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所在平台: Udemy |
课程主页: https://www.udemy.com/course/googlecloud-genai/
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**Coursera 课程总结：Google Cloud 生成式 AI 领导者认证考试（Google Cloud Generative AI Leader Certification Test Exam）** 本课程旨在帮助学员成为一名卓越的 Google Cloud 生成式 AI 领导者，他们能够精准识别生成式 AI（Gen AI）如何在企业中发挥变革作用并加以应用。课程包含四套模拟考试，分别包含 45、45、30 和 45 道题目，这些题目经过精心设计，力求贴近真实的认证考试内容，为您的成功保驾护航。 成为一名生成式 AI 领导者，您将掌握 Google Cloud Gen AI 产品和服务的业务层面知识，从而有力推动组织内 AI 的创新和负责任的应用。我们的模拟考试在题目权重上精确对应了官方的 Google Cloud 生成式 AI 领导者考试指南，全面涵盖了所有关键考点： * **Gen AI 基础知识（约占考试的 30%）：** 深入了解 Gen AI 的核心概念，如大型语言模型、提示工程和扩散模型，以及机器学习生命周期。学习如何为特定的企业用例选择合适的基金模型，并理解不同数据类型在 Gen AI 中的业务影响。 * **Google Cloud 的 Gen AI 产品（约占考试的 35%）：** 掌握 Google 的 AI 优先策略和企业级 AI 平台。熟悉 Gemini 应用和 Gemini for Google Workspace 等预构建产品，以及 Vertex AI 平台（包括 Model Garden 和 Vertex AI Search）等开发者工具。 * **提升 Gen AI 模型输出的技巧（约占考试的 20%）：** 学习如何解决生成式 AI 的常见局限性，例如模型“幻觉”（hallucinations）和知识截止日期问题。精通提示工程技巧（如 zero-shot、few-shot、chain-of-thought），并理解检索增强生成（RAG）等模型输出的 grounding 技术。 * **成功的 Gen AI 解决方案的业务策略（约占考试的 15%）：** 掌握将 Gen AI 整合到组织中的关键步骤，理解 Google 安全 AI 框架（SAIF）的重要性，以及包括隐私、公平性和问责制在内的关键负责任 AI 原则。 在模拟考试 #1、#2 和 #3 中，请特别关注带有星号 (*) 的题目，这些题目旨在模仿真实认证考试的题型。您作为生成式 AI 领导者的专长体现在战略领导力和影响力，而非深层技术实现，但扎实的理论概念理解至关重要。建议您在模拟考试中力争达到 80% 的分数线。通过结合这些有针对性的练习以及学习 Google 的官方学习路径，您将为通过认证考试并自信地领导富有成效的 Gen AI 计划做好充分准备。
Step into the role of a Google Cloud Certified Generative AI Leader, a visionary professional adept at identifying how generative AI (gen AI) can transform and be used within a business. This course features four practice exams (with 45, 45, 30, and 45 questions respectively) meticulously designed to mirror the actual certification content and ensure your success. As a Generative AI Leader, you'll possess business-level knowledge of Google Cloud's gen AI products and services, enabling you to influence innovative and responsible AI adoption within your organization.Our practice exams are precisely weighted to reflect the official Google Cloud Generative AI Leader exam guide, covering all critical sections:Fundamentals of Gen AI (~30% of the exam): Explore core gen AI concepts (like large language models, prompt engineering, and diffusion models), the machine learning lifecycle, how to choose appropriate foundation models for business use cases, and the business implications of various data types in gen AI.Google Cloud's Gen AI Offerings (~35% of the exam): Understand Google's AI-first approach and enterprise-ready AI platform. Familiarize yourself with prebuilt offerings like the Gemini app and Gemini for Google Workspace, and developer tools such as Vertex AI Platform, including Model Garden and Vertex AI Search.Techniques to Improve Gen AI Model Output (~20% of the exam): Learn to address common foundation model limitations like hallucinations and the knowledge cutoff. Master prompt engineering techniques (zero-shot, few-shot, chain-of-thought) and understand grounding techniques, including retrieval-augmented generation (RAG).Business Strategies for a Successful Gen AI Solution (~15% of the exam): Grasp the steps to integrate gen AI into an organization, the importance of Google's Secure AI Framework (SAIF), and crucial responsible AI principles including privacy, fairness, and accountability.Pay special attention to questions marked with an asterisk (*) in exams #1, #2, and #3, as these are styled to reflect questions encountered in the real certification exam. Your expertise as a Generative AI Leader lies in strategic leadership and influence, not deep technical implementation, though a strong conceptual understanding is vital. We recommend aiming for an 80% benchmark on these practice exams. By combining this targeted practice with study of Google's official learning path, you'll be thoroughly prepared to pass your certification and confidently lead impactful gen AI initiatives.
