用 Database Migration Service 将 MySQL 数据迁移至 Cloud SQL
Earned Apr 22, 2024 EDT
Managing Change when Moving to Google Cloud
Earned Apr 18, 2024 EDT
Oracle to Cloud Spanner
Earned Apr 18, 2024 EDT
Migrate MySQL Databases to Cloud SQL
Earned Apr 17, 2024 EDT
Microsoft SQL Server to Cloud SQL
Earned Apr 17, 2024 EDT
PostgreSQL to Cloud SQL
Earned Apr 17, 2024 EDT
MySQL to Cloud SQL
Earned Apr 17, 2024 EDT
Modernizing Mainframe Applications with Google Cloud
Earned Apr 13, 2024 EDT
Building Resilient Streaming Systems on Google Cloud Platform
Earned Mar 22, 2024 EDT
Build Batch Data Pipelines on Google Cloud
Earned Mar 21, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Mar 4, 2024 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Feb 26, 2024 EST
Preparing for your Professional Data Engineer Journey
Earned Jan 18, 2024 EST
在 Google Cloud 上部署 Kubernetes 应用
Earned Feb 14, 2023 EST
Google Kubernetes Engine 使用入门
Earned Jul 3, 2022 EDT
可靠的 Google Cloud 基础设施: 设计和流程
Earned Jul 3, 2022 EDT
在 Google Cloud 中使用 Kubernetes
Earned Jul 3, 2022 EDT
Google Cloud 弹性基础设施：扩缩和自动化
Earned Jul 3, 2022 EDT
Migrating to Google Cloud
Earned Jul 3, 2022 EDT
Google Cloud 重要基础设施：核心服务
Earned Jul 3, 2022 EDT
Google Cloud 重要基础设施：基础
Earned Jul 2, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Jun 29, 2022 EDT
设置 Google Cloud 网络
Earned May 18, 2022 EDT
DEPRECATED Cloud Architecture
Earned May 18, 2022 EDT
在 Google Cloud 上使用 Terraform 构建基础设施
Earned May 18, 2022 EDT
开发 Google Cloud 网络
Earned May 17, 2022 EDT
云工程
Earned May 16, 2022 EDT
在 Google Cloud 上设置应用开发环境
Earned May 13, 2022 EDT
基准：基础架构
Earned May 13, 2022 EDT
为 Compute Engine 实现云负载均衡
Earned May 3, 2022 EDT
Google Cloud 基础知识
Earned May 3, 2022 EDT
Google Cloud 基础知识：核心基础设施
Earned Apr 3, 2022 EDT
In this challenge lab, you will demonstrate your ability to author agents using Agent Development Kit (ADK), deploy those agents to Agent Engine, and use them from a web app. Complete the challenge lab to earn a Google Cloud skill badge.
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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts.
A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
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In this skill bagde, you will demonstrate your ability to use and compare models available in the Vertex AI Model Garden. You'll deploy a model to a Vertex AI Endpoint, query other models via their API, and use Vertex AI's Gen AI evaluation service to measure the performance of multiple models.
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With this course you will learn how to use different techniques to fine-tune Gemini. Model tuning is an effective way to customize large models like Gemini for your specific tasks. It's a key step to improve the model's quality and efficiency.
This course will give an overview of model tuning, describe the tuning options available for Gemini, help you determine when each tuning option should be used and how to perform tuning.
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本课程能让机器学习从业者掌握评估生成式和预测式 AI 模型的基本工具、方法和最佳实践。要确保机器学习系统在实际运用中提供可靠、准确、高效的结果，做好模型评估至关重要。
学员将深入了解各项评估指标、方法及如何在不同模型类型和任务中适当应用这些指标和方法。课程将着重介绍生成式 AI 模型带来的独特挑战，并提供有效解决这些挑战的策略。通过利用 Google Cloud 的 Vertex AI Platform，学员可学习如何在模型选择、优化和持续监控工作中实施卓有成效的评估流程。
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This course delves into the complexities of assessing the quality of large language model outputs. It examines the challenges enterprises face due to the subjective and sometimes incorrect nature of LLM responses, including hallucinations and inconsistent results. The course introduces various evaluation metrics for different tasks like classification, text generation, and question answering, such as Accuracy, Precision, Recall, F1 score, ROUGE, BLEU, and Exact Match. It also explores evaluation methods offered by Vertex AI LLM Evaluation Services, including computation-based, autorater, and human evaluation, providing insights into their application and benefits. Finally, the module covers how to unit test LLM applications within Vertex AI.
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Model Garden is a model library that helps you discover, test, and deploy models from Google and Google partners. Learn how to explore the available models and select the right ones for your use case. And how to deploy and interact with Model Garden models through the Google Cloud console and APIs.
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This Security quest consists of a series of advanced-level labs designed to validate your proficiency in enterprise security. Each lab presents a set of the required tasks that you must complete with minimal assistance.
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This Data Analytics course consists of a series of advanced-level labs designed to validate your proficiency in using Google Cloud services. Each lab presents a set of the required tasks that you must complete with minimal assistance.
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This Networking course consists of a series of advanced-level labs designed to validate your proficiency in managing a customer's network using Google Cloud services. Each lab presents a set of the required tasks that you must complete with minimal assistance.
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Actifio GO for Google Cloud is a SaaS offering which enables powerful enterprise class backup and recovery for Google Cloud resident and on-premises workloads. Actifio now supports backup, disaster recovery and rapid database cloning of Oracle on Bare Metal Solution on Google Cloud besides other enterprise workloads including SAP HANA, SQL Server, and others. This course provides a deep dive into at the preparation and deployment of the Actifio GO solution and its constituent components. Each module contains demos and explanations of each component. The Actifio GO training was originally designed for and only made available to Google Teams, however we’ve recognized how beneficial it would be for our Partners and are now offering our Partners exclusive access to the Actifio training and products, so they can benefit from the demos and best practices and bring them to their Google Cloud Customers.
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“生成式 AI 智能体：助力组织转型”是“Gen AI Leader”学习路线中的第五门课程，也是最后一门课程。本课程探讨了组织如何使用量身定制的生成式 AI 智能体，帮助应对特定的业务挑战。您将亲自动手构建一个基本的生成式 AI 智能体，并探索这些智能体的组成部分，例如模型、推理循环以及各种工具。
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This Databases course consists of a series of advanced-level labs designed to validate your proficiency in migrating and managing Google Cloud databases. Each lab presents a set of the required tasks that you must complete with minimal assistance.
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"This Application Modernization course consists of a series of advanced-level labs designed to validate your proficiency in modernizing a customer's legacy software using Google Cloud. Each lab presents a set of the required tasks that you must complete with minimal assistance."
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“生成式 AI 应用：改变工作方式”是 Generative AI Leader 学习路线的第四门课程。本课程介绍 Google 的生成式 AI 应用，例如 Gemini for Workspace 和 NotebookLM。它将引导您逐一了解接地、检索增强生成、构建有效提示和构建自动化工作流等概念。
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There's much excitement about cloud technology and digital transformation, but often many unanswered questions.
For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin?
If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.
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“生成式 AI: 全面了解生成式 AI”是 Generative AI Leader 学习路线中的第三门课程。生成式 AI 正在改变我们的工作方式,以及我们与周围世界的互动方式。作为领导者,应该如何利用生成式 AI 来推动实现实际的业务成果?在本课程中,您将探索构建生成式 AI 解决方案的不同层级、Google Cloud 的产品,以及选择解决方案时需要考虑的因素。
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This course is designed to enhance your demonstration skills and help you deliver impactful presentations.
Course activities use an external tool (Yoodli). Refer to Yoodli's Terms of Service and Privacy Notice.
Note: The Yoodli Labs in this course will be deprecated on March 31st. We encourage you to finish your remaining Yoodli Labs before the March 31 deadline.
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This Artificial Intelligence and Machine Learning course consists of a series of advanced-level labs designed to validate your proficiency in using AI and ML to extract, analyze, search, and store structured data from documents and improve customer service. Each lab presents a set of required tasks that you must complete with minimal assistance.
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The course aims to train Google technical sales partners on the business value discovery process using proprietary content.
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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google…
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with migrating from an Enterprise Data Warehouse (EDW) to BigQuery using the DMT tool and sample data. Learners will complete a lab that uses the DMT tool to transfer schema and data from Teradata to BigQuery.
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“生成式 AI: 剖析基本概念”是 Generative AI Leader 学习路线中的第二门课程。在本课程中,您将了解生成式 AI 的基本概念。您要探索 AI、机器学习和生成式 AI 之间的区别,了解各种数据类型如何赋能生成式 AI,从而应对各种业务挑战。您还将深入了解 Google Cloud 应对基础模型局限性的策略,以及负责任和安全的 AI 开发与部署面临着哪些关键挑战。
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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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这一简短的课程将介绍如何在 Google Cloud 上将应用与 Gemini 1.0 Pro 模型集成，可帮助您探索 Gemini API 及其生成式 AI 模型。此课程会教您如何通过代码访问 Gemini 1.0 Pro 和 Gemini 1.0 Pro Vision 模型。课程会安排您在应用中使用文本、图片和视频提示来测试这些模型的功能。
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本课程专为各个级别的开发者打造，您将学到 Gemini Code Assist 的核心特性和功能。Gemini Code Assist 依托 AI 技术，可协助您在 Google Cloud 上进行应用开发。从智能代码建议、自动补全、实时错误检测到重构辅助，您将发现 Gemini Code Assist 如何显著提升开发效率和代码质量，帮助您节省宝贵时间，专注于更具价值和趣味性的任务。
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In this course, you learn about Cloud Run functions, Google's serverless, fully-managed functions as a service (FaaS) product that lets you implement single-purpose function code that reponds to HTTP requests and events from your cloud infrastructure.
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This course introduces you to event-based applications and teaches you how to use service orchestration and choreography to coordinate microservices. Using lectures and hands-on labs, you learn how to use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to build microservices applications on Google Cloud.
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In this course, you learn the fundamentals of application development on Google Cloud. You learn best practices for cloud applications, and how to select compute and data options to match your application use cases. You're introduced to generative AI and how it's used to help build applications. You learn about authentication and authorization, application deployment, continuous integration and delivery, and monitoring and performance tuning for your applications running in Google Cloud. Using lectures and hands-on labs, you learn how to get started building and running applications on Google Cloud.
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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email.
A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!"
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An LLM-based application can process language in a way that resembles thought. But if you want to extend its capabilities to take actions by running other functions you have coded, you will need to use function calling. This can also be referred to as tool use. Additionally, you can give a model the ability to search Google or search a data store of documents to ground its responses. In other words, to base its answers on that information. In this course, you’ll explore these concepts.
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This Course is utilized to certify completion of The Skills Challenge at Next 2025.
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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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This course provides hands-on experience with Google Cloud's Search for Retail, focusing on practical skills in setting up and managing retail search functionalities using APIs and console configurations. Participants will engage with real-world scenarios to learn how to import product data, manage user events, configure search parameters, and optimize search results within a retail environment.
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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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This skill badge course aims to unlock the power of data visualization and business intelligence reporting with Looker, and gain hands-on experience through labs.
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Learn to build generative AI applications leveraging Firebase Genkit to call LLMs on Google Cloud and elsewhere, simplify complex applications' code and deploy your solution on Google Cloud.
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This skill badge aims to provide partners an introduction to BigQuery Data Transfer Service and Migration Service, two powerful tools for managing and migrating data in the cloud. Learners will learn how to leverage these tools to efficiently migrate and manage data, and gain hands-on experience through labs.
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This skill badge aims to evaluate a partner's ability to migrate PostgreSQL databases to AlloyDB. Learners will gain hands-on experience through labs and achieve comprehensive knowledge and practical skills for migrating PostgreSQL databases to AlloyDB.
This skill badge aims to evaluate a partner's ability to utilize BigQuery's features and capabilities to manage and analyze large datasets. Learners will gain hands-on experience through labs and achieve solid understanding of BigQuery's foundational concepts and features.
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完成借助 Firebase 开发无服务器应用技能徽章中级课程， 展示您在以下方面的技能：借助 Firebase 设计无服务器 Web 应用架构以及构建无服务器 Web 应用； 利用 Firestore 管理数据库；利用 Cloud Build 自动完成部署流程； 以及将 Google 助理功能集成到您的应用中。
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This skill badge aims to provide partners a comprehensive understanding of migrating PostgreSQL databases to Cloud SQL for PostgreSQL using the Database Migration Service, and gain hands-on experience through labs.
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This skill badge aims to provide partners a comprehensive understanding of migrating MySQL databases to Cloud Spanner, and gain hands-on experience through labs.
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This skill badge aims to provide partners a comprehensive understanding of migrating Microsoft SQL Server databases to Cloud SQL for SQL Server, and gain hands-on experience through labs.
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完成构建安全的 Google Cloud 网络课程，赢取技能徽章。在此课程中，您将了解与网络有关的众多 资源，以便在 Google Cloud 上构建、扩缩和保护自己的应用。
完成在 Google Cloud 上构建网站技能徽章课程，赢取入门级技能徽章。本课程以 Get Cooking in Cloud 系列视频为基础， 涵盖以下主题：在 Cloud Run 上部署网站在 Compute Engine 上托管 Web 应用在 Google Kubernetes Engine 上创建、部署和扩缩网站使用 Cloud Build 从单体式应用迁移到微服务架构
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完成在 Google Cloud 上实施云安全基础措施技能徽章中级课程， 展示自己在以下方面的技能：使用 Identity and Access Management (IAM) 创建和分配角色； 创建和管理服务账号；跨虚拟私有云 (VPC) 网络实现专用连接； 使用 Identity-Aware Proxy 限制应用访问权限； 使用 Cloud Key Management Service (KMS) 管理密钥和加密数据；创建专用 Kubernetes 集群。
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完成在 Cloud Run 上开发无服务器应用技能徽章中级课程， 展示您在以下方面的技能：集成 Cloud Run 与 Cloud Storage 以管理数据， 使用 Cloud Run 和 Pub/Sub 设计弹性异步系统架构， 构建依托 Cloud Run 技术的 REST API 网关，以及在 Cloud Run 上构建和部署服务。
完成在 Google Cloud 上实现 CI/CD 流水线技能徽章课程，赢取中级技能徽章。 您将学习如何使用 Artifact Registry、Cloud Build 和 Cloud Deploy。您将与 Google Cloud 控制台、Google Cloud CLI、Cloud Run 和 GKE 互动。本课程将介绍如何构建持续集成 流水线，存储和保护工件，扫描漏洞，证明已批准版本 的有效性。此外，您还将获得在 GKE 和 Cloud Run 中 部署应用的实操经验。
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Demonstrate your ability to implement updated prompt engineering techniques and utilize several of Gemini's key capacilities including multimodal understanding and function calling. Then integrate generative AI into a RAG application deployed to Cloud Run. This course contains labs that are to be used as a test environment. They are deployed to test your understanding as a learner with a limited scope. These technologies can be used with fewer limitations in a real world environment.
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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.
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本课程介绍 Vertex AI Studio，这是一种用于与生成式 AI 模型交互、围绕业务创意进行原型设计并在生产环境中落地的工具。通过沉浸式应用场景、富有吸引力的课程和实操实验，您将探索从提示到产品的整个生命周期，了解如何将 Vertex AI Studio 用于多模态 Gemini 应用、提示设计、提示工程和模型调优。本课程的目的在于帮助您利用 Vertex AI Studio，在自己的项目中充分发掘生成式 AI 的潜力。
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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随着企业对人工智能和机器学习的应用越来越广泛，以负责任的方式构建这些技术也变得更加重要。但对很多企业而言，真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI，本课程正适合您。
本课程将介绍 Google Cloud 目前如何践行 Responsible AI，以及从中总结的最佳实践和经验教训，便于您以此为框架构建自己的 Responsible AI 方法。
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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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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
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完成“创建和管理 Cloud SQL for PostgreSQL 实例”这一入门级的技能徽章课程，展示您在以下方面的技能： 迁移、配置和管理 Cloud SQL for PostgreSQL 实例及数据库。
Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.
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This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to Google Cloud while taking advantage of various services.
This course covers how to move on-premises, enterprise databases like SQL Server to Google Cloud (Compute Engine and Cloud SQL) and Oracle to Google Cloud bare metal.
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完成“创建和管理 Cloud SQL for PostgreSQL 实例”这一入门级的技能徽章课程，展示您在以下方面的技能： 迁移、配置和管理 Cloud SQL for PostgreSQL 实例及数据库。
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完成用 Database Migration Service 将 MySQL 数据迁移至 Cloud SQL 这一入门级的技能徽章课程，展示您在以下方面的技能： 使用 Database Migration Service 中提供的不同作业类型和连接选项，将 MySQL 数据迁移到 Cloud SQL； 以及在运行 Database Migration Service 作业时 迁移 MySQL 用户数据。
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Moving to the cloud creates numerous opportunities to start working in
a new way and it empowers the workforce to better collaborate and innovate. But
it’s also a big change. Sometimes the success of the change hinges not on the change
itself, but on how it’s managed.
This course will help people managers to understand
some of the key challenges associated with cloud adoption, and provide them with
a verified in-the-field framework that will assist them in supporting their teams
on the change journey. By addressing the human factor of moving to the cloud, organizations
increase their chances of realizing business objectives and investing in their future
talent.
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Migration from Oracle to Cloud Spanner using HarbourBridge. This course describes an example scenario that uses sample data during the migration. This process includes using HarbourBridge for Assessment, Schema Conversion, Schema Transformation, Data Migration, and supporting tools for data validation.
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This skill badge aims to provide partners an comprehensive understanding of migrating MySQL databases to Cloud SQL using the Database Migration Service, and gain hands-on experience through labs.
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This course aims to upskill Google Cloud partners to perform specific tasks of migrating data from Microsoft SQL Server to CloudSQL using the built-in replication capabilities of SQL Server.
Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data, and related processes to corresponding Google Cloud products.
One or more challenge labs will test the learner's understanding of the topics.
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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from PostgreSQL to CloudSQL using the Database Migration Service.
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Migration from MySQL to Cloud SQL using Database Migration Service that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.
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This course enables system integrators and partners to understand the principles of automated migrations, plan legacy system migrations to Google Cloud leveraging G4 Platform, and execute a trial code conversion.
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This 1-week, accelerated on-demand course builds upon Google Cloud Platform Big Data and Machine Learning Fundamentals. Through a combination of video lectures, demonstrations, and hands-on labs, you'll learn to build streaming data pipelines using Google cloud Pub/Sub and Dataflow to enable real-time decision making. You will also learn how to build dashboards to render tailored output for various stakeholder audiences.
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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
欢迎学习“Google Kubernetes Engine 使用入门”课程。Kubernetes 是位于应用和硬件基础架构之间的软件层，如果您对 Kubernetes 感兴趣，那就来对地方了！Google Kubernetes Engine 将 Kubernetes 作为 Google Cloud 上的代管式服务提供给您使用。
本课程的目标是介绍 Google Kubernetes Engine（通常称为 GKE）的基础知识，以及将应用容器化并在 Google Cloud 中运行的方法。本课程首先介绍 Google Cloud 的基础知识，然后概述容器、Kubernetes、Kubernetes 架构以及 Kubernetes 操作。
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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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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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这是一套自助式速成课程，向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务。学员将通过一系列视频讲座、演示和实操实验，探索和部署各种解决方案元素，包括安全互连网络、负载均衡、自动扩缩、基础架构自动化和代管式服务。
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This course introduces participants to the strategies to migrate from a source environment to Google Cloud. Participants are introduced to Google Cloud's fundamental concepts and more in depth topics, like creating virtual machines, configuring networks and managing access and identities. The course then covers the installation and migration process of Migrate for Compute Engine, including special features like test clones and wave migrations.
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这门自助式速成课程向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务，着重介绍了 Compute Engine。学员将通过一系列视频讲座、演示和动手实验，探索和部署各种解决方案元素，包括网络、系统和应用服务等基础架构组件。本课程的内容还包括如何部署实用的解决方案，包括客户提供的加密密钥、安全和访问权限管理、配额和结算，以及资源监控。
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这门自助式速成课程向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务，其中着重介绍了 Compute Engine。学员将通过一系列视频讲座、演示和动手实验，探索和部署各种解决方案元素，包括网络、虚拟机和应用服务等基础架构组件。您将学习如何通过控制台和 Cloud Shell 使用 Google Cloud。您还将了解云架构师角色、基础架构设计方法以及虚拟网络配置和虚拟私有云 (VPC)、项目、网络、子网、IP 地址、路由及防火墙规则。
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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
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完成设置 Google Cloud 网络课程，赢取技能徽章， 您将了解如何在 Google Cloud Platform 上执行基本的网络组建和管理任务 - 创建自定义网络、添加子网防火墙规则，然后创建虚拟机并测试 虚拟机之间相互通信时的延迟时间。
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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。
Deploy an Agent with Agent Development Kit (ADK)
Earned Jan 23, 2026 EST
Edit images with Imagen
Earned Jan 17, 2026 EST
Deploy and Evaluate Model Garden Models
Earned Jan 15, 2026 EST
Supervised Fine-tuning for Gemini
Earned Jan 14, 2026 EST
利用 Vertex AI 实现机器学习运维 (MLOps)：模型评估
Earned Jan 6, 2026 EST
Model evaluation on Vertex AI
Earned Jan 2, 2026 EST
Find, Explore and Deploy Model Garden Models
Earned Dec 17, 2025 EST
Implement Google Cloud Security Solutions
Earned Dec 16, 2025 EST
Build Data Analytics Solutions on Google Cloud
Earned Dec 15, 2025 EST
Implement Cloud Networking Solutions
Earned Dec 11, 2025 EST
Inside Track: Install, Deploy and Configure Actifio GO Solutions
Earned Dec 10, 2025 EST
生成式 AI 智能体：助力组织转型
Earned Dec 8, 2025 EST
Optimize Database Workloads on Google Cloud
Earned Dec 5, 2025 EST
Migrate and Modernize Applications with Google Cloud
Earned Dec 1, 2025 EST
生成式 AI 应用：改变工作方式
Earned Nov 26, 2025 EST
Digital Transformation with Google Cloud
Earned Nov 26, 2025 EST
生成式 AI: 全面了解生成式 AI
Earned Nov 23, 2025 EST
Deliver Effective Product Demos
Earned Nov 20, 2025 EST
Build AI/ML Models on Google Cloud
Earned Nov 20, 2025 EST
Discover Business Value for Customers
Earned Nov 19, 2025 EST
Google Cloud Run Serverless Workshop
Earned Oct 22, 2025 EDT
Data Migration Tool
Earned Sep 5, 2025 EDT
生成式 AI：剖析基本概念
Earned Aug 22, 2025 EDT
生成式 AI：不只是聊天机器人
Earned Aug 22, 2025 EDT
在 Google Cloud 上将应用与 Gemini 1.0 Pro 集成
Earned Aug 21, 2025 EDT
借助 Gemini Code Assist 简化应用开发
Earned Aug 21, 2025 EDT
Developing Applications with Cloud Run Functions on Google Cloud
Earned Aug 13, 2025 EDT
Service Orchestration and Choreography on Google Cloud
Earned Aug 6, 2025 EDT
Developing Applications with Google Cloud: Foundations
Earned Jul 30, 2025 EDT
Extend Gemini with controlled generation and Tool use
Earned Jul 28, 2025 EDT
Empower Gen AI Apps with Tool Use
Earned Jul 28, 2025 EDT
[DEPRECATED] The Skills Challenge at Next 2025
Earned Apr 14, 2025 EDT
Developing a Google SRE Culture
Earned Dec 19, 2024 EST
Exploring Vertex AI Search for Retail
Earned Dec 11, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned Dec 11, 2024 EST
Visualize Your Data in Looker
Earned Dec 11, 2024 EST
Integrate Generative AI Into Your Apps with Firebase Genkit
Earned Dec 4, 2024 EST
Automate Data Migrations to BigQuery
Earned Dec 4, 2024 EST
Migrate PostgreSQL to AlloyDB
Earned Dec 4, 2024 EST
使用 Google Cloud Observability 进行监控和记录
Earned Nov 13, 2024 EST
Monitor and Manage Data in BigQuery
Earned Nov 11, 2024 EST
借助 Firebase 开发无服务器应用
Earned Nov 11, 2024 EST
Migrate PostgreSQL to Cloud SQL
Earned Nov 11, 2024 EST
Migrate MySQL to Cloud Spanner
Earned Nov 11, 2024 EST
Migrate Microsoft SQL Server to Cloud SQL
Earned Nov 11, 2024 EST
构建安全的 Google Cloud 网络
Earned Nov 10, 2024 EST
用 Chrome 企业进阶版安全功能保护云中的数据流量
Earned Nov 9, 2024 EST
在 Google Cloud 上构建网站
Earned Nov 7, 2024 EST
在 Google Cloud 上实施云安全基础措施
Earned Nov 5, 2024 EST
在 Cloud Run 上开发无服务器应用
Earned Nov 3, 2024 EST
在 Google Cloud 中实施 DevOps 工作流
Earned Nov 3, 2024 EST
在 Google Cloud 上实现 CI/CD 流水线
Earned Nov 1, 2024 EDT
Build and Deploy a Generative AI solution using a RAG framework
Earned Oct 2, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Sep 25, 2024 EDT
Vertex AI Studio 简介
Earned Sep 5, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned Sep 4, 2024 EDT
Text Prompt Engineering Techniques
Earned Sep 4, 2024 EDT
Generative AI Fundamentals
Earned Aug 30, 2024 EDT
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Aug 29, 2024 EDT
负责任的 AI 简介
Earned Aug 29, 2024 EDT
Generative AI for Business Leaders
Earned Aug 28, 2024 EDT
创建和管理 Cloud SQL for PostgreSQL 实例
Earned May 4, 2024 EDT
创建和管理 AlloyDB 实例
Earned May 4, 2024 EDT
创建和管理 Bigtable 实例
Earned May 4, 2024 EDT
创建和管理 Cloud Spanner 实例
Earned May 2, 2024 EDT
Cloud SQL
Earned May 2, 2024 EDT
Enterprise Database Migration
Earned May 2, 2024 EDT
创建和管理 Cloud SQL for PostgreSQL 实例
Earned Apr 25, 2024 EDT
用 Database Migration Service 将 MySQL 数据迁移至 Cloud SQL
Earned Apr 22, 2024 EDT
Managing Change when Moving to Google Cloud
Earned Apr 18, 2024 EDT
Oracle to Cloud Spanner
Earned Apr 18, 2024 EDT
Migrate MySQL Databases to Cloud SQL
Earned Apr 17, 2024 EDT
Microsoft SQL Server to Cloud SQL
Earned Apr 17, 2024 EDT
PostgreSQL to Cloud SQL
Earned Apr 17, 2024 EDT
MySQL to Cloud SQL
Earned Apr 17, 2024 EDT
Modernizing Mainframe Applications with Google Cloud
Earned Apr 13, 2024 EDT
Building Resilient Streaming Systems on Google Cloud Platform
Earned Mar 22, 2024 EDT
Build Batch Data Pipelines on Google Cloud
Earned Mar 21, 2024 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Mar 4, 2024 EST
Google Cloud Big Data and Machine Learning Fundamentals
Earned Feb 26, 2024 EST
Preparing for your Professional Data Engineer Journey
Earned Jan 18, 2024 EST
在 Google Cloud 上部署 Kubernetes 应用
Earned Feb 14, 2023 EST
Google Kubernetes Engine 使用入门
Earned Jul 3, 2022 EDT
可靠的 Google Cloud 基础设施: 设计和流程
Earned Jul 3, 2022 EDT
在 Google Cloud 中使用 Kubernetes
Earned Jul 3, 2022 EDT
Google Cloud 弹性基础设施：扩缩和自动化
Earned Jul 3, 2022 EDT
Migrating to Google Cloud
Earned Jul 3, 2022 EDT
Google Cloud 重要基础设施：核心服务
Earned Jul 3, 2022 EDT
Google Cloud 重要基础设施：基础
Earned Jul 2, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned Jun 29, 2022 EDT
设置 Google Cloud 网络
Earned May 18, 2022 EDT
DEPRECATED Cloud Architecture
Earned May 18, 2022 EDT
在 Google Cloud 上使用 Terraform 构建基础设施
Earned May 18, 2022 EDT
开发 Google Cloud 网络
Earned May 17, 2022 EDT
云工程
Earned May 16, 2022 EDT
在 Google Cloud 上设置应用开发环境
Earned May 13, 2022 EDT
基准：基础架构
Earned May 13, 2022 EDT
为 Compute Engine 实现云负载均衡
Earned May 3, 2022 EDT
Google Cloud 基础知识
Earned May 3, 2022 EDT
Google Cloud 基础知识：核心基础设施
Earned Apr 3, 2022 EDT