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Ray Safar

成为会员时间：2022

Handle Consumer Interactions with CCaaS Earned Jul 23, 2024 EDT
在 Google 試算表使用函式、公式及圖表 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
Looker 資料模型管理 Earned Apr 18, 2024 EDT
在 Looker 建構 LookML 物件 Earned Apr 17, 2024 EDT
在 Looker 應用進階 LookML 概念 Earned Apr 17, 2024 EDT
Understanding LookML in Looker Earned Apr 17, 2024 EDT
Google Cloud 資料分析簡介 Earned Apr 17, 2024 EDT
為 Looker 資訊主頁和報表準備資料 Earned Apr 17, 2024 EDT
使用 AppSheet 建構應用程式 Earned Apr 16, 2024 EDT
開始使用 Looker Earned Apr 16, 2024 EDT
在連結試算表中分析 BigQuery 資料 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
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則 Earned Apr 12, 2024 EDT
在 Vertex AI 設計提示 Earned Apr 12, 2024 EDT
負責任的 AI 技術簡介 Earned Apr 11, 2024 EDT
大型語言模型簡介 Earned Apr 11, 2024 EDT
生成式 AI 簡介 Earned Apr 11, 2024 EDT
Gemini in Google Meet Earned Apr 11, 2024 EDT
Gemini in Google Sheets Earned Apr 11, 2024 EDT
Gemini in Google Slides Earned Apr 11, 2024 EDT
Gemini in Google Docs Earned Apr 11, 2024 EDT
Gemini in Gmail Earned Apr 11, 2024 EDT
Gemini for Google Workspace 簡介 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 為機器學習 API 準備資料 Earned Mar 6, 2022 EST
在 Google Cloud 設定應用程式開發環境 Earned Mar 5, 2022 EST
Google Cloud 基礎知識：核心基礎架構 Earned Mar 5, 2022 EST
在 Compute Engine 導入 Cloud Load Balancing 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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完成在 Google 試算表使用函式、公式及圖表技能徽章中階課程， 即可證明您具備下列技能：運用函式分析資料、使用圖表呈現資料、設定資料格式，以及搜尋、 驗證與顯示資料。

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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 Looker 資料模型管理技能徽章中階課程，即可證明您具備下列技能：維護 LookML 專案的健全性、運用 SQL Runner 驗證資料、採用 LookML 最佳做法、改良查詢及 報表，並執行永久衍生資料表和快取政策。

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完成「在 Looker 建構 LookML 物件」技能徽章入門課程， 即可證明您具備下列技能： 建立新的維度和測量指標、檢視畫面和衍生資料表；根據需求設定測量指標篩選器和類型； 更新維度和測量指標； 建構及調整「探索」；將檢視表彙整至現有「探索」；以及配合業務需求決定要建立哪些 LookML 物件。

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在本課程中，您將透過實際操作，瞭解如何在 Looker 應用進階 LookerML 概念。您將學習如何使用 Liquid 自訂和建立動態維度 和測量指標、建構動態 SQL 衍生資料表和自訂的原生衍生資料表， 並運用擴充參數將 LookML 程式碼模組化。

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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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這堂初級課程將介紹 Google Cloud 的資料分析工作流程，以及用於探索、分析資料並以圖表呈現的工具。您也能學會如何與相關人員分享自己的發現結果。本課程包含個案研究、實作實驗室、講座、測驗和示範，實際展示如何將原始資料集轉化為清晰的資料，進而呈現出能發揮成效的圖表和資訊主頁。無論您是資料領域從業人員、想瞭解如何透過 Google Cloud 取得成功，或有意在職涯中更上一層樓，本課程都能協助您踏出第一步。絕大多數在工作上執行或運用資料分析的學員，都能從本課程受益。

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完成「為 Looker 資訊主頁和報表準備資料」技能徽章入門課程， 即可證明您具備下列技能：可篩選、排序和 pivot 資料、合併不同的 Looker 探索結果， 還能使用函式和運算子建構 Looker 資訊主頁和報表，取得資料分析結果和圖表。

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完成使用 AppSheet 建構應用程式課程，即可獲得技能徽章 ，瞭解如何使用 AppSheet 建構、設定及發布應用程式。

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完成「開始使用 Looker」技能徽章課程，即可獲得技能徽章， 您將從中瞭解如何使用 Looker Studio 和 Looker 分析、呈現及整理資料。

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完成「在連結試算表中分析 BigQuery 資料」技能徽章，即可證明您能使用連結試算表，在 Google 試算表中存取、分析及共用數十億列的 BigQuery 資料，還能以圖表呈現。

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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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隨著企業持續擴大使用人工智慧和機器學習，以負責任的方式發展相關技術也日益重要。對許多企業來說，談論負責任的 AI 技術可能不難，如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術，本課程絕對能助您一臂之力。 您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談，協助貴機構奠定良好基礎，實踐負責任的 AI 技術。

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完成 在 Vertex AI 設計提示 技能徽章入門課程，即可證明您具備下列技能： 在 Vertex AI 設計提示、分析圖片，以及運用多模態模型生成內容。瞭解如何建立有效的提示、引導生成式 AI 輸出內容， 以及將 Gemini 模型用於實際的行銷情境。

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這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。

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這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。

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這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。

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Gemini 版 Google Workspace 是一項外掛程式，可讓使用者存取生成式 AI 功能。本課程會使用影片、實作活動和練習範例，深入介紹 Gemini 版 Google Meet 的功能。您會學到如何透過 Gemini 生成背景圖片、提升視訊品質及翻譯字幕。本課程結束後，您將具備 Gemini 版 Google Meet 的知識及技能，安心運用這項工具提高視訊會議的效率。

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安裝 Gemini 版 Google Workspace 外掛程式後，客戶就能在 Google Workspace 使用生成式 AI 功能。這堂迷你課程會介紹 Gemini 的主要功能，並說明如何在 Google 試算表善用這些功能，提高生產力和效率。

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Gemini 版 Google Workspace 是一項外掛程式，可讓客戶在 Google Workspace 使用生成式 AI 功能。這堂迷你課程會介紹 Gemini 的主要功能，並說明如何在 Google 簡報善用這些功能，提高生產力和效率。

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使用者將能透過 Gemini 版 Google Workspace 外掛程式運用生成式 AI 功能。本課程會使用影片、實作活動和練習範例，深入介紹 Gemini 版 Google 文件的功能。您將學到如何透過 Gemini 使用提示生成撰寫內容、編輯寫好的文字，以提升整體工作效率。本課程結束後，您將具備 Gemini 版 Google 文件的知識及技能，可自信地運用這項工具提升寫作品質。

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Gemini 版 Google Workspace 是一項外掛程式，可讓客戶在 Google Workspace 使用生成式 AI 功能。這堂迷你課程會介紹 Gemini 的主要功能，並說明如何在 Gmail 善用這些功能，提高生產力和效率。

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客戶能透過 Gemini 版 Google Workspace 外掛程式在 Google Workspace 使用生成式 AI 功能。本學習路徑會介紹 Gemini 的主要功能，並說明如何在 Google Workspace 善用這些功能，提高生產力和效率。

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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 在 Google Cloud 為機器學習 API 準備資料 技能徽章入門課程，即可證明您具備下列技能： 使用 Dataprep by Trifacta 清理資料、在 Dataflow 執行資料管道、在 Dataproc 建立叢集和執行 Apache Spark 工作，以及呼叫機器學習 API，包含 Cloud Natural Language API、Google Cloud Speech-to-Text API 和 Video Intelligence API。

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只要修完「在 Google Cloud 設定應用程式開發環境」課程，就能獲得技能徽章。 在本課程中，您將學會如何使用以下技術的基本功能，建構和連結以儲存空間為中心的雲端基礎架構：Cloud Storage、Identity and Access Management、Cloud Functions 和 Pub/Sub。

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「Google Cloud 基礎知識：核心基礎架構」介紹了在使用 Google Cloud 時會遇到的重要概念和術語。本課程會透過影片和實作實驗室，介紹並比較 Google Cloud 的多種運算和儲存服務，同時提供重要的資源和政策管理工具。

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完成「在 Compute Engine 導入 Cloud Load Balancing」技能徽章入門課程，即可證明您具備下列技能： 在 Compute Engine 建立及部署虛擬機器， 以及設定網路和應用程式負載平衡器。

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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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