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| Section | Weight | Objectives |
|---|---|---|
| Techniques to Improve Generative AI Model Output | 20% | - Mitigation of bias and inaccuracies - Prompt engineering principles and best practices - Fine-tuning and adaptation methods - Evaluation and optimization of output quality |
| Fundamentals of Generative AI | 30% | - Key technologies and differences from traditional AI - Responsible AI principles and application - Core concepts and characteristics of generative AI - Foundation models: definition, capabilities, and use cases |
| Business Strategies for Successful Generative AI Solutions | 15% | - Identifying business use cases and value opportunities - Planning and adoption frameworks - Governance, risk management, and compliance - Scaling and measuring success of generative AI initiatives |
| Google Cloud's Generative AI Offerings | 35% | - Overview of Google Cloud generative AI services and tools - Vertex AI generative AI capabilities - Generative AI application development platforms - Model Garden and available models - Enterprise integration and security features |
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NEW QUESTION # 26
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?
Answer: C
Explanation:
Data is typically classified into two main types: structured and unstructured.
Structured data is highly organized, formatted for a predefined data model, and easily searchable in tabular form (e.g., columns and rows in a database, like customer names, order IDs, or star ratings). Unstructured data lacks a pre-defined format or organization. The customer feedback described is a detailed, free-text response written in the customer's own words. This qualitative data, whether it is an email, an essay, or a long-form survey response, does not fit into fixed fields and requires advanced Natural Language Processing (NLP) or Generative AI techniques to extract meaning. Since the text is non-tabular and has no inherent structure enforced by the collection method, it is correctly classified as Unstructured Data.
NEW QUESTION # 27
A large e-commerce company with a substantial product catalog and many support documents has customers struggling to find information on their website. This leads to high support costs and poor user experience. The company wants a Google Cloud solution to improve website search and reduce support costs while improving customer satisfaction. What Google Cloud product should the company use?
Answer: A
NEW QUESTION # 28
A team is discussing the different layers of the generative AI (gen AI) landscape and where specific tools and technologies fit within those layers. They want to clarify the role of Gemini Enterprise Agent Platform and data management tools in the overall landscape. In which layer of the generative AI landscape are Gemini Enterprise Agent Platform and data management tools?
Answer: D
Explanation:
The generative AI technology stack consists of four key layers:
Infrastructure: Compute (TPUs, GPUs, Compute Engine), networking, and physical infrastructure.
Models: Foundation models (Gemini, Gemma, Imagen, third-party models in Model Garden).
Platform: Development and management software suites-including Gemini Enterprise Agent Platform (formerly Vertex AI), Vertex AI Studio, Model Registry, and data management/grounding services-used to build, tune, evaluate, and orchestrate workloads.
Agents / Applications: End-user conversational agents, copilots, and business applications delivering specific capabilities.
NEW QUESTION # 29
A large e-commerce company with a vast and frequently updated product catalog finds that customers struggle to find products on their website, and support agents spend too much time finding detailed product information. The company wants to improve search accuracy and efficiency for both customers and support.
What Google Cloud solution should they use?
Answer: A
Explanation:
This scenario strongly points to the need for accurate and up-to-date information retrieval from a product catalog. Pre-built RAG (Retrieval-Augmented Generation) combined with Vertex AI Search is the ideal solution. Vertex AI Search can index the product catalog, and RAG can then use thisindexed data to ground the responses of a generative AI model, ensuring that both customer searches and support agent queries retrieve precise and relevant product information.
________________________________________
NEW QUESTION # 30
What is the function of the platform layer in the generative AI (gen AI) landscape?
Answer: C
NEW QUESTION # 31
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