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在 Google Cloud 控制台中运用您的技能

Ray Safar

成为会员时间：2022

Handle Consumer Interactions with CCaaS Earned Jul 23, 2024 EDT
在 Google 表格中使用函数、公式和图表 Earned May 9, 2024 EDT
Preparing for your Professional Data Engineer Journey Earned May 7, 2024 EDT
Scaling with Google Cloud Operations Earned Apr 21, 2024 EDT
Exploring Data Transformation with Google Cloud Earned Apr 21, 2024 EDT
在 Looker 中管理数据模型 Earned Apr 18, 2024 EDT
在 Looker 中构建 LookML 对象 Earned Apr 17, 2024 EDT
在 Looker 中应用高级 LookML 概念 Earned Apr 17, 2024 EDT
Understanding LookML in Looker Earned Apr 17, 2024 EDT
Google Cloud 数据分析功能简介 Earned Apr 17, 2024 EDT
为 Looker 信息中心和报告准备数据 Earned Apr 17, 2024 EDT
用 AppSheet 来构建应用 Earned Apr 16, 2024 EDT
Looker 使用入门 Earned Apr 16, 2024 EDT
在关联工作表中分析 BigQuery 数据 Earned Apr 16, 2024 EDT
Trust and Security with Google Cloud Earned Apr 15, 2024 EDT
Innovating with Google Cloud Artificial Intelligence Earned Apr 15, 2024 EDT
Responsible AI: 和 Google Cloud 一起践行 AI 原则 Earned Apr 12, 2024 EDT
在 Vertex AI 中设计提示 Earned Apr 12, 2024 EDT
负责任的 AI 简介 Earned Apr 11, 2024 EDT
大型语言模型简介 Earned Apr 11, 2024 EDT
生成式 AI 简介 Earned Apr 11, 2024 EDT
Google Meet 中的 Gemini Earned Apr 11, 2024 EDT
Google 表格中的 Gemini Earned Apr 11, 2024 EDT
Google 幻灯片中的 Gemini Earned Apr 11, 2024 EDT
Google 文档中的 Gemini Earned Apr 11, 2024 EDT
Gmail 中的 Gemini Earned Apr 11, 2024 EDT
Gemini for Google Workspace 简介 Earned Apr 11, 2024 EDT
Building No-Code Apps with AppSheet: Automation Earned Nov 11, 2022 EST
Building No-Code Apps with AppSheet: Implementation Earned Nov 10, 2022 EST
Building No-Code Apps with AppSheet: Foundations Earned Nov 8, 2022 EST
Build, Train and Deploy ML Models with Keras on Google Cloud Earned Aug 28, 2022 EDT
Developing Data Models with LookML Earned Aug 8, 2022 EDT
Applying Machine Learning to your Data with Google Cloud Earned Jul 31, 2022 EDT
Achieving Advanced Insights with BigQuery Earned Jul 24, 2022 EDT
Creating New BigQuery Datasets and Visualizing Insights Earned Jul 23, 2022 EDT
Exploring and Preparing your Data with BigQuery Earned Jul 22, 2022 EDT
Machine Learning in the Enterprise Earned Jul 22, 2022 EDT
Analyzing and Visualizing Data in Looker Earned Apr 6, 2022 EDT
Launching into Machine Learning Earned Apr 3, 2022 EDT
How Google Does Machine Learning Earned Mar 11, 2022 EST
Scaling with Google Cloud Operations Earned Mar 6, 2022 EST
Modernize Infrastructure and Applications with Google Cloud Earned Mar 6, 2022 EST
Exploring Data Transformation with Google Cloud Earned Mar 6, 2022 EST
Digital Transformation with Google Cloud Earned Mar 6, 2022 EST
在 Google Cloud 上为机器学习 API 准备数据 Earned Mar 6, 2022 EST
在 Google Cloud 上设置应用开发环境 Earned Mar 5, 2022 EST
Google Cloud 基础知识：核心基础设施 Earned Mar 5, 2022 EST
为 Compute Engine 实现云负载均衡 Earned Mar 5, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals Earned Mar 4, 2022 EST

This course teaches contact center agents about the core agent features and functionality in Contact Center as a Service (CCaaS). CCaaS is a unified contact center platform that accelerates an organization's ability to leverage and deploy contact centers without relying on multiple technology providers. This course is most appropriate for those who handle consumer interactions via chat and call.

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完成中级技能徽章课程“在 Google 表格中使用函数、公式和图表”， 展现您在以下方面的技能：使用函数分析数据；使用图表直观呈现数据；以及搜索和验证数据、 设置数据格式、显示数据。

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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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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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完成中级技能徽章课程在 Looker 中管理数据 模型，展示以下方面的技能：维护 LookML 项目的健康状况；利用 SQL Runner 进行数据验证；采用 LookML 最佳实践；优化查询和 报告；以及实现永久性派生表和缓存政策。

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完成在 Looker 中构建 LookML 对象入门技能徽章课程，展示以下方面的技能： 构建新的维度、测量、视图和派生表；根据需求设置测量的过滤条件和 类型；更新维度和测量； 构建并优化探索；将视图联接到现有探索；并根据业务需求 决定要创建哪些 LookML 对象。

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在本课程中，您将获得在 Looker 中应用高级 LookML 概念 的实践经验。您将学习如何使用 Liquid 自定义和创建动态 维度和测量、创建动态 SQL 派生表和自定义原生 派生表，并运用扩展功能来模块化你的 LookML 代码

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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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在本新手级课程中，您将了解 Google Cloud 数据分析工作流，以及可用于探索、分析和直观呈现数据并与相关人员共享发现结果的工具。结合案例研究、实操实验、讲座和测验/演示，本课程展示了如何将原始数据集转化为纯净数据，进而转化为实用的可视化图表和信息中心。无论您是已经在从事数据工作并想了解如何通过 Google Cloud 取得成功，还是在寻求职业发展，都可以借助本课程迈出第一步。几乎所有在工作中执行或使用数据分析的人都可以从本课程中受益。

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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 Looker 使用入门技能徽章课程，赢取技能徽章， 在这门课程中，您将学习如何使用 Looker Studio 和 Looker 分析、直观呈现和整理数据。

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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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As organizations move their data and applications to the cloud, they must address new security challenges. The Trust and Security with Google Cloud course explores the basics of cloud security, the value of Google Cloud's multilayered approach to infrastructure security, and how Google earns and maintains customer trust in the cloud. 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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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. “Innovating with Google Cloud Artificial Intelligence” explores how organizations can use AI and ML to transform their business processes. 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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随着企业对人工智能和机器学习的应用越来越广泛，以负责任的方式构建这些技术也变得更加重要。但对很多企业而言，真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI，本课程正适合您。 本课程将介绍 Google Cloud 目前如何践行 Responsible AI，以及从中总结的最佳实践和经验教训，便于您以此为框架构建自己的 Responsible AI 方法。

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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。

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这是一节入门级微课程，旨在解释什么是负责任的 AI、它的重要性，以及 Google 如何在自己的产品中实现负责任的 AI。此外，本课程还介绍了 Google 的 7 个 AI 开发原则。

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这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。

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这是一节入门级微课程，旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。

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Google Workspace 专用 Gemini 是一个插件，可为用户提供对生成式 AI 功能的访问权限。本课程深入探讨了“Google Meet 中的 Gemini”的功能。通过视频课程、实操活动和实际示例，您将全面了解 Google Meet 中的 Gemini 功能。您将学习如何使用 Gemini 生成背景图片、提高视频质量以及翻译字幕。学完本课程后，您将掌握相关知识和技能，能够自信地利用 Google Meet 中的 Gemini 尽可能提高视频会议的效率。

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Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本迷你课程中，您将了解 Gemini 的主要功能，以及如何在 Google 表格中使用它们来提高工作效率。

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Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本迷你课程中，您将了解 Gemini 的主要功能，以及如何在 Google 幻灯片中使用它们来提高工作效率。

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Google Workspace 专用 Gemini 是一个插件，用户可通过它来使用生成式 AI 功能。本课程通过视频课程、实操活动和实际示例，深入探讨了“Google 文档中的 Gemini”的功能。您将学习如何使用 Gemini 来根据提示生成书面内容。您还会探索如何使用 Gemini 来修改已撰写好的文本，帮助提升整体工作效率。学完本课程后，您将掌握相关知识和技能，能够自信地利用 Google 文档中的 Gemini 来提升写作水平。

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Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本迷你课程中，您将了解 Gemini 的主要功能，以及如何在 Gmail 中使用这些功能来提高工作效率。

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Google Workspace 专用 Gemini 是一个插件，可在 Google Workspace 中为客户提供生成式 AI 功能。在本学习路线中，您将了解 Gemini 的主要功能，以及如何在 Google Workspace 中使用它们来提高工作效率。

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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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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 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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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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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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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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In this course, we see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Dataprep to analyze and transform your datasets. This is the first course of the From Data to Insights with Google Cloud series. After completing this course, enroll in the Creating New BigQuery Datasets and Visualizing Insights course.

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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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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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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 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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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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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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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 Dataproc 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“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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“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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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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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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