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Google Cloud Generative AI Leader Training 2025 · LearnSpace
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courseraПрограммирование

Google Cloud Generative AI Leader Training 2025

Курс от Packt
Средний≈ 5.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Embark on a transformative journey with the Google Cloud Generative AI Leader Training, designed to equip you with the essential skills and knowledge to become a certified Generative AI leader. Through engaging lessons, you will understand the fundamental concepts of Generative AI, including the core technologies such as AI, machine learning, and natural language processing (NLP). The course will provide a comprehensive view of how these technologies are applied in real-world scenarios, particularly in Google Cloud’s ecosystem. You will also dive into critical aspects such as prompt engineering, model performance, and data management, with a focus on practical applications. As you progress, the course guides you through the Google Cloud tools and platforms specifically tailored for generative AI. From TPUs to enterprise-ready AI strategies, you will explore scalable AI solutions designed for businesses of all sizes. You will also be introduced to Google's unique AI technologies, including Gemini, Gemma, and Vertex AI. The course is structured to help you master everything from the AI lifecycle to deployment strategies, ensuring you are well-prepared to work with AI at the enterprise level. This course is ideal for those aiming to work with Google Cloud’s generative AI tools or seeking to build expertise in AI governance, security, and scalability. It's designed for learners interested in AI, cloud computing, and enterprise innovation. A background in technology or business is recommended, but there are no strict prerequisites. The course is suitable for intermediate learners seeking to enhance their expertise in the rapidly evolving field of AI. By the end of the course, you will be able to define key generative AI concepts, apply machine learning techniques to real-world problems, leverage Google Cloud tools to scale AI solutions, and integrate responsible AI practices in enterprise environments.

Навыки, которые вы освоите

Generative AIResponsible AIAI IntegrationsPrompt EngineeringAI SecurityLarge Language ModelingGoogle Cloud PlatformGoogle GeminiCloud SolutionsGeminiRisk MitigationGenerative Model ArchitecturesEnterprise ArchitectureModel DeploymentAI Product Strategy

Программа курса

6 модулей · 67 учебных материалов

01Introduction5 материалов

Introduction

Welcome to the Generative AI Leader Certification CourseВидеоFull Course ResourcesЧтениеGoogle Cloud Generative AI Leader - Exam Overview and Preparation StrategyВидеоWho Should Take This Course – Is This Course Right for You?Видео

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Packt - Course Instructors

Преподаватель курса

Google Cloud Generative AI Leader Training 2025
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Новые знания — в удобное для вас время.

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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 5.5 ч

6 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Индонезийский, Испанский, Японский

Часть программы вашего университета
How to Navigate and Maximize This CourseВидео
02Fundamentals of Generative AI: Concepts, Models, and Business Relevance16 материалов

Fundamentals of Generative AI: Concepts, Models, and Business Relevance

What is Generative AI (Generative AI Explained)? Definitions and DifferentiatorsВидеоCore Concepts of Generative AI: AI, ML, NLP, LLMs, and Foundation ModelsВидеоMastering Prompt Engineering, Diffusion Models, and Multimodal AIВидеоReal-World Business Applications of Generative AIВидеоSupervised, Unsupervised, and Reinforcement Learning in Generative AIВидеоThe Machine Learning Lifecycle: From Data Ingestion to Responsible DeploymentВидеоGoogle Cloud AI Tools Mapped to the ML LifecycleВидеоChoosing the Right Foundation Model: Modality, Context, and CostВидеоModel Performance, Fine-Tuning, and Security in Generative AIВидеоData Quality and Accessibility: Foundations of Responsible AIВидеоStructured vs. Unstructured Data in Generative AI WorkflowsВидеоLabeled vs. Unlabeled Data: Choosing the Right Training StrategyВидеоThe Gen AI Technology Stack: From Infrastructure to ApplicationsВидеоGemini, Gemma, Imagen, and Veo: Google's Foundation Models ExplainedВидеоDistinguishing Generative AI from Traditional AI and Managing Enterprise Data QualityDIALOGUEFundamentals of Generative AI: Concepts, Models, and Business Relevance - AssessmentЗадание
03Google Cloud Gen AI: Platform, Tools, and Enterprise Capabilities18 материалов

Google Cloud Gen AI: Platform, Tools, and Enterprise Capabilities

What Sets Google Apart in Generative AIВидеоEnterprise-Ready AI: Privacy, Scale, and Reliability on Google CloudВидеоOpen, Governed, and Accountable: Google's AI Strategy for EnterprisesВидеоTPUs, GPUs, and the AI Hypercomputer: Scaling Performance with GoogleВидеоData Privacy, Model Governance, and Control with Google Cloud AIВидеоGemini App vs. Gemini Advanced: Choosing the Right Enterprise ToolВидеоGoogle Agentspace: Custom Agents, NotebookLM, and Search IntegrationВидеоGemini for Google Workspace: AI Inside Gmail, Docs, Sheets, and MoreВидеоVertex AI Search vs. Google Search: Enterprise Knowledge RetrievalВидеоCustomer Engagement AI: Contact Center, Agent Assist, and InsightsВидеоVertex AI, Model Garden, and AutoML: Tools for Every Developer LevelВидеоRetrieval-Augmented Generation (RAG): APIs and Enterprise WorkflowsВидеоVertex AI Agent Builder: Low-Code Tools for Custom AI WorkflowsВидеоExtensions, Plugins, and Data Access: Making Agents ActionableВидеоSpeech, Vision, Translation, and Document AI: Google Cloud APIsВидеоGoogle AI Studio vs. Vertex AI Studio: Prototyping vs. ProductionВидеоBuilding Enterprise AI Agents with Google CloudDIALOGUEGoogle Cloud Gen AI: Platform, Tools, and Enterprise Capabilities - AssessmentЗадание
04Responsible Generative AI: Risks, Grounding, and Output Control11 материалов

Responsible Generative AI: Risks, Grounding, and Output Control

Common Gen AI Risks: Bias, Hallucination & Knowledge GapsВидеоMitigation Strategies: Grounding, RAG, HITL & Fine-TuningВидеоMonitoring Gen AI: KPIs, Observability & Feature StoreВидеоPrompt Engineering: Zero-Shot, One-Shot, and Few-Shot TechniquesВидеоRole Prompting and Prompt Chaining for Structured AI BehaviorВидеоChain-of-Thought and ReAct Prompting: Reasoning and ActionВидеоGrounding in Gen AI: Enterprise, Third-Party, and Public DataВидеоHow RAG Improves Output Accuracy, Relevance, and TrustВидеоTuning Output with Sampling Parameters: Tokens, Temperature, Top-pВидеоIdentifying and Mitigating GenAI Model RisksDIALOGUEResponsible Generative AI: Risks, Grounding, and Output Control - AssessmentЗадание
05Scaling and Governing Generative AI in the Enterprise11 материалов

Scaling and Governing Generative AI in the Enterprise

Mapping Solutions – Text, Image, Code, PersonalizationВидеоAligning Solutions with Business NeedsВидеоSteps to Integrate Gen AI into the EnterpriseВидеоImpact Measurement TechniquesВидеоGoogle's Secure AI Framework (SAIF)ВидеоIAM, Secure-by-Design Infrastructure, Monitoring ToolsВидеоTransparency, Explainability, and AccountabilityВидеоPrivacy – Anonymization, PseudonymizationВидеоBias, Fairness, and Ethical Business UseВидеоAligning Generative AI Modalities to Business ValueDIALOGUEScaling and Governing Generative AI in the Enterprise - AssessmentЗадание
06Final Exam Preparation and Leadership Readiness6 материалов

Final Exam Preparation and Leadership Readiness

Sample Questions and Practice WalkthroughВидеоCommon Mistakes and Time Management TipsВидеоFinal Exam Strategies and Certification SuccessВидеоFinal Exam Preparation and Leadership ReadinessЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание