Put It All Together: Prepare for a Cloud Data Analyst Job
Earned May 30, 2024 EDT
大型語言模型簡介
Earned Apr 29, 2024 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned Mar 26, 2024 EDT
Baseline: Deploy & Develop
Earned Mar 12, 2024 EDT
Google Cloud 中的 Kubernetes
Earned Mar 8, 2024 EST
在 Google Cloud 使用機器學習 API
Earned Mar 6, 2024 EST
基本概念：資料、機器學習和 AI
Earned Feb 29, 2024 EST
機器學習簡介：語言處理
Earned Feb 27, 2024 EST
Google Developer Essentials
Earned Feb 27, 2024 EST
使用 BigQuery 進行機器學習
Earned Feb 23, 2024 EST
DEPRECATED BigQuery for Data Warehousing
Earned Feb 23, 2024 EST
瞭解 Google Cloud 費用
Earned Feb 19, 2024 EST
Intro to ML: Image Processing
Earned Feb 19, 2024 EST
Developing a Google SRE Culture
Earned Feb 19, 2024 EST
Google Cloud 基礎知識：核心基礎架構
Earned Feb 18, 2024 EST
安全性與身分識別基礎知識
Earned Feb 15, 2024 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Feb 14, 2024 EST
Google Cloud 運算的基本概念：Cloud 運算基礎知識
Earned Feb 14, 2024 EST
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned Feb 13, 2024 EST
基本概念：基礎架構
Earned Feb 12, 2024 EST
在 Google Cloud 儲存、處理與管理資料 - 控制台
Earned Feb 12, 2024 EST
Data Catalog Fundamentals
Earned Feb 6, 2024 EST
實現 Cloud Storage 和數據保護解決方案
Earned Jan 30, 2024 EST
這是 Google Cloud Data Analytics 專業證書五堂課程中的第五堂。在本課程中，您將結合第一到第四堂課程的基礎知識和技能，並活用所學，透過專題實作呈現完整的資料生命週期。您將練習使用雲端式工具，有效率地取得、儲存、處理、分析資料，並以圖表呈現及傳達資料洞察結果。本課程結束後，您將完成一項專案，證明自己精通於有效整理多個來源的資料、向不同相關人士說明解決方案，以及運用雲端式軟體將資料洞察結果以圖表呈現。此外，您還會更新履歷，並練習面試技巧，為應徵和面試做好準備。
完成「監控及管理 Google Cloud 資源」技能徽章入門課程，即可證明您具備下列技能：授予及撤銷 IAM 權限； 安裝 Monitoring 和 Logging 代理程式；建立、部署及測試事件導向的 Cloud Run 函式。
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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，可協助您透過 Google Cloud 使用 Google 產品和服務，開發、測試、部署及管理應用程式。有了 Gemini 的協助，您會學到如何開發和建構網頁應用程式、修正應用程式中的錯誤、開發測試及查詢資料。在實作研究室中，您也會體驗到 Gemini 如何改良軟體開發生命週期 (SDLC)。
Duet AI 已更名為 Gemini，這是我們的新一代模型。
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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.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
This is the fifth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll combine and apply the foundational knowledge and skills from courses 1-4 in a hands-on Capstone project that focuses on the full data lifecycle project. You’ll practice using cloud-based tools to acquire, store, process, analyze, visualize, and communicate data insights effectively. By the end of the course, you’ll have completed a project demonstrating their proficiency in effectively structuring data from multiple sources, presenting solutions to varied stakeholders, and visualizing data insights using cloud-based software. You’ll also update your resume and practice interview techniques to help prepare for applying and interviewing for jobs.
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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。
In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
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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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完成「在 Google Cloud 使用機器學習 API」課程，即可獲得進階技能徽章。本課程說明以下機器學習和 AI 技術的基本功能： Cloud Vision API、Cloud Translation API 和 Cloud Natural Language API。
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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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大家都知道，機器學習是發展最快的科技領域之一， 而 Google Cloud Platform 在這方面功不可沒。 GCP 提供多種 API，凡是與機器學習相關的任務，幾乎都能處理。您將在本入門課程的 實驗室，實際演練機器學習技術 在語言處理方面的應用，學會如何從文中擷取實體資訊、 執行情緒和語法分析，並使用 Speech-to-Text API 轉錄語音。
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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
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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本課程最適合從事科技或金融職務， 且負責管理 Google Cloud 費用的人士修習。您將學習如何設定帳單帳戶、 整理資源及管理帳單存取權限。 在實作實驗室，您會瞭解如何查看帳單、使用 BigQuery 或 Google 試算表分析帳單資料， 以及使用 Data Studio 建立自訂的帳單資訊主頁。如需影片提及的參考資源連結， 請參閱其他資源文件。
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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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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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Google Cloud 的服務在安全上絕不妥協， 因此開發了專用工具，確保所有專案安全無虞， 使用者也能妥善管理身分識別機制。在這堂入門課程中，您會實際使用 Google Cloud 的 Identity and Access Management (IAM) 服務， 練習管理使用者和虛擬機器帳戶。您將 佈建虛擬私有雲和 VPN 來熟悉網路安全功能，並瞭解有哪些工具 可防範資安威脅和資料遺失。
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. 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.
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Google Cloud 運算基本概念課程，適合幾乎沒有雲端運算背景或經驗的學員。這些課程會說明雲端運算基本知識、大數據和機器學習的核心概念，以及 Google Cloud 的角色和定位。完成這一系列課程後，學員將能夠闡述這些概念並展示實用技能。學員應依以下順序完成課程：
1. Google Cloud 運算的基本概念：Cloud 運算基礎知識
2. Google Cloud 運算的基本概念：Google Cloud 基礎架構
3. Google Cloud 運算的基本概念：Google Cloud 的網路與安全性
4. Google Cloud 運算的基本概念：Google Cloud 中的資料、機器學習和 AI
第一門課會概略說明雲端運算、Google Cloud 的使用方式，以及不同的運算選項。
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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.
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如果您是剛起步的雲端開發人員， 想在 Google Cloud Essentials 外獲得更多實作經驗，歡迎參加本課程。您將透過實作實驗室， 深入瞭解 Cloud Storage 和其他重要應用程式服務，例如： Monitoring 和 Cloud Functions。您將習得 在任何 Google Cloud 專案都適用的寶貴技能。
Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.
綜合應用：為 Cloud 資料分析師工作做準備
Earned Oct 28, 2025 EDT
在 Google Cloud 儲存、處理與管理資料 - 指令列
Earned Apr 1, 2025 EDT
搭配使用 API 和 Cloud Storage
Earned Apr 1, 2025 EDT
使用 Google API 分析語音和語言
Earned Mar 27, 2025 EDT
使用 Dataplex 整理及管理資料
Earned Mar 24, 2025 EDT
在 Google App Engine 上部署及管理應用程式
Earned Mar 24, 2025 EDT
監控及管理 Google Cloud 資源
Earned Feb 4, 2025 EST
使用 Gemini：端對端 SDLC
Earned Oct 7, 2024 EDT
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Sep 15, 2024 EDT
在 Google Cloud 實作 Cloud 安全防護措施：基礎知識
Earned Jul 8, 2024 EDT
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned May 30, 2024 EDT
大型語言模型簡介
Earned Apr 29, 2024 EDT
在 Google Cloud 部署 Kubernetes 應用程式
Earned Mar 26, 2024 EDT
Baseline: Deploy & Develop
Earned Mar 12, 2024 EDT
Google Cloud 中的 Kubernetes
Earned Mar 8, 2024 EST
在 Google Cloud 使用機器學習 API
Earned Mar 6, 2024 EST
基本概念：資料、機器學習和 AI
Earned Feb 29, 2024 EST
機器學習簡介：語言處理
Earned Feb 27, 2024 EST
Google Developer Essentials
Earned Feb 27, 2024 EST
使用 BigQuery 進行機器學習
Earned Feb 23, 2024 EST
DEPRECATED BigQuery for Data Warehousing
Earned Feb 23, 2024 EST
瞭解 Google Cloud 費用
Earned Feb 19, 2024 EST
Intro to ML: Image Processing
Earned Feb 19, 2024 EST
Developing a Google SRE Culture
Earned Feb 19, 2024 EST
Google Cloud 基礎知識：核心基礎架構
Earned Feb 18, 2024 EST
安全性與身分識別基礎知識
Earned Feb 15, 2024 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned Feb 14, 2024 EST
Google Cloud 運算的基本概念：Cloud 運算基礎知識
Earned Feb 14, 2024 EST
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned Feb 13, 2024 EST
基本概念：基礎架構
Earned Feb 12, 2024 EST
在 Google Cloud 儲存、處理與管理資料 - 控制台
Earned Feb 12, 2024 EST
Data Catalog Fundamentals
Earned Feb 6, 2024 EST
實現 Cloud Storage 和數據保護解決方案
Earned Jan 30, 2024 EST