Google DeepMind: Train A Small Language Model
Earned Jan 11, 2026 EST
安全与身份基础知识
Earned Jan 6, 2026 EST
使用 Google Cloud Observability 进行监控和记录
Earned Jan 4, 2026 EST
Logging and Monitoring in Google Cloud
Earned Jan 4, 2026 EST
在 Google Cloud 环境中使用 DevSecOps
Earned Jan 3, 2026 EST
Cloud Logging
Earned Jan 1, 2026 EST
Machine Learning Operations (MLOps): Getting Started
Earned Dec 29, 2025 EST
Google Kubernetes Engine Best Practices: Security
Earned Dec 29, 2025 EST
在 Google Cloud 中使用 Kubernetes
Earned Dec 29, 2025 EST
Getting Started with Terraform for Google Cloud
Earned Dec 29, 2025 EST
Hybrid Cloud Service Mesh with Anthos
Earned Dec 27, 2025 EST
可靠的 Google Cloud 基础设施: 设计和流程
Earned Dec 25, 2025 EST
生成式 AI：不只是聊天机器人
Earned Oct 6, 2025 EDT
Developing a Google SRE Culture
Earned Sep 24, 2025 EDT
适用于生成式 AI 的机器学习运维 (MLOps)
Earned Sep 11, 2025 EDT
负责任的 AI 简介
Earned Sep 4, 2025 EDT
大型语言模型简介
Earned Sep 4, 2025 EDT
Deutsche Bank: Prompt Engineering Fundamentals
Earned Sep 3, 2025 EDT
DEPRECATED Cloud Architecture
Earned Mar 17, 2023 EDT
在 Google Cloud 上使用 Terraform 构建基础设施
Earned Jan 19, 2023 EST
在 Google Cloud 上部署 Kubernetes 应用
Earned Jan 12, 2023 EST
开发 Google Cloud 网络
Earned Dec 30, 2022 EST
Using the Cloud SDK Command Line
Earned Dec 29, 2022 EST
为 Compute Engine 实现云负载均衡
Earned Dec 27, 2022 EST
在 Google Cloud 上实施云安全基础措施
Earned Dec 15, 2022 EST
构建安全的 Google Cloud 网络
Earned Dec 12, 2022 EST
在 Google Cloud 上设置应用开发环境
Earned Nov 3, 2022 EDT
Google Cloud 基础知识
Earned Nov 2, 2022 EDT
在本课程中，您将了解 Gemini（Google Cloud 推出的一款依托生成式 AI 的协作工具）如何帮助您使用 Google 产品和服务开发、测试、部署和管理应用。在 Gemini 的协助下，您可以学习如何开发和构建 Web 应用、修复应用中的错误、开发测试和查询数据。您可以通过实操实验了解如何利用 Gemini 来改进软件开发生命周期 (SDLC)。
Duet AI 已更名为 Gemini，这是我们的新一代模型。
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在本课程中，您将了解 Google Cloud 中依托生成式 AI 技术的协作工具 Gemini 如何帮助开发者构建应用。您将学习如何向 Gemini 输入提示，让其为您解释代码、推荐 Google Cloud 服务并为您的应用生成代码。您将通过实操实验体验 Gemini 对应用开发工作流的改进作用。
Duet AI 已更名为 Gemini，这是我们的新一代模型。
本课程全面概述了 Google Cloud 的智能体平台，包括 Vertex AI Agent Builder、Gemini Enterprise、Conversational Agents 和智能体开发套件。学员将了解每项产品的独特功能，区分具体应用场景的最佳解决方案，并获得有关创建搜索和聊天应用的基础知识。
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在本课程中，您将了解 Gemini（Google Cloud 的生成式 AI 赋能的协作工具）如何帮助分析客户数据并预测产品销售情况。此外，您还将了解如何在 BigQuery 中使用客户数据来识别、开发新客户并对其进行分类。通过动手实验，您将体验 Gemini 如何改进数据分析和机器学习工作流。
Duet AI 已更名为 Gemini，这是我们的新一代模型。
了解详情
这是一节入门级微课程，旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。
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Complete the advanced Google DeepMind: Train A Small Language Model skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Access this lab at no-cost by signing up for the no-cost subscription. Receive 35 free credits each month!
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安全是 Google Cloud 服务绝不妥协的核心原则，为此， Google Cloud 开发了特定工具，为您的所有项目提供 安全与身份保障。本入门课程中，您将了解 用于管理用户和虚拟机账号的 Google Cloud Identity and Access Management (IAM) 服务 并进行实操练习。您还将通过 配置 VPC 和 VPN 获取网络安全方面的实践经验，并了解有哪些工具可用于 抵御安全威胁和防止数据泄露。
Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.
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在本课程中，您将学习在 Google Cloud 上实施安全高效的 DevSecOps 实践所需的基本技能。您将学习如何使用 Artifact Registry、 Cloud Build、Cloud Deploy 和 Binary Authorization 等 Google Cloud 服务来保护开发流水线。这使您能够在整个 CI/CD 流水线中构建、测试和部署具有安全控制机制的容器化应用。
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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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Get Anthos Ready. This Google Kubernetes Engine-centric quest of best practice hands-on labs focuses on security at scale when deploying and managing production GKE environments -- specifically role-based access control, hardening, VPC networking, and binary authorization.
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Kubernetes 是最受欢迎的容器编排系统， Google Kubernetes Engine 专为支持 Google Cloud 中的托管式 Kubernetes 部署 而设计。在本高级课程中，您将亲自动手配置 Docker 映像、容器，并部署功能完备的 Kubernetes Engine 应用。 此课程将帮助您掌握在工作流中集成容器编排所需的 实用技能。 想要参加实操实验室挑战赛， 展示您的技能并检验所学知识？完成本课程后，不妨继续参与这项额外的 实验室挑战赛，赢得 Google Cloud 专属数字徽章。 该挑战赛位于在 Google Cloud 上部署 Kubernetes 应用课程的结尾处。
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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure.
Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
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This on-demand course equips students to understand and adopt Istio-based
service-mesh with Anthos for centralized observability, traffic management,
and service-level security.
This is the second course of the Architecting Hybrid Cloud Infrastructure with
Anthos series. After completing this course, learners should continue to the
Hybrid Cloud Multi-Cluster with Anthos course.
Completion of the Architecting with Google Kubernetes Engine path is a
prerequisite for this course.
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本课程指导学员运用久经考验的设计模式在 Google Cloud 上构建高度可靠且高效的解决方案。它是“Google Compute Engine 架构设计”或“Google Kubernetes Engine 架构设计”课程的延续，并假定您有使用其中任何一门课程所涵盖技术的实践经验。通过一系列演示、设计活动和动手实验，学员可以了解如何定义及平衡业务要求和技术要求，以便设计可靠性和可用性高、安全且经济实惠的 Google Cloud 部署。
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“生成式 AI：不只是聊天机器人”是 Generative AI Leader 学习路线中的第一门课程。学习本课程没有知识门槛。本课程旨在帮助您超越对聊天机器人的基本认知,探索生成式 AI技术为您的组织带来的真正潜力。您将探索基础模型和提示工程等概念,这些知识对利用生成式 AI 的强大功能至关重要。本课程还将说明,为组织制定成功的生成式 AI 策略时,需要考虑哪些重要因素。
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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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本课程致力于为您提供所需的知识和工具，让您能够了解 MLOps 团队在部署和管理生成式 AI 模型以及探索 Vertex AI 如何帮助 AI 团队简化 MLOps 流程时面临的独特挑战，并帮助您在生成式 AI 项目中取得成功。
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这是一节入门级微课程，旨在解释什么是负责任的 AI、它的重要性，以及 Google 如何在自己的产品中实现负责任的 AI。此外，本课程还介绍了 Google 的 7 个 AI 开发原则。
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这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
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Master your Gen AI skills through hands-on labs!
Embark on a dynamic learning experience with Prompt Engineering Fundamentals, where you'll learn the art of designing effective prompts that harness the full power of Generative AI. Dive into the essentials of crafting clear and compelling prompts while exploring advanced techniques such as few-shot and Free-form prompting. Through hands-on labs, you'll apply your newfound skills to creatively analyze images, design prompts, and generate conversations directly on the Google Cloud console.
Upon completion, you'll earn a digital badge showcasing your newly acquired skills, perfect for highlighting on your LinkedIn profile and email signature. Remember to click "End" after finishing each lab to claim your well-deserved points.
This course is OPTIONAL, nevertheless HIGHLY recommended.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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完成在 Google Cloud 上使用 Terraform 构建基础设施技能徽章中级课程， 展示您在以下方面的技能：在使用 Terraform 时遵循基础设施即代码 (IaC) 原则；利用 Terraform 配置 来预配和管理 Google Cloud 资源；管理有效状态（本地和远程）；以及将 Terraform 代码模块化，以方便重复使用和整理。
For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.
适用于端到端 SDLC 的 Gemini
Earned Apr 13, 2026 EDT
适用于应用开发者的 Gemini
Earned Apr 3, 2026 EDT
编码器-解码器架构
Earned Jan 29, 2026 EST
注意力机制
Earned Jan 29, 2026 EST
图像生成简介
Earned Jan 29, 2026 EST
Gemini Enterprise 简介
Earned Jan 28, 2026 EST
了解 Google Cloud 智能体
Earned Jan 28, 2026 EST
面向数据科学家和分析师的 Gemini
Earned Jan 18, 2026 EST
生成式 AI 简介
Earned Jan 18, 2026 EST
Google DeepMind: Train A Small Language Model
Earned Jan 11, 2026 EST
安全与身份基础知识
Earned Jan 6, 2026 EST
使用 Google Cloud Observability 进行监控和记录
Earned Jan 4, 2026 EST
Logging and Monitoring in Google Cloud
Earned Jan 4, 2026 EST
在 Google Cloud 环境中使用 DevSecOps
Earned Jan 3, 2026 EST
Cloud Logging
Earned Jan 1, 2026 EST
Machine Learning Operations (MLOps): Getting Started
Earned Dec 29, 2025 EST
Google Kubernetes Engine Best Practices: Security
Earned Dec 29, 2025 EST
在 Google Cloud 中使用 Kubernetes
Earned Dec 29, 2025 EST
Getting Started with Terraform for Google Cloud
Earned Dec 29, 2025 EST
Hybrid Cloud Service Mesh with Anthos
Earned Dec 27, 2025 EST
可靠的 Google Cloud 基础设施: 设计和流程
Earned Dec 25, 2025 EST
生成式 AI：不只是聊天机器人
Earned Oct 6, 2025 EDT
Developing a Google SRE Culture
Earned Sep 24, 2025 EDT
适用于生成式 AI 的机器学习运维 (MLOps)
Earned Sep 11, 2025 EDT
负责任的 AI 简介
Earned Sep 4, 2025 EDT
大型语言模型简介
Earned Sep 4, 2025 EDT
Deutsche Bank: Prompt Engineering Fundamentals
Earned Sep 3, 2025 EDT
DEPRECATED Cloud Architecture
Earned Mar 17, 2023 EDT
在 Google Cloud 上使用 Terraform 构建基础设施
Earned Jan 19, 2023 EST
在 Google Cloud 上部署 Kubernetes 应用
Earned Jan 12, 2023 EST
开发 Google Cloud 网络
Earned Dec 30, 2022 EST
Using the Cloud SDK Command Line
Earned Dec 29, 2022 EST
为 Compute Engine 实现云负载均衡
Earned Dec 27, 2022 EST
在 Google Cloud 上实施云安全基础措施
Earned Dec 15, 2022 EST
构建安全的 Google Cloud 网络
Earned Dec 12, 2022 EST
在 Google Cloud 上设置应用开发环境
Earned Nov 3, 2022 EDT
Google Cloud 基础知识
Earned Nov 2, 2022 EDT