools.

The specific business problems the company aims to solve and the desired outcomes.

The availability of pre-trained models that are offered on various cloud computing platforms.

The frequency of updates to the underlying foundation models used by different gen AI platforms.

QUESTION 27
A financial services company receives a high volume of loan applications daily submitted as scanned documents and PDFs with varying layouts. The manual process of extracting key information is time-consuming and prone to errors. This causes delays in loan processing and impacts customer satisfaction. The company wants to automate the extraction of this critical data to improve efficiency and accuracy. Which Google Cloud tool should they use?

Natural Language API

Dataflow

Vision AI

Document AI API

QUESTION 28
An animation studio needs to swiftly produce brief animated cartoons based on written descriptions of scenes and character actions. They want to preview their animated storyboards and obtain rapid feedback on the story and flow. Why should they use Veo for this task?

Veo is a lightweight model that offers a customizable solution for specialized AI applications.

Veo is optimized for generating high-quality and natural-sounding speech.

Veo is optimized for producing video from text and still pictures.

Veo is a powerful multimodal model that can process and produce code for applications.

QUESTION 29
A finance team wants to use Gemma to help with daily tasks so that the financial analysts can focus on other work. Which business problem can Gemma most efficiently address?

The complexity of building and deploying sophisticated internal knowledge bases to answer employees
‘ finance-related questions with accurate and up-to-date information.

The difficulty in analyzing large datasets of financial transactions and market data to identify anomalies and predict future financial performance.

The struggle to accurately extract key financial figures and insights from a variety of document formats, such as balance sheets and income statements, for quick reporting.

The challenge of efficiently producing high-quality written summaries and initial drafts of financial communications.

QUESTION 30
A travel app asks users to take a photo of a famous landmark and then returns a written overview with historical notes and nearby attractions. The system’s capability to interpret the picture and produce natural language output reflects what kind of model?

An image classification model

A multimodal learning model

A time-series forecasting model

A text-only unimodal model

QUESTION 31
A marketing team wants to use a generative AI model to create product descriptions for their new line of eco-friendly water bottles. They provide a brief prompt stating, “Write a product description for our new water bottle.” The model generates a generic, lackluster description that is factually accurate but lacks engaging language and doesn’t highlight the environmental benefits that are key to their brand. What should the marketing team do to overcome this limitation of the generated product description?

Train the model on a dataset of marketing materials from other eco-friendly brands.

Add details to the prompt about the audience, tone, and keywords.

Increase the token count for the model to allow for longer descriptions.

Lower the temperature setting of the model to produce more consistent results.

QUESTION 32
An organization is increasingly concerned about the security of its sensitive business data as it begins to use generative AI applications that are hosted on Google Cloud. They want to ensure that the underlying infrastructure itself has robust security measures built in from the ground up to protect against potential threats and vulnerabilities. What Google Cloud security features directly address this need?

Google Cloud Observability

Identity and Access Management

Security Command Center

Secure-by-design infrastructure

QUESTION 33
What will Google Cloud’s Agent Assist help a company achieve?

The infrastructure to provide an enterprise-grade contact center solution with omnichannel support, routing, and integration with CRM systems.

The ability to analyze conversational data to identify customer sentiment, common topics of discussion, and insights into agent performance and customer experience.

The ability to provide real-time assistance and recommended responses to live customer service agents during their interactions.

The ability to build and deploy deterministic and generative chatbot agents for automated customer support.

QUESTION 34
Pike and Rowan Law uses a generative AI system to produce first draft contract clauses for its clients. To ensure accuracy and compliance, a licensed attorney must review, edit, and approve each AI draft before any client sees it. This addition of expert oversight within the AI workflow represents which recommended practice?

Vertex AI Guardrails

Human in the Loop (HITL)

Fine-tuning

Grounding

QUESTION 35
A software developer needs a highly efficient, open-source large language model that can be fine-tuned on a local machine for rapid prototyping of a chatbot application. They require a model that offers strong performance in natural language understanding and generation, while being lightweight enough to run on limited hardware. Which Google-developed family of models should they use?

Veo

Gemini

Gemma

Imagen

QUESTION 36
An order fulfillment team has an agent that automatically processes orders, updates inventory, sends shipping notifications, and handles returns. What type of agent is this?

A workflow agent

An employee productivity agent

A customer service agent

A conversational agent

QUESTION 37
A social media platform uses a generative AI model to automatically generate summaries of user-submitted posts to provide quick overviews for other users. While the summaries are generally accurate for factual posts, the model occasionally misinterprets sarcasm, satire, or nuanced opinions, leading to summaries that misrepresent the original intent and potentially cause misunderstandings or offense among users. What should the platform do to overcome this limitation of the AI-generated summaries?

Implement stricter safety settings to filter out potentially misinterpreted content altogether.

Increase the temperature parameter of the model to encourage more varied and less literal interpretations.

Decrease the output length of the summaries to make them more concise.

Incorporate a human-in-the-loop (HITL) review process to refine the summaries.

QUESTION 38
A company is developing a conversational AI chatbot. They need to ensure the chatbot can engage in human-like conversations and provide accurate information. What should they do to enhance the chatbot’s ability to understand and respond effectively to user prompts?

Use prompt engineering techniques, like few-shot prompting, to provide the chatbot with examples of successful interactions.

Limit the chatbot’s training data to prevent it from learning irrelevant information.

Use strict keyword matching to ensure that the chatbot only responds to specific commands.

Lower model temperature setting to produce more consistent and predictable responses.

QUESTION 39
An online travel marketplace plans to pilot a generative AI system that crafts personalized in app messages to promote weekend deals. Executives want clarity on which factors should be treated as business requirements because they will guide solution objectives and success criteria. Which factor would count as a business requirement that would shape the gen AI approach?

Whether inference will be deployed on Cloud Run or on Google Kubernetes Engine

The targeted percentage lift in open rate for those in app messages

Selecting a foundation model from Vertex AI Model Garden versus custom model training

The availability of NVIDIA GPUs for training and fine tuning

QUESTION 40
A company ‘ s sales team spends a significant amount of time researching potential leads and manually entering data into their customer relationship management (CRM) tool. They want to improve the team ‘ s efficiency and enable them to focus on building relationships and closing deals. What should the organization do?

Integrate the CRM with a popular sales intelligence platform to automatically enrich lead profiles with valuable data.

Develop a custom AI solution using Google Cloud’s AutoML Natural Language to analyze lead communications and automatically update the CRM.

Implement Gemini Enterprise ” unified enterprise search ” including a CRM agent to automate lead research and data entry.

Implement Google Cloud ‘ s Contact Center AI to qualify leads and route them to the appropriate sales representatives.

QUESTION 41
A company collects customer feedback through open-ended survey questions where customers can write detailed responses in their own words, such as “The product was easy to use, and the customer support was excellent, but the delivery took longer than expected.” What type of data is this?

Unstructured data

Structured data

Labeled data

Quantitative data

QUESTION 42
A company wants to use generative AI to create a chatbot that can answer customer questions about their products and services. They need to ensure that the chatbot only uses information from the company’s official documentation. What should the company do?

Use role prompting.

Adjust the temperature parameter.

Use prompt chaining.

Use grounding.

QUESTION 43
A national bank is overwhelmed by customer inquiries across multiple channels and needs an AI-powered solution to provide seamless, consistent support, empower customer support agents, and improve service quality. What Google Cloud product should the bank use?

Vertex AI Search

Gemini for Google Workspace

Google Contact Center as a Service

Gemini for Google Cloud