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Nilay Saraf

成为会员时间：2021

白银联赛

72920 积分
使用 Agent Platform 探索生成式 AI Earned May 6, 2025 EDT
使用 Gemini 和 Streamlit 开发生成式 AI 应用 Earned May 5, 2025 EDT
使用多模态 Gemini 和多模态 RAG 检查富文档 Earned May 5, 2025 EDT
使用 Gemini 和 Imagen 构建实用 AI 应用 Earned Apr 18, 2025 EDT
在 Agent Platform 中设计提示 Earned Apr 17, 2025 EDT
监控和管理 Google Cloud 资源 Earned Sep 5, 2023 EDT
Qwiklabs Trivia August 2023 Earned Aug 22, 2023 EDT
Automate Interactions with Contact Center AI Earned Aug 17, 2023 EDT
使用 Eventarc 构建事件驱动型应用 Earned Aug 17, 2023 EDT
在 Google Cloud 上存储、处理和管理数据 - 控制台 Earned Aug 15, 2023 EDT
通过 API 使用 Cloud Storage Earned Aug 12, 2023 EDT
为 Looker 信息中心和报告准备数据 Earned Aug 12, 2023 EDT
使用 Cloud Run Functions 构建无服务器应用 Earned Aug 11, 2023 EDT
用 Document AI 实现大规模自动数据采集 Earned Aug 11, 2023 EDT
使用 Google Cloud Speech API Earned Aug 10, 2023 EDT
用 AppSheet 来构建应用 Earned Aug 10, 2023 EDT
在关联工作表中分析 BigQuery 数据 Earned Aug 10, 2023 EDT
使用 Natural Language API 分析情感 Earned Aug 10, 2023 EDT
Level 3: GenAI Earned Aug 9, 2023 EDT
使用 Google API 分析语音和语言 Earned Aug 9, 2023 EDT
在 Google Cloud　上使用 Machine Learning API Earned Aug 9, 2023 EDT
BigQuery 流式数据分析 Earned Aug 8, 2023 EDT
实现 Cloud Storage 和数据保护解决方案 Earned Aug 8, 2023 EDT
Level 2: Apps Script and Networks Earned Aug 8, 2023 EDT
使用预训练 API 实现语音和语言解决方案 Earned Aug 7, 2023 EDT
在 Google Cloud 上构建网站 Earned Aug 7, 2023 EDT
构建安全的 Google Cloud 网络 Earned Aug 7, 2023 EDT
利用 BigQuery ML 构建预测模型时的数据工程处理 Earned Aug 7, 2023 EDT
使用 Apps 脚本和 AppSheet 进行开发 Earned Aug 5, 2023 EDT
用 Apps 脚本整合 BigQuery 数据和 Google Workspace Earned Aug 5, 2023 EDT
为 Google Cloud 配置服务账号和 IAM 角色 Earned Aug 5, 2023 EDT
在 Google Cloud 上为机器学习 API 准备数据 Earned Aug 5, 2023 EDT
云架构：设计、实施和管理 Earned Aug 5, 2023 EDT
Level 1: BigQuery ML, Cloud Architecture and Devops Skills Earned Aug 5, 2023 EDT
在 Google Cloud 中实施 DevOps 工作流 Earned Aug 4, 2023 EDT
借助 Firebase 开发无服务器应用 Earned Aug 4, 2023 EDT
通过 BigQuery ML 创建机器学习模型 Earned Aug 3, 2023 EDT
在 Google Cloud 上实施云安全基础措施 Earned Aug 3, 2023 EDT
Qwiklabs Trivia July 2023 Earned Jul 25, 2023 EDT
从 BigQuery 数据中挖掘数据洞见 Earned Jul 19, 2023 EDT
保护 Lakehouse 数据 Earned Jul 18, 2023 EDT
Level 2: Data Deep Dive Earned Jul 18, 2023 EDT
增强 Lakehouse 数据的元数据管理与数据发现能力 Earned Jul 17, 2023 EDT
在 Google Cloud 中实施 Sensitive Data Protection Earned Jul 16, 2023 EDT
用 Cloud Vision API 分析图片 Earned Jul 15, 2023 EDT
设置 Google Cloud 网络 Earned Jul 15, 2023 EDT
在 Google App Engine 上部署和管理应用 Earned Jul 12, 2023 EDT
Level 1: AppDev and Infrastructure Earned Jul 12, 2023 EDT
Google Cloud 云计算基础知识 Earned Jul 12, 2023 EDT
DEPRECATED Networking Fundamentals on Google Cloud Earned Jul 12, 2023 EDT
Machine Learning Operations (MLOps): Getting Started Earned Jul 11, 2023 EDT
Getting Started with Go on Google Cloud Earned Jul 11, 2023 EDT
Build a Certification Study Guide: PCA Exam Prep Earned Jan 16, 2023 EST
可靠的 Google Cloud 基础设施: 设计和流程 Earned Jan 16, 2023 EST
Manage Security in Google Cloud Earned Jan 9, 2023 EST
Application Development with Cloud Run Earned Jan 5, 2023 EST
App Deployment, Debugging, and Performance Earned Jan 5, 2023 EST
Networking in Google Cloud: Fundamentals Earned Jan 4, 2023 EST
Networking in Google Cloud: Routing and Addressing Earned Dec 30, 2022 EST
Build a Certification Study Guide: PCNE Exam Prep Earned Dec 30, 2022 EST
使用 Google Cloud Operations 进行扩缩 Earned Dec 28, 2022 EST
使用 Google Cloud 进行基础设施和应用的现代化改造 Earned Dec 28, 2022 EST
使用 Google Cloud 探索数据转换 Earned Dec 28, 2022 EST
利用 Google Cloud 实现数字化转型 Earned Dec 28, 2022 EST
Google Cloud Fundamentals for AWS Professionals Earned Dec 27, 2022 EST
Anthos on Bare Metal Earned Dec 25, 2022 EST
DEPRECATED Cloud Operations and Service Mesh with Anthos Earned Dec 25, 2022 EST
Multi-Cluster, Multi-Cloud with Anthos Earned Dec 25, 2022 EST
Hybrid Cloud Modernizing Applications with Anthos Earned Dec 25, 2022 EST
Hybrid Cloud Service Mesh with Anthos Earned Dec 25, 2022 EST
Hybrid Cloud Multi-Cluster with Anthos Earned Dec 25, 2022 EST
Architecting with Google Kubernetes Engine: Production Earned Dec 25, 2022 EST
Architecting with Google Kubernetes Engine: Workloads Earned Dec 22, 2022 EST
Hybrid Cloud Infrastructure Foundations with Anthos Earned Dec 20, 2022 EST
Architecting with Google Kubernetes Engine: Foundations - 简体中文 Earned Dec 20, 2022 EST
Building No-Code Apps with AppSheet: Automation Earned Dec 20, 2022 EST
Building No-Code Apps with AppSheet: Implementation Earned Dec 20, 2022 EST
Building No-Code Apps with AppSheet: Foundations Earned Dec 18, 2022 EST
Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI Earned Dec 17, 2022 EST
Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性 Earned Dec 16, 2022 EST
Google Cloud 云计算基础课程：Google Cloud 中的基础设施 Earned Dec 16, 2022 EST
Google Cloud 云计算基础课程：云计算基础知识 Earned Dec 16, 2022 EST
Recommendation Systems on Google Cloud Earned Dec 15, 2022 EST
Natural Language Processing on Google Cloud Earned Dec 15, 2022 EST
Computer Vision Fundamentals with Google Cloud Earned Dec 14, 2022 EST
Production Machine Learning Systems Earned Dec 13, 2022 EST
Launching into Machine Learning Earned Dec 13, 2022 EST
[Depricated] Build, Train and Deploy ML Models with Keras on Google Cloud Earned Dec 12, 2022 EST
[DEPRECATED] Feature Engineering Earned Dec 11, 2022 EST
How Google Does Machine Learning Earned Dec 10, 2022 EST
Machine Learning in the Enterprise Earned Dec 10, 2022 EST
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Dec 9, 2022 EST
在 Google Cloud 上使用 Terraform 构建基础设施 Earned Dec 8, 2022 EST
开发 Google Cloud 网络 Earned Dec 7, 2022 EST
在 Google Cloud 上设置应用开发环境 Earned Dec 5, 2022 EST
为 Compute Engine 实现云负载均衡 Earned Dec 4, 2022 EST
Logging and Monitoring in Google Cloud Earned Dec 4, 2022 EST
Google Kubernetes Engine 使用入门 Earned Dec 2, 2022 EST
Getting Started with Terraform for Google Cloud Earned Nov 30, 2022 EST
Google Cloud 弹性基础设施：扩缩和自动化 Earned Nov 30, 2022 EST
Google Cloud 重要基础设施：基础 Earned Nov 28, 2022 EST
Google Cloud 重要基础设施：核心服务 Earned Nov 28, 2022 EST
Google Cloud 基础知识：核心基础设施 Earned Nov 21, 2022 EST
Build a Certification Study Guide: ACE Exam Prep Earned Nov 17, 2022 EST

完成中级技能徽章课程使用 Agent Platform 探索生成式 AI，展示自己在以下方面的技能： 文本生成技能、用于增强内容创作能力的图像和视频分析技能，以及在 Gemini API 中应用函数调用技术的技能。 了解如何运用先进的 Gemini 技术、探索多模态内容生成方法，并扩展 AI 赋能项目的功能。

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完成中级技能徽章课程“使用 Gemini 和 Streamlit 开发生成式 AI 应用”，展示您在以下方面的技能： 文本生成、通过 Python SDK 和 Gemini API 应用函数调用，以及通过 Cloud Run 部署 Streamlit 应用。 您将了解如何以不同方式通过提示来让 Gemini 生成文本、使用 Cloud Shell 进行测试，以及如何迭代 Streamlit 应用，随后将其封装成 Docker 容器并部署在 Cloud Run 中。

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完成中级技能徽章课程使用多模态 Gemini 和多模态 RAG 检查富文档，展示您在以下方面的技能： 将多模态与 Gemini 配合使用，从而使用多模态提示从文本数据和视觉数据中提取信息、生成视频说明、 检索视频中不包含的额外信息； 将多模态检索增强生成 (RAG) 与 Gemini 配合使用，以构建包含文本和图片的文档的元数据、获取所有相关文本块并输出引用。

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完成“使用 Gemini 和 Imagen 构建实际 AI 应用”技能徽章入门课程，展示您在以下方面的技能：图像识别、自然语言处理、 使用 Google 强大的 Gemini 和 Imagen 模型生成图像、在 Vertex AI 平台上部署应用。

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完成 在 Agent Platform 中设计提示入门技能徽章课程，展示以下方面的技能： Agent Platform 中的提示工程、图片分析和多模态生成式技术。探索如何编写有效的提示，指导生成式 AI 输出， 以及将 Gemini 模型应用于真实的营销场景。

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完成监控和管理 Google Cloud 资源这一入门级技能徽章课程，展示您在以下方面的技能：授予和撤消 IAM 权限； 安装 Monitoring 代理和 Logging 代理；创建、部署和测试事件驱动型 Cloud Run 函数。

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Welcome to Qwiklabs Trivia for August! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the August badge.

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Earn a skill badge by completing the Automate Interactions with Contact Center AI quest, where you will learn about the features of Contact Center AI, including how to Build a virtual agent, Design conversation flows for your virtual agent; Add a phone gateway to your virtual agent; Use Dialogflow for troubleshooting; Review logs and debug your virtual agent. 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 skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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完成“使用 Eventarc 构建事件驱动型应用”课程，赢取技能徽章。 在这门课程中，您将使用 Eventarc 为不同资源创建事件触发器，包括 Pub/Sub 主题和 Cloud Storage 存储桶。

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Cloud Storage, Cloud Functions 和 Cloud Pub/Sub 都是 Google Cloud Platform 服务，可用于存储、处理和管理数据。这三项 服务可结合使用，创建各种数据驱动型应用。在 此技能徽章课程中，您将使用 Cloud Storage 存储图片，使用 Cloud Functions 函数 处理图片，并使用 Cloud Pub/Sub 将图片发送到另一个应用。

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完成通过 API 使用 Cloud Storage 这一入门级技能徽章课程，展示您在以下方面的技能： 使用 API 来处理 Cloud Storage 资源，包括 Cloud Storage API。

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完成为 Looker 信息中心和报告准备数据入门级技能徽章课程， 展现您在以下方面的技能：对数据进行过滤、排序和透视；将来自不同 Looker 探索的结果合并； 以及使用函数和运算符构建 Looker 信息中心和报告以用于数据分析和可视化。

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完成“使用 Cloud Run Functions 构建无服务器应用”课程，赢取“入门”技能徽章。您将学习如何通过 Google Cloud 控制台和命令行使用 Cloud Run Functions。 技能徽章通过动手实验和挑战赛形式的评估，检验您对特定产品的实际知识掌握情况。完成课程即可获得徽章， 也可直接参加实验室挑战赛，快速获得徽章。徽章可证明您掌握技能的熟练程度，提升您的专业形象，最终助您获得更多职业机会。欢迎访问您的个人资料，并跟踪您已获得的徽章。

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完成用 Document AI 实现大规模自动数据采集课程，赢取入门级技能徽章。在本课程中，您将学习如何使用 Document AI 提取、处理和采集数据。

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完成 使用 Google Cloud Speech API这一技能徽章课程，赢取技能徽章。在此课程中，您将学习如何创建 Speech-to-Text API 请求、 将音频语音转写成文字，以及转写语音。

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完成用 AppSheet 来构建应用课程，赢取技能徽章。 在此课程中，您将学习如何使用 AppSheet 构建、配置和发布应用。

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完成在关联工作表中分析 BigQuery 数据这一技能徽章课程，展示您能够使用关联工作表，在 Google 表格的电子表格中访问、分析、可视化并共享数十亿行 BigQuery 数据。

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完成使用 Natural Language API 分析情感挑战任务，赢取技能徽章 。在此过程中，您将学习如何使用 API 从文本中提取情感。

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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!

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完成使用 Google API 分析语音和语言课程，赢取技能徽章 。在此课程中，您将学习如何在真实场景中使用 Natural Language API 和 Speech API。

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完成在 Google Cloud　上使用 Machine Learning API 课程，赢取高级技能徽章。 在本课程中，您将了解以下机器学习和 AI 技术的基本功能： Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。

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完成 BigQuery 流式数据分析技能徽章课程，赢取技能徽章 。在这门课程中，您将结合使用 Pub/Sub、Dataflow 和 BigQuery 来实现流式 数据分析。

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完成 实现 Cloud Storage 和数据保护解决方案这一技能徽章课程，赢取技能 徽章。学习如何创建 Cloud Storage 存储桶，如何 使用 Cloud Storage 命令行，以及如何使用存储桶锁定来保护 存储桶中的对象。

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For organisations to thrive in the digital world, it is important for them to have secured networks to protect sensitive data, prevent cyber threats and maintain customer trust. Learn the principles of network design, security and management and integrating BigQuery Data and Google Workspace using Apps Script. Gain hands-on experience with labs carefully designed to nurture and assess your tech skills and set you on a course to earn your first Google Cloud credential.

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完成使用预训练 API 实现语音和语言解决方案课程以获得技能徽章，了解如何使用与语音相关的 API 工具来合成和转录语音。

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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。

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完成中级技能徽章课程利用 BigQuery ML 构建预测模型时的数据工程处理， 展示自己在以下方面的技能：利用 Dataprep by Trifacta 构建 BigQuery 数据转换流水线； 利用 Cloud Storage、Dataflow 和 BigQuery 构建提取、转换和加载 (ETL) 工作流； 以及利用 BigQuery ML 构建机器学习模型。

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完成使用 Apps 脚本和 AppSheet 进行开发技能徽章课程，赢取技能徽章。 在此课程中，您将学习如何构建聊天机器人，以及如何 在任何文档中使用脚本编辑器。

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完成用 Apps 脚本整合 BigQuery 数据和 Google Workspace 这一入门级技能徽章课程，展示通过 AppSheet 连接 Workspace 产品与 BigQuery 的技能。

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完成“为 Google Cloud 配置服务账号和 IAM 角色”课程，赢取入门级技能徽章。在本课程中，您将了解服务账号、自定义角色以及如何使用 gcloud 设置权限。

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完成入门级技能徽章课程在 Google Cloud 上为机器学习 API 准备数据，展示以下技能： 使用 Dataprep by Trifacta 清理数据、在 Dataflow 中运行数据流水线、在 Managed Service for Apache Spark 中创建集群和运行 Apache Spark 作业，以及调用机器学习 API，包括 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

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完成 云架构：设计、实施和管理课程，赢取技能徽章，展示您在以下方面的技能：使用 Apache Web 服务器部署可公开访问的网站；使用启动脚本配置 Compute Engine 虚拟机； 使用 Windows 堡垒主机和防火墙规则配置安全 RDP；构建 Docker 映像并将其部署到 Kubernetes 集群，然后进行更新；以及创建 CloudSQL 实例并导入 MySQL 数据库。 此技能徽章课程是非常有用的资源， 可帮助您理解 Google Cloud 认证 Professional Cloud Architect 认证考试中将会出现的主题。

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The world around us is changing and mastering future-driven technologies is the key to success. We want you to get started by learning a little of everything! Discover machine learning in data analysis, build scalable cloud solutions and accelerate software development that will shape the future. The possibilities in the Arcade are endless and all of those will lead you towards earning your first Google Cloud Credential. No prior experience required.

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完成在 Google Cloud 中实施 DevOps 工作流技能徽章中级课程， 展示您在以下方面的技能：创建和管理 git 代码库； 在 Google Kubernetes Engine (GKE) 上启动、管理和扩缩 Deployment； 设计 CI/CD 流水线架构，以自动构建容器映像并将其部署到 GKE。

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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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完成中级技能徽章课程通过 BigQuery ML 创建机器学习模型，展示您在以下方面的技能： 使用 BigQuery ML 创建和评估机器学习模型，以执行数据预测。

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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。

了解详情

Welcome to Qwiklabs Trivia for July! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the July badge.

了解详情

完成入门级技能徽章课程“从 BigQuery 数据中挖掘数据洞见”，展示您在以下方面的技能： 编写 SQL 查询、查询公共表、将示例数据加载到 BigQuery 中、 在 BigQuery 中使用查询验证器排查常见的语法错误，以及通过连接到 BigQuery 数据在 Data Studio 中 创建报告。

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完成保护 Lakehouse 数据这一入门级技能徽章课程，展示您在以下方面的技能：使用 IAM、BigQuery、Lakehouse 和 Knowledge Catalog 中的 Data Catalog 创建和保护 Lakehouse 表。

了解详情

The demand for data skills is growing rapidly, and we want you to get ahead! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. There are a lot of different aspects to any data role, so it's important to start with the basics - and we’ve got you covered. Learn how to tap into ML APIs, dive into your first data lake, and learn how the experts think about securing data. No experience required.

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完成增强 Lakehouse 数据的元数据管理与数据发现能力这一技能徽章课程，展示您在 BigQuery、 Lakehouse 和 Knowledge Catalog 方面的技能。您将创建 Lakehouse 表，并增强表数据的元数据管理与数据发现能力。

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完成 在 Google Cloud 中实施 Sensitive Data Protection 这一入门级技能徽章课程，展示您在以下方面的技能：使用 Sensitive Data Protection 服务 （包括 Cloud Data Loss Prevention API）来检查和隐去 Google Cloud 中的敏感数据，并对敏感数据进行去标识处理。

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完成用 Cloud Vision API 分析图片课程，赢取技能徽章。在此挑战任务中，您将了解如何利用 Cloud Vision API 执行各种任务，包括从图片中提取文本。

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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。

了解详情

完成在 Google App Engine 上部署和管理应用课程，赢取技能徽章。在此课程中，您将学习如何将 App Engine 与 Python、Go 和 PHP 搭配使用。

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Demand for cloud-skilled workers is rising. According to a report by Indeed, cloud computing jobs are expected to grow by 22% over the next five years, much faster than the average for all occupations. Play now to get hands-on experience building with Google Cloud's powerful coding and infrastructure management tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.

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完成Google Cloud 云计算基础知识挑战任务，赢取技能徽章。 您将学习如何在　Compute Engine　中使用虚拟机 (VM)、永久性 磁盘和 Web 服务器。

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Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers on Google Cloud. 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 this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

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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 started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.

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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Architect certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.

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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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This course provides foundational knowledge for securing your Google Cloud environment. You will learn Google Cloud's security model, including Zero Trust principles and the Shared Fate model. You will configure identity services like Cloud Identity and Workforce Identity Federation, manage access control using Identity and Access Management (IAM) roles, conditions, and policies, and implement network security controls such as VPCs, Cloud Firewall tiers, and VPC Service Controls to build a secure perimeter. As the foundation of the Security in Google Cloud learning path, this course establishes the core principles required for two subsequent specialized tracks: the five-course Security Best Practices in Google Cloud series and the four-course Mitigate Threats in Google Cloud series.

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This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to on Google Cloud using Cloud Run.design, implement, deploy, secure, manage, and scale applications

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to create repeatable deployments by treating infrastructure as code, choose the appropriate application execution environment for an application, and monitor application performance. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer.

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Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals.  This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharing of VPC networks. Additionally, the course covers network logging and monitoring techniques. 

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Welcome to the second course in the networking and Google Cloud series routing and addressing. In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities. Module one will lay the foundation by exploring network routing and addressing in Google Cloud, covering key building blocks such as routing IPv4, bringing your own IP addresses and setting up cloud DNS. In Module two will shift our focus to private connection options, exploring use cases and methods for accessing Google and other services privately using internal IP addresses. By the end of this course, you'll have a solid grasp of how to effectively route and address your network traffic within Google Cloud.

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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Network Engineer certification exam. You'll review Gemini Notebook features, add sources to your notebook, and learn how to personalize your Gemini Notebook experience to study for the exam.

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各种规模的组织都在利用云的强大功能和灵活性来改变运营方式。然而，有效管理和扩缩云资源可能是一项复杂的任务。本课程探讨了云中现代运营、可靠性和弹性方面的基本概念，以及 Google Cloud 如何帮助支持这些工作。 作为 Cloud Digital Leader 学习路线的一部分，本课程旨在帮助个人在自己的岗位上成长，并为企业谋求未来发展。

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许多传统企业都在使用无法满足现代客户期望的旧式系统和应用。业务领导者往往需要在维护老旧的 IT 系统和投资新产品与服务之间做出选择。本课程探讨了这些挑战，并提供了利用云技术克服这些挑战的解决方案。 作为 Cloud Digital Leader 学习路线的一部分，本课程旨在帮助个人在工作中成长，并为企业打造美好未来。

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云技术是一项强大的资产，与数据相结合后，它将成为创新和提升客户体验的催化剂。《使用 Google Cloud 探索数据转换》课程探讨了组织如何利用云技术让数据更易于访问、更具实用价值和商业价值。 作为“Cloud Digital Leader 学习路线”的一部分，本课程旨在帮助个人提升职业素养，并为企业谋求未来发展。

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数字化转型是现代组织的必经之路，而扎实掌握云计算基础知识，是推动实质性创新的第一步。《利用 Google Cloud 实现数字化转型》课程将讲解核心技术与战略框架，助力组织实现运营现代化。本课程介绍关于云的基本概念、全球网络基础设施和责任共担模式，帮助领导者从容推进上云进程。 作为 Cloud Digital Leader 学习路线的一部分，本课程旨在帮助学员提升岗位能力，从而为企业打造美好未来。

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Google Cloud Fundamentals for AWS Professionals introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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Course three of the Anthos series prepares students to run Anthos in a customer’s on-premises environment, on bare metal.Through presentations and hands-on labs, participants explore deploying and running Anthos applications on bare metal, creating the Anthos infrastructure, deploying applications, and performing monitoring, logging, and tracing. This course is a continuation of course two, Cloud Operations and Service Mesh with Anthos, and assumes direct experience with the topics covered in that course.

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Course two of the Architecting Hybrid Cloud with Anthos series prepares students to operate and observe Anthos environments. Through presentations and hands-on labs, participants explore adjusting existing clusters, setting up advanced traffic routing policies, securing communication across workloads, and observing clusters in Anthos. This course is a continuation of course one, Multi-Cluster, Multi-Cloud with Anthos, and assumes direct experience with the topics covered in that course.

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Course one of the Architecting Hybrid Cloud with Anthos series introduces participants to manage multi-cloud and hybrid Kubernetes deployments using Anthos. Through presentations and hands-on labs, participants explore planning and creating Anthos environments and building manageable and reliable multi-cluster Kubernetes infrastructure environments centered around Anthos and containers. This course is a continuation of Architecting with GKE and assumes direct experience with the technologies covered in that course.

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Course four of the Anthos series prepares students to consider multiple approaches for modernizing applications and services within Anthos environments. Topics include optimizing workloads on serverless platforms and migrating workloads to Anthos. This course is a continuation of course three, Anthos on Bare Metal, and assumes direct experience with the topics covered in that course.

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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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This on-demand course equips students to understand, configure, and maintain multi-cluster Kubernetes infrastructures using Anthos GKE, and Istio-based service mesh, whether deployed with Anthos on Google Cloud or with Anthos deployed on VMware. This is the third, and final, course of the Architecting Hybrid Cloud Infrastructure with Anthos series. Completion of the Architecting with Google Kubernetes Engine path is a prerequisite for this course.

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In this course, you'll learn about Kubernetes and Google Kubernetes Engine (GKE) security; logging and monitoring; and using Google Cloud managed storage and database services from within GKE. This is the second course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Reliable Google Cloud Infrastructure: Design and Process course or the Hybrid Cloud Infrastructure Foundations with Anthos course.

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In "Architecting with Google Kubernetes Engine- Workloads", you'll embark on a comprehensive journey into cloud-native application development. Throughout the learning experience, you'll explore Kubernetes operations, deployment management, GKE networking, and persistent storage. This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine- Production course.

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Welcome to Hybrid Cloud Infrastructure Foundations with Anthos! This is the first course of the Architecting Hybrid Cloud Infrastructure with Anthos path. Anthos enables you to build and manage modern applications, and gives you the freedom to choose where to run them. Anthos gives you one consistent experience in both your on-premises and cloud environments. During this course, you will be presented with modules that will take you through skills that you will use as an architect or administrator running Anthos environments. The modules in this course include videos, hands-on labs, and links to helpful documentation.

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在本课程“Google Kubernetes Engine 架构设计：基础知识”中，您将了解 Google Cloud 的概况和原理，然后学习如何创建和管理软件容器，以及了解 Kubernetes 的架构。 这是“Google Kubernetes Engine 架构设计”系列课程的第一门课程。完成本课程后，请报名参加“Google Kubernetes Engine 架构设计：工作负载”课程。

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This course helps you recognize the need to implement business process automation in your organization. You learn about automation patterns and use cases, and how to use AppSheet constructs to implement automation in your app. You learn about the various features of AppSheet automation, and integrate your app with Google Workspace products. You also learn how to send email, push notifications and text messages from your app, parse documents and generate reports with AppSheet automation.

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This course teaches you how to implement various capabilities that include data organization and management, application security, actions and integrations in your app using AppSheet. The course also includes topics on managing and upgrading your app, improving performance and troubleshooting issues with your app.

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In this course you will learn the fundamentals of no-code app development and recognize use cases for no-code apps. The course provides an overview of the AppSheet no-code app development platform and its capabilities. You learn how to create an app with data from spreadsheets, create the app’s user experience using AppSheet views and publish the app to end users.

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Google Cloud 云计算基础课程面向没有或很少有云计算基础或经验的人群。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。 完成本系列课程后，学员将能够清晰阐述这些概念，并掌握一些实际操作技能。 课程应按以下顺序完成： 1. Google Cloud 云计算基础课程：云计算基础知识 2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施 3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性 4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI 本课程是该系列课程的最后一门，回顾了托管式大数据服务、机器学习及其价值，以及如何通过获得技能徽章来进一步展示您在 Google Cloud 方面的技能。

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Google Cloud 云计算基础课程面向几乎没有云计算背景或经验的人士。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。 完成本课程系列后，学员将能够阐述这些概念，并展示一定的实操技能。 课程应按以下顺序完成： 1. Google Cloud 云计算基础课程：云计算基础知识 2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施 3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性 4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI 本课是第三门课程，介绍云端自动化和管理工具以及如何构建安全网络。

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Google Cloud 云计算基础课程面向云计算零基础或经验较少的人群。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。 完成本系列课程后，学员将能够清晰阐述这些概念，并掌握部分实操技能。 课程应按以下顺序完成： 1. Google Cloud 云计算基础课程：云计算基础知识 2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施 3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性 4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI

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Google Cloud 云计算基础课程面向云计算零基础或经验较少的人群。本课程概述了云计算基础知识、大数据和机器学习的核心概念，以及 Google Cloud 在其中的定位与应用方式。 完成本系列课程后，学员将能够清晰阐述这些概念，并掌握部分实操技能。 课程应按以下顺序完成： 1. Google Cloud 云计算基础课程：云计算基础知识 2. Google Cloud 云计算基础课程：Google Cloud 中的基础设施 3. Google Cloud 云计算基础课程：Google Cloud 中的网络服务和安全性 4. Google Cloud 云计算基础课程：Google Cloud 中的数据、机器学习和 AI 本课是第一门课程，概述了云计算、Google Cloud 的使用方式以及各种计算选项。

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In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.

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This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models. The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data. The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models. Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.

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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.

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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.

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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.

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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.

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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

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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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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。

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完成开发 Google Cloud 网络课程，赢取技能徽章。在此课程中，您将学习 部署和监控应用的多种方法，包括执行以下任务的方法：探索 IAM 角色并添加/移除 项目访问权限、创建 VPC 网络、部署和监控 Compute Engine 虚拟机、 编写 SQL 查询、在 Compute Engine 中部署和监控虚拟机，以及使用 Kubernetes 通过多种部署方法部署应用。

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完成“在 Google Cloud 上设置应用开发环境”课程，赢取技能徽章；通过该课程，您将了解如何使用以下技术的基本功能来构建和连接以存储为中心的云基础设施： Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。

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完成入门级技能徽章课程为 Compute Engine 实现云负载均衡，展示以下方面的技能： 在 Compute Engine 中创建和部署虚拟机 以及配置网络和应用负载均衡器。

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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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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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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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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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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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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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“Google Cloud 基础知识：核心基础设施”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务，并提供重要的资源和政策管理工具。

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Learn how to use Gemini Notebook to create a personalized study guide for the Associate Cloud Engineer certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook , and learn how to use a study guide to practice for a certification exam.

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