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Archit Sharma

成为会员时间：2022

黄金联赛

25850 积分
使用 Gemini 和 Imagen 构建实用 AI 应用 Earned Apr 17, 2025 EDT
在 Vertex AI 中设计提示 Earned Apr 17, 2025 EDT
Level 1: Google Cloud Console Earned Feb 10, 2024 EST
Google Cloud 云计算基础知识 Earned Jan 18, 2024 EST
Level 1: AppDev and Infrastructure Earned Jul 16, 2023 EDT
DEPRECATED Networking Fundamentals on Google Cloud Earned Jul 16, 2023 EDT
App Engine: 3 Ways Earned Jul 15, 2023 EDT
Create and Manage Cloud Spanner Instances Earned May 30, 2023 EDT
借助 Firebase 开发无服务器应用 Earned May 21, 2023 EDT
在 Google Cloud 上使用 Terraform 构建基础设施 Earned May 19, 2023 EDT
Google Workspace Core Services Earned May 2, 2023 EDT
Google Workspace Security Earned May 2, 2023 EDT
Google Workspace Data Governance Earned May 2, 2023 EDT
Google Calendar Earned May 2, 2023 EDT
Gmail Earned May 2, 2023 EDT
在 Vertex AI 上构建和部署机器学习解决方案 Earned Apr 25, 2023 EDT
使用 Google Cloud Observability 进行监控和记录 Earned Apr 25, 2023 EDT
在 Google Cloud 上部署 Kubernetes 应用 Earned Apr 25, 2023 EDT
Share Data Using Google Data Cloud Earned Apr 23, 2023 EDT
Use Machine Learning APIs on Google Cloud Earned Apr 23, 2023 EDT
优化 Google Kubernetes Engine 的费用 Earned Apr 22, 2023 EDT
DEPRECATED Planning for a Google Workspace Deployment Earned Apr 22, 2023 EDT
Machine Learning Operations (MLOps): Getting Started Earned Apr 22, 2023 EDT
On Premises Installation and Fundamentals with Google Cloud's Apigee API Platform Earned Feb 10, 2023 EST
Google Cloud Computing Foundation with Kubernetes Earned Jan 5, 2023 EST
云架构：设计、实施和管理 Earned Jan 5, 2023 EST
Measure Site Reliability using Cloud Operations Suite Earned Jan 4, 2023 EST
在 Cloud Run 上开发无服务器应用 Earned Jan 4, 2023 EST
App Deployment, Debugging, and Performance Earned Jan 2, 2023 EST
可靠的 Google Cloud 基础设施: 设计和流程 Earned Dec 29, 2022 EST
Logging and Monitoring in Google Cloud Earned Dec 29, 2022 EST
API Security on Google Cloud's Apigee API Platform Earned Dec 28, 2022 EST
Production Machine Learning Systems Earned Dec 28, 2022 EST
Google Cloud 重要基础设施：核心服务 Earned Dec 28, 2022 EST
Google Cloud 弹性基础设施：扩缩和自动化 Earned Dec 28, 2022 EST
Architecting with Google Kubernetes Engine: Foundations - 简体中文 Earned Dec 28, 2022 EST
Architecting with Google Kubernetes Engine: Workloads Earned Dec 28, 2022 EST
Architecting with Google Kubernetes Engine: Production Earned Dec 28, 2022 EST
Google Kubernetes Engine 使用入门 Earned Dec 28, 2022 EST
Anthos on Bare Metal Earned Dec 26, 2022 EST
Hybrid Cloud Service Mesh with Anthos Earned Dec 26, 2022 EST
Multi-Cluster, Multi-Cloud with Anthos Earned Dec 26, 2022 EST
Hybrid Cloud Multi-Cluster with Anthos Earned Dec 26, 2022 EST
Recommendation Systems on Google Cloud Earned Dec 25, 2022 EST
Natural Language Processing on Google Cloud Earned Dec 25, 2022 EST
Security Best Practices in Google Cloud Earned Dec 25, 2022 EST
Networking in Google Cloud: Fundamentals Earned Dec 25, 2022 EST
Hybrid Cloud Modernizing Applications with Anthos Earned Dec 25, 2022 EST
Mitigating Security Vulnerabilities on Google Cloud Earned Dec 25, 2022 EST
Machine Learning in the Enterprise Earned Dec 25, 2022 EST
Google Cloud 重要基础设施：基础 Earned Dec 25, 2022 EST
API Design and Fundamentals of Google Cloud's Apigee API Platform Earned Dec 25, 2022 EST
API Development on Google Cloud's Apigee API Platform Earned Dec 25, 2022 EST
Getting Started with Terraform for Google Cloud Earned Dec 25, 2022 EST
DEPRECATED Cloud Operations and Service Mesh with Anthos Earned Dec 25, 2022 EST
Feature Engineering Earned Dec 25, 2022 EST
Build, Train and Deploy ML Models with Keras on Google Cloud Earned Dec 25, 2022 EST
Application Development with Cloud Run Earned Dec 24, 2022 EST
How Google Does Machine Learning Earned Dec 24, 2022 EST
Networking in Google Cloud: Routing and Addressing Earned Dec 24, 2022 EST
Architecting and Installing the Apigee Hybrid API Platform Earned Dec 24, 2022 EST
Managing Security in Google Cloud Earned Dec 24, 2022 EST
Virtual Agent Development in Dialogflow ES for Software Devs Earned Dec 24, 2022 EST
On Premises Management, Security, and Upgrade with Google Cloud's Apigee API Platform Earned Dec 24, 2022 EST
Contact Center AI: Conversational Design Fundamentals Earned Dec 24, 2022 EST
Virtual Agent Development in Dialogflow ES for Citizen Devs Earned Dec 24, 2022 EST
Virtual Agent Development in Dialogflow CX for Citizen Devs Earned Dec 23, 2022 EST
CCAI Operations and Implementation Earned Dec 23, 2022 EST
Virtual Agent Development in Dialogflow CX for Software Devs Earned Dec 23, 2022 EST
On Premises Capacity Upgrade and Monitoring with Google Cloud's Apigee API Platform Earned Dec 23, 2022 EST
Google Cloud Fundamentals for Azure Professionals: Core Infrastructure Earned Dec 23, 2022 EST
Monitor Environments with Google Cloud Managed Service for Prometheus Earned Dec 21, 2022 EST
DEPRECATED Language, Speech, Text, & Translation with Google Cloud APIs Earned Dec 20, 2022 EST
Google Cloud Fundamentals for AWS Professionals Earned Dec 7, 2022 EST
Digital Transformation with Google Cloud - Locales Earned Dec 7, 2022 EST
Google Cloud Fundamentals: Core Infrastructure - 简体中文 Earned Dec 7, 2022 EST
Google Workspace User and Resource Management Earned Dec 7, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals - Locales Earned Dec 7, 2022 EST
Building Resilient Streaming Analytics Systems on Google Cloud - Locales Earned Dec 7, 2022 EST
Smart Analytics, Machine Learning, and AI on Google Cloud - Locales Earned Dec 7, 2022 EST
Google Cloud 基础知识：核心基础设施 Earned Dec 7, 2022 EST
Migrating to Google Cloud Earned Dec 4, 2022 EST
Understand Your Google Cloud Costs Earned Dec 4, 2022 EST
Managing Cloud Infrastructure with Terraform Earned Dec 4, 2022 EST
Preparing for Your Professional Data Engineer Journey - Locales Earned Dec 2, 2022 EST
构建安全的 Google Cloud 网络 Earned Dec 1, 2022 EST
DEPRECATED Network Performance and Optimization Earned Dec 1, 2022 EST
Launching into Machine Learning Earned Nov 30, 2022 EST
在 Google Cloud 上实施云安全基础措施 Earned Nov 30, 2022 EST
开发 Google Cloud 网络 Earned Nov 30, 2022 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned Nov 29, 2022 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud Earned Nov 29, 2022 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud Earned Nov 29, 2022 EST
Understanding LookML in Looker Earned Nov 28, 2022 EST
在 Google Cloud 上设置应用开发环境 Earned Nov 28, 2022 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned Nov 23, 2022 EST
Analyzing and Visualizing Data in Looker Earned Nov 23, 2022 EST
从 BigQuery 数据中挖掘数据洞见 Earned Nov 23, 2022 EST
通过 BigQuery ML 创建机器学习模型 Earned Nov 23, 2022 EST
Applying Advanced LookML Concepts in Looker Earned Nov 23, 2022 EST
Build LookML Objects in Looker Earned Nov 22, 2022 EST
Manage Data Models in Looker Earned Nov 22, 2022 EST
利用 BigQuery ML 构建预测模型时的数据工程处理 Earned Nov 22, 2022 EST
Creating New BigQuery Datasets and Visualizing Insights Earned Nov 22, 2022 EST
Achieving Advanced Insights with BigQuery Earned Nov 22, 2022 EST
Applying Machine Learning to your Data with Google Cloud Earned Nov 22, 2022 EST
Developing Data Models with LookML Earned Nov 21, 2022 EST
使用 BigQuery 构建数据仓库 Earned Nov 21, 2022 EST
Building Batch Data Pipelines on Google Cloud Earned Nov 20, 2022 EST
Building Resilient Streaming Analytics Systems on Google Cloud Earned Nov 20, 2022 EST
Smart Analytics, Machine Learning, and AI on Google Cloud Earned Nov 20, 2022 EST
Serverless Data Processing with Dataflow: Foundations Earned Nov 20, 2022 EST
Modernizing Data Lakes and Data Warehouses with Google Cloud Earned Nov 19, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals Earned Nov 19, 2022 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned Nov 6, 2022 EST
Google Cloud Computing Foundations: Networking and Security in Google Cloud Earned Oct 31, 2022 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud Earned Oct 26, 2022 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned Oct 23, 2022 EDT
Preparing for your Professional Data Engineer Journey Earned Sep 1, 2022 EDT
Scaling with Google Cloud Operations Earned Aug 29, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud Earned Aug 29, 2022 EDT
Exploring Data Transformation with Google Cloud Earned Aug 29, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey Earned Aug 25, 2022 EDT
Digital Transformation with Google Cloud Earned Aug 17, 2022 EDT

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 Vertex AI 中设计提示入门技能徽章课程，展示以下方面的技能： Vertex AI 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。 技能徽章 是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 并在您的社交圈中秀一秀自己的水平。

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Google Cloud Console serves as a centralized hub where users can access and control their cloud infrastructure, services, and applications. It is essential for users, developers, and administrators who work with Google Cloud Platform. Game on to get familiar with Google Cloud Console, and get your hands on a Google Cloud Credential. No prior experience required!

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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。 技能徽章是一种专有数字徽章， 由 Google Cloud 颁发，旨在认可您已熟悉特定的 Google Cloud 产品与服务， 并在交互式实操环境中证明了运用所学知识 的能力。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得相应的数字徽章，在您的人际圈中秀出自己的技能。

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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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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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Earn a skill badge by completing the App Engine: 3 ways quest, where you learn how to use App Engine with Python, Go, and PHP. 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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Complete the introductory Create and Manage Cloud Spanner Instances skill badge to demonstrate skills in the following: creating and interacting with Cloud Spanner instances and databases; loading Cloud Spanner databases using various techniques; backing up Cloud Spanner databases; defining schemas and understanding query plans; and deploying a Modern Web App connected to a Cloud Spanner instance.

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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。 技能徽章 是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 在您的人际圈中炫出自己的技能。

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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。 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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This course was designed to give learners a comprehensive understanding of Google Workspace core services. Learners will explore enabling, disabling, and configuring settings for these services, including Gmail, Calendar, Drive, Meet, Chat, and Docs. Next, they'll learn how to deploy and manage Gemini to empower their users. Finally, learners will examine use cases for AppSheet and Apps Script to automate tasks and extend the functionality of Google Workspace applications.

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This course empowers learners to secure their Google Workspace environment. Learners will implement strong password policies and two-step verification to govern user access. They will then utilize the security investigation tool to proactively identify and respond to security risks. Next, they will manage third-party app access and mobile devices to ensure security. Finally, learners will enforce email security and compliance measures to protect organizational data.

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This course equips learners with skills to govern data within their Google Workspace environment. Learners will explore data loss prevention rules in Gmail and Drive to prevent data leakage. They will then learn how to use Google Vault for data retention, preservation, and retrieval purposes. Next, they will learn how to configure data regions and export settings to align with regulations. Finally, learners will discover how to classify data using labels for enhanced organization and security.

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With Google Calendar, you can quickly schedule meetings and events and create tasks, so you always know what’s next. Google Calendar is designed for teams, so it’s easy to share your schedule with others and create multiple calendars that you and your team can use together. In this course, you’ll learn how to create and manage Google Calendar events. You will learn how to update an existing event, delete and restore events, and search your calendar. You will understand when to apply different event types such as tasks and appointment schedules. You will explore the Google Calendar settings that are available for you to customize Google Calendar to suit your way of working. During the course you will learn how to create additional calendars, share your calendars with others, and access other calendars in your organization.

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Gmail is Google’s cloud based email service that allows you to access your messages from any computer or device with just a web browser. In this course, you’ll learn how to compose, send and reply to messages. You will also explore some of the common actions that can be applied to a Gmail message, and learn how to organize your mail using Gmail labels. You will explore some common Gmail settings and features. For example, you will learn how to manage your own personal contacts and groups, customize your Gmail Inbox to suit your way of working, and create your own email signatures and templates. Google is famous for search. Gmail also includes powerful search and filtering. You will explore Gmail’s advanced search and learn how to filter messages automatically.

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完成在 Vertex AI 上构建和部署机器学习解决方案课程，赢取中级技能徽章。 在此课程中，您将了解如何使用 Google Cloud 的 Vertex AI Platform、AutoML 以及自定义训练服务来 训练、评估、调优、解释和部署机器学习模型。 此技能徽章课程的目标受众是专业的数据科学家和机器学习 工程师。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您对 Google Cloud 产品与服务的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能徽章课程 和作为最终评估的实验室挑战赛，即可获得数字徽章， 在您的人际圈中炫出自己的技能。

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完成入门级使用 Google Cloud Observability 进行监控和记录技能徽章课程， 展示自己在以下方面的技能：监控 Compute Engine 中的虚拟机； 利用 Cloud Monitoring 监控多个项目；将监控和日志记录功能扩展到 Cloud Functions； 创建和发送自定义应用指标；以及根据自定义指标配置 Cloud Monitoring 提醒。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 在您的人际圈中炫出自己的技能。

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完成在 Google Cloud 上部署 Kubernetes 应用技能徽章中级课程，展示您在以下方面的技能： 配置和构建 Docker 容器映像，创建和管理 Google Kubernetes Engine (GKE) 集群，利用 kubectl 实现高效 集群管理，以及按照稳健的持续交付 (CD) 实践部署 Kubernetes 应用。 技能徽章是由 Google Cloud 颁发的专有数字徽章，旨在认可您在 Google Cloud 产品与服务方面的熟练度； 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。 完成此技能徽章课程和作为最终评估的实验室挑战赛，获得技能徽章，在您的人际圈中炫出自己的技能。

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Earn a skill badge by completing the Share Data Using Google Data Cloud course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards. 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 course, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.

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完成中级技能徽章课程“优化 Google Kubernetes Engine 的费用”， 展示您在以下方面的技能：创建和管理多租户集群、按命名空间监控资源使用情况、 配置集群和 Pod 自动扩缩以提高效率、设置负载均衡以实现最佳资源分布， 以及实现活跃性与就绪性探测以确保应用正常运行并具有成本效益。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 证明您在特定 Google Cloud 产品与服务方面的熟练程度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 在您的人际圈中炫出自己的技能。

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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series. In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area. You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training. This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.

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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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This course introduces you to the fundamentals and advanced practices applicable to the installation and management of Google Cloud's Apigee API Platform for private cloud. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, install, secure, manage, and scale Apigee API Platform. This is the first course of the Installing and Managing Google Cloud's Apigee API Platform for Private Cloud series. After completing this course, enroll in the On Premises Management, Security, and Upgrade with Google Cloud's Apigee API Platform course.

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This module helps you build a robust understanding of concepts related to Networking, Security & Kubernetes Engine. This course is part of a series of courses called Google Cloud Computing Foundations. The courses should be completed in the following order: Google Cloud Computing Foundations: Cloud Computing Fundamentals Google Cloud Computing Foundations: Infrastructure in Google Cloud Google Cloud Computing Foundations: Networking and Security in Google Cloud Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Google Cloud Computing Foundation with Kubernetes

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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。 技能徽章 是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 在您的人际圈中炫出自己的技能。

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Earn a skill badge by completing the Measure Site Reliability using Cloud Operations Suite quest, where you will learn how to set Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Service Level Agreements (SLAs); create logs-based metrics to capture to capture specific issues and address them; define alerts to notify Site Reliability Engineers of issues in production environment, and troubleshoot application issues with Cloud Trace, Debugger, Profiler, Monitoring and Logging. 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 quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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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。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度。您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，获得技能徽章， 并在您的社交圈中秀一秀自己的成就。

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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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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 teaches participants techniques for monitoring and improving infrastructure and application performance in Google Cloud. Using a combination of presentations, demos, hands-on labs, and real-world case studies, attendees gain experience with full-stack monitoring, real-time log management and analysis, debugging code in production, tracing application performance bottlenecks, and profiling CPU and memory usage.

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In this course, you learn how to secure your APIs. You explore the security concerns you will encounter for your APIs. You learn about OAuth, the primary authorization method for REST APIs. You will learn about JSON Web Tokens (JWTs) and federated security. You also learn about securing against malicious requests, safely sending requests across a public network, and how to secure your data for users of Apigee. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the second course of the Developing APIs with Google Cloud's Apigee API Platform series. After completing this course, enroll in the API Development on Google Cloud's Apigee API Platform course.

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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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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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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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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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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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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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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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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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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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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 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 self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.

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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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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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In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.

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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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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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In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API life cycle, and how the Apigee API platform helps you manage all aspects of the life cycle. You learn about how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the first course of the Developing APIs with Google Cloud's Apigee API Platform series. After completing this course, enroll in the API Security on Google Cloud's Apigee API Platform course.

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In this course, you learn how to create APIs that utilize multiple services and how you can use custom code on Apigee. You will also learn about fault handling, and how to share logic between proxies. You learn about traffic management and caching. You also create a developer portal, and publish your API to the portal. You learn about logging and analytics, as well as CI/CD and the different deployment models supported by Apigee. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform.This is the third and final course of the Developing APIs with Google Cloud's Apigee API Platform course series.

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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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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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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 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 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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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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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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This course introduces you to the fundamentals and practices used to install and manage Google Cloud's Apigee API Platform for hybrid cloud. Through a combination of lectures, a hands-on lab, and supplemental materials, you will learn how to install and operate the Apigee API Platform.

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls. This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.

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Welcome to "CCAI Virtual Agent Development in Dialogflow ES for Software Developers", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn to use additional features of Dialogflow ES for your virtual agent, create a Firestore instance to store customer data, and implement cloud functions that access the data. With the ability to read and write customer data, learner’s virtual agents are conversationally dynamic and able to defer contact center volume from human agents. You'll be introduced to methods for testing your virtual agent and logs which can be useful for understanding issues that arise. Lastly, learn about connectivity protocols, APIs, and platforms for integrating your virtual agent with services already established for your business.

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This course discusses the management and operation of the Apigee platform for private cloud. It includes topics on operational practices, API deployment, analytics, security and upgrade of the platform. This is the second course of the Installing and Managing Google Cloud's Apigee API Platform for Private Cloud course series. After completing this course, enroll in the On Premises Capacity Upgrade and Monitoring with Google Cloud's Apigee API Platform course.

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Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.

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Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will use Dialogflow ES to create virtual agents and test them using the Dialogflow ES simulator. This course also provides best practices on developing virtual agents. You will also be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations. Through a combination of presentations, demos, and hands-on labs, participants learn how to create virtual agents. This is an intermediate course, intended for learners with the following types of roles: Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows. Citizen developers: Creates new business applications fo…

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Welcome to "Virtual Agent Development in Dialogflow CX for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations using Dialogflow CX.

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Welcome to "CCAI Operations and Implementation", the fourth course in the "Customer Experiences with Contact Center AI" series. In this course, learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale. In this course, you'll be introduced to Agent Assist and the technology it uses so you can delight your customers with the efficiencies and accuracy of services provided when customers require human agents, connectivity protocols, APIs, and platforms which you can use to create an integration between your virtual agent and the services already established for your business, Dialogflow's Environment Management tool for deployment of different versions of your virtual agent for various purposes, compliance measures and regulations you should be aware of when bringing your virtual agent to production, and you'll be given tips from virtua…

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Welcome to "Virtual Agent Development in Dialogflow CX for Software Devs", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop more customized customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to more advanced and customized handling for virtual agent conversations that need to look up and convey dynamic data, and methods available to you for testing your virtual agent and logs which can be useful for understanding issues that arise. This is an intermediate course, intended for learners with the following type of role: Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API.

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Learn how to upgrade capacity for the Apigee for private cloud platform installation, and how to monitor the platform. This is the third and final course of the Installing and Managing Google Cloud's Apigee API Platform for Private Cloud series.

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Google Cloud Fundamentals for Azure 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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Earn a skill badge by completing the Monitor Environments with Managed Service for Prometheus quest, where you learn Kubernetes Monitoring with Google Cloud Managed Service for Prometheus. 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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In this quest you will use a collection of Google APIs that are all related to language, and speech. You will use the Speech-to-Text API to transcribe an audio file into a text file, the Cloud Translation API to translate from one language to another, the Cloud Translation API to detect what language is being used and translate to a different language, the Natural Language API to classify text and analyze sentiment, and create synthetic speech.

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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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This course, Digital Transformation with Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Digital Transformation with Google Cloud. 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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“Google Cloud 基础知识：核心基础架构”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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This course was designed to provide an understanding of user and resource management in Google Workspace. Learners will explore the configuration of organizational units to align with their organization's needs. Additionally, learners will discover how to manage various types of Google Groups. They will also develop expertise in managing domain settings within Google Workspace. Finally, learners will master the optimization and structuring of resources within their Google Workspace environment.

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This course, Google Cloud Big Data and Machine Learning Fundamentals - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Big Data and Machine Learning Fundamentals. 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, Building Resilient Streaming Analytics Systems on Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Building Resilient Streaming Analytics Systems on Google Cloud. Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud using QwikLabs.

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This course, Smart Analytics, Machine Learning, and AI on Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Smart Analytics, Machine Learning, and AI on Google Cloud. Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.

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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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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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This Quest is most suitable for those working in a technology or finance role who are responsible for managing Google Cloud costs. You’ll learn how to set up a billing account, organize resources, and manage billing access permissions. In the hands-on labs, you'll learn how to view your invoice, track your Google Cloud costs with Billing reports, analyze your billing data with BigQuery or Google Sheets, and create custom billing dashboards with Looker Studio. References made to links in the videos can be accessed in this Additional Resources document.

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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.

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This course, Preparing for your Professional Data Engineer Journey - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Preparing for your Professional Data Engineer Journey. 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.

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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。 技能徽章是由 Google Cloud 颁发的专有数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 在您的人际圈中炫出自己的技能。

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If you want to take your Google Cloud networking skills to the next level, look no further. This course is composed of labs that cover real-life use cases and it will teach you best practices for overcoming common networking bottlenecks. From getting hands-on practice with testing and improving network performance, to integrating high-throughput VPNs and networking tiers, Network Performance and Optimization is an essential course for Google Cloud developers who are looking to double down on application speed and robustness.

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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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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。 技能徽章是由 Google Cloud 颁发的专有数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 并在您的社交圈中秀一秀自己的能力。

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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。 技能徽章是 由 Google Cloud 颁发的专有数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在交互式实操环境中参加考核， 证明自己运用所学知识的能力后才能获得。完成此技能徽章课程和 作为最终评估的实验室挑战赛，即可获得技能徽章，并在您的社区圈中秀一秀 自己的水平。

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This third course covers cloud automation and management tools and building secure networks.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud

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In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.

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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。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度；您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得。完成此技能徽章课程和作为最终评估的实验室挑战赛，获得技能徽章，在您的人际圈中炫出自己的技能。

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.

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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

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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 Looker Studio 中 创建报告。 技能徽章是由 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度。 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章 。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得技能徽章，在您的人际圈中炫出自己的技能。

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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。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您在 Google Cloud 产品与服务方面的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成此技能 徽章课程和作为最终评估的实验室挑战赛，即可获得技能徽章， 在您的人际圈中炫出自己的技能。

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In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.

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Complete the introductory Build LookML Objects in Looker skill badge to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.

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Complete the intermediate Manage Data Models in Looker skill badge to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies. 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 course, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

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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。 技能徽章是由 Google Cloud 颁发的专属数字徽章，旨在认可 您对 Google Cloud 产品与服务的熟练度；您需要在 交互式实操环境中参加考核，证明自己运用所学知识的能力后才能获得此徽章。完成技能徽章课程和 作为最终评估的实验室挑战赛，即可获得数字徽章， 在您的人际圈中炫出自己的技能。

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This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.

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The third course in this course series is Achieving Advanced Insights with BigQuery. Here we will build on your growing knowledge of SQL as we dive into advanced functions and how to break apart a complex query into manageable steps. We will cover the internal architecture of BigQuery (column-based sharded storage) and advanced SQL topics like nested and repeated fields through the use of Arrays and Structs. Lastly we will dive into optimizing your queries for performance and how you can secure your data through authorized views. After completing this course, enroll in the Applying Machine Learning to your Data with Google Cloud course.

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In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.

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This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.

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完成中级技能徽章课程使用 BigQuery 构建数据仓库，展示以下技能： 联接数据以创建新表、排查联接故障、使用并集附加数据、创建日期分区表， 以及在 BigQuery 中使用 JSON、数组和结构体。 技能徽章是 Google Cloud 颁发的专属数字徽章， 旨在认可您在 Google Cloud 产品与服务方面的熟练度； 您需要在交互式实操环境中参加考核，证明自己运用所学知识的能力后 才能获得。完成此技能徽章课程和作为最终评估的实验室挑战赛， 获得数字徽章，在您的人际圈中炫出自己的技能。

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Data pipelines typically fall under one of the Extract and Load (EL), Extract, Load and Transform (ELT) or Extract, Transform and Load (ETL) paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.

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Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Bigtable for analysis. Learners get hands-on experience building streaming data pipeline components on Google Cloud by using QwikLabs.

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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

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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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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment. This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.

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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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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide a detailed overview of concepts covering cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the course, learners will be able to articulate concepts around cloud computing, big data, and machine learning, and demonstrate some hands-on skills. This course is part of a series of courses called Google Cloud Computing Foundations. The courses should be completed in the following order: Google Cloud Computing Foundations: Cloud Computing Fundamentals Google Cloud Computing Foundations: Infrastructure in Google Cloud Google Cloud Computing Foundations: Networking and Security in Google Cloud Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Google Cloud Computing Foundation with Kubernetes This final course in the series rev…

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide a detailed overview of concepts covering cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the course, learners will be able to articulate concepts around cloud computing, big data, and machine learning, and demonstrate some hands-on skills. This course is part of a series of courses called Google Cloud Computing Foundations. The courses should be completed in the following order: Google Cloud Computing Foundations: Cloud Computing Fundamentals Google Cloud Computing Foundations: Infrastructure in Google Cloud Google Cloud Computing Foundations: Networking and Security in Google Cloud Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Google Cloud Computing Foundation with Kubernetes This third course covers how to build secure networks, …

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. This course is part of a series of courses called Google Cloud Computing Foundations. The courses should be completed in the following order: Google Cloud Computing Foundations: Cloud Computing Fundamentals Google Cloud Computing Foundations: Infrastructure in Google Cloud Google Cloud Computing Foundations: Networking and Security in Google Cloud Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Google Cloud Computing Foundations: Kubernetes Engine Fundamentals This first course provides an overview of cloud computing, ways to use 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.

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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. "Modernize Infrastructure and Applications with Google Cloud" explores these challenges and offers solutions to overcome them by using cloud technology. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences. “Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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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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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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