Build Batch Data Pipelines on Google Cloud
Earned Jun 21, 2023 EDT
Cloud Run Functions: 3 種使用方式
Earned Jun 19, 2023 EDT
Level 2: Cloud security
Earned Jun 19, 2023 EDT
Google Cloud 監控工具
Earned Jun 19, 2023 EDT
在 Cloud Storage 建立安全的資料湖泊
Earned Jun 18, 2023 EDT
開始使用 Eventarc
Earned Jun 18, 2023 EDT
開始使用 Cloud Storage
Earned Jun 16, 2023 EDT
使用 Google API 分析語音和語言
Earned Jun 15, 2023 EDT
Level 1: Data with Google Cloud
Earned Jun 15, 2023 EDT
開始使用 Dataplex
Earned Jun 15, 2023 EDT
在 Cloud Storage 建立串流資料湖泊
Earned Jun 15, 2023 EDT
開始使用 Looker
Earned Jun 14, 2023 EDT
Kubernetes 是最受歡迎的容器自動化調度管理系統，Google Kubernetes Engine 則專門支援 Google Cloud 中的 代管 Kubernetes 部署項目。這門進階課程將帶您實際練習設定 Docker 映像檔和容器，並部署完整的 Kubernetes Engine 應用程式。 您會學到如何將容器自動化調度管理機制， 整合到自己的工作流程，這些技巧相當實用。 想透過實作挑戰實驗室展現 技能、驗收學習成果嗎？本課程結束後，再完成 在 Google Cloud 部署 Kubernetes 應用程式課程 結尾的挑戰實驗室，即可獲得專屬 Google Cloud 數位徽章。
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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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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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具，可協助開發人員透過 Google Cloud 建構應用程式。您將瞭解如何透過提示讓 Gemini 為您解釋程式碼內容、推薦 Google Cloud 服務，以及生成應用程式的程式碼。在實作研究室中，您也會體驗到 Gemini 如何改良應用程式的開發工作流程。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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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「Introduction to Generative AI」、「Introduction to Large Language Models」和「Introduction to Responsible AI」課程，即可獲得技能徽章。通過最終測驗，就能展現您對生成式 AI 基本概念的掌握程度。
「技能徽章」是 Google Cloud 核發的數位徽章，用於表彰您對 Google Cloud 產品和服務的相關知識。您可以將技能徽章公布在社群媒體的個人資料中，向其他人分享您的成果。
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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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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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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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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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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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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!
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As employers increasingly seek data experts on a global scale to solve real-world problems, we want you to stay ahead of the curve by acquiring the latest and most in-demand data skills. Game on to showcase your talent to the world by earning your first Google Cloud Credential!
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The beautiful game is changing, and data science is playing a big role. Teams are now using data to make better decisions about everything, from player recruitment to game strategy. We invite you to get hands-on experience on the fundamentals of sports data science no matter who you're cheering for! Use BigQuery ML to train advanced models to predict goals and evaluate performance. Learn new skills and get started towards earning your first Google Cloud Credential. No prior experience required.
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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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Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.
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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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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.
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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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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大數據、機器學習和人工智慧 (AI) 是時下熱門的 電腦相關話題，但這些領域相當專業，就算想要入門 也難以取得教材或資料。幸好，Google Cloud 提供了此領域的多種服務，而且容易使用。 參加這堂入門課程，您就能踏出第一步， 開始學習運用 BigQuery、Cloud Speech API 以及 Video Intelligence 等工具。
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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.
In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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若想獲得入門技能徽章，請完成「Cloud Run Functions: 3 種使用方式」課程， 瞭解如何在 Google Cloud 控制台和指令列中 使用 Cloud Run functions。
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There’s so much more to cloud security than making your passwords something other than “password”. As more and more businesses move their data and applications to the cloud, the importance of - and demand for - cloud security is growing exponentially. In fact, the demand for cloud security professionals is outpacing the supply: according to a report by Cybersecurity Ventures, there are roughly 3.5 million unfilled cybersecurity positions around the world in 2023. Unlock your cloud security potential with hands-on experience in the Arcade - each lab teaches and tests your growing tech skills, and sets you on the path to a Google Cloud credential.
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完成「Google Cloud 監控工具」技能徽章入門課程， 即可證明您具備下列技能：使用 Cloud Monitoring 工具監控 Google Cloud 資源。
完成「使用 Google API 分析語音和語言」課程， 瞭解如何將 Natural Language API 和 Speech API 投入實際應用， 即可獲得技能徽章。
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The demand for data skills is growing rapidly, and we want you to get some of that sweet knowledge! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. Data can be used to identify trends, patterns, and insights that can help businesses improve their operations, products, and services - which makes data career paths highly valuable. There are a lot of different aspects to data science, so it's important to start with the basics - and we’ve got you covered. Kickstart your data skills discovery and get hands-on experience in the Arcade, with labs that help you learn and earn your first Google Cloud credential. No experience required.
Google Cloud 中的 Kubernetes
Earned Aug 13, 2024 EDT
Build Streaming Data Pipelines on Google Cloud
Earned Jul 1, 2024 EDT
Managing Cloud Infrastructure with Terraform
Earned Jun 30, 2024 EDT
使用 Gemini：應用程式開發人員
Earned Feb 6, 2024 EST
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Jan 25, 2024 EST
Generative AI Fundamentals - 繁體中文
Earned Jan 25, 2024 EST
Serverless Data Processing with Dataflow: Foundations
Earned Dec 3, 2023 EST
Exploring Data Transformation with Google Cloud
Earned Nov 30, 2023 EST
Modernize Infrastructure and Applications with Google Cloud
Earned Nov 27, 2023 EST
Scaling with Google Cloud Operations
Earned Nov 17, 2023 EST
負責任的 AI 技術簡介
Earned Nov 11, 2023 EST
Level 3: GenAI
Earned Sep 29, 2023 EDT
Level 2: BigQuery and BigLake Data Skills
Earned Sep 25, 2023 EDT
Level 1: Sports Data
Earned Sep 20, 2023 EDT
大型語言模型簡介
Earned Sep 13, 2023 EDT
生成式 AI 簡介
Earned Sep 13, 2023 EDT
Data Lake Modernization on Google Cloud: Cloud Composer
Earned Aug 20, 2023 EDT
DEPRECATED BigQuery for Data Warehousing
Earned Aug 6, 2023 EDT
Digital Transformation with Google Cloud
Earned Jul 27, 2023 EDT
App Engine：3 種應用
Earned Jul 25, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Jun 30, 2023 EDT
Preparing for your Professional Data Engineer Journey
Earned Jun 29, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Jun 27, 2023 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned Jun 27, 2023 EDT
[DEPRECATED] Data Engineering
Earned Jun 26, 2023 EDT
Creating New BigQuery Datasets and Visualizing Insights
Earned Jun 26, 2023 EDT
基本概念：資料、機器學習和 AI
Earned Jun 23, 2023 EDT
Exploring and Preparing your Data with BigQuery
Earned Jun 23, 2023 EDT
在 Compute Engine 導入 Cloud Load Balancing
Earned Jun 21, 2023 EDT
Build Batch Data Pipelines on Google Cloud
Earned Jun 21, 2023 EDT
Cloud Run Functions: 3 種使用方式
Earned Jun 19, 2023 EDT
Level 2: Cloud security
Earned Jun 19, 2023 EDT
Google Cloud 監控工具
Earned Jun 19, 2023 EDT
在 Cloud Storage 建立安全的資料湖泊
Earned Jun 18, 2023 EDT
開始使用 Eventarc
Earned Jun 18, 2023 EDT
開始使用 Cloud Storage
Earned Jun 16, 2023 EDT
使用 Google API 分析語音和語言
Earned Jun 15, 2023 EDT
Level 1: Data with Google Cloud
Earned Jun 15, 2023 EDT
開始使用 Dataplex
Earned Jun 15, 2023 EDT
在 Cloud Storage 建立串流資料湖泊
Earned Jun 15, 2023 EDT
開始使用 Looker
Earned Jun 14, 2023 EDT