使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL
Earned Oct 14, 2025 EDT
Select a Google Cloud Database for Your Applications
Earned Oct 12, 2025 EDT
Build a Certification Study Guide: PMLE
Earned Oct 2, 2025 EDT
運用 Cloud Run 開發無伺服器應用程式
Earned Mar 22, 2025 EDT
在 Google Cloud 設定應用程式開發環境
Earned Mar 9, 2025 EDT
使用 BigQuery 進行機器學習
Earned Mar 8, 2025 EST
機器學習簡介：語言處理
Earned Mar 8, 2025 EST
Google Cloud 的 AI 和機器學習服務簡介
Earned Mar 7, 2025 EST
在 Compute Engine 導入 Cloud Load Balancing
Earned Mar 7, 2025 EST
Google Cloud 基礎知識：核心基礎架構
Earned Mar 3, 2025 EST
Google Cloud 必備知識
Earned Mar 3, 2025 EST
基本概念：基礎架構
Earned Mar 3, 2025 EST
使用 BigQuery ML 為預測模型進行資料工程
Earned Mar 3, 2025 EST
運用 BigQuery ML 建立機器學習模型
Earned Mar 3, 2025 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Mar 2, 2025 EST
安全性與身分識別基礎知識
Earned Mar 1, 2025 EST
使用 Natural Language API 分析情緒
Earned Feb 26, 2025 EST
使用 Google API 分析語音和語言
Earned Feb 17, 2025 EST
在 Google Cloud 使用機器學習 API
Earned Feb 17, 2025 EST
In this course, you learn about containers and how to build, and package container images. The content in this course includes best practices for creating and securing containers, and provides an introduction to Cloud Run and Google Kubernetes Engine for application developers.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Cloud Architect certification exam.
You'll review NotebookLM features, create a notebook in NotebookLM, and learn how to use a study guide to practice for a certification exam.
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In this course, you learn about Cloud Run functions, Google's serverless, fully-managed functions as a service (FaaS) product that lets you implement single-purpose function code that reponds to HTTP requests and events from your cloud infrastructure.
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This course introduces you to event-based applications and teaches you how to use service orchestration and choreography to coordinate microservices. Using lectures and hands-on labs, you learn how to use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to build microservices applications on Google Cloud.
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這堂課程可讓參加人員瞭解如何使用確實有效的設計模式，在 Google Cloud 中打造相當可靠且效率卓越的解決方案。這堂課程接續了「設定 Google Compute Engine 架構」或「設定 Google Kubernetes Engine 架構」課程的內容，並假設參加人員曾實際運用上述任一課程涵蓋的技術。這堂課程結合了簡報、設計活動和實作研究室，可讓參加人員瞭解如何定義業務和技術需求，並在兩者之間取得平衡，設計出相當可靠、可用性高、安全又符合成本效益的 Google Cloud 部署項目。
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完成使用 Google Cloud Managed Service for Prometheus 監控環境技能徽章課程，學習透過 Google Cloud Managed Service for Prometheus 監控 Kubernetes，即可獲得技能徽章。
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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Gemini Cloud Assist investigations is an AI-enabled tool for iterative troubleshooting in Google Cloud environments, and aims to help users troubleshoot common issues to find the root cause of problems that may occur when using Google Cloud services.
This course equips DevOps, SRE, and platform engineers with the skills to effectively use Gemini Cloud Assist investigations for streamlined troubleshooting of Google Cloud services. The training focuses on foundational knowledge of Gemini Cloud Assist investigations, with the intent to reduce troubleshooting time and enhance overall operational efficiency for users of Google Cloud.
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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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Welcome to the sixth course in our Networking and Google Cloud series, Hybrid and Multicloud. The first module will walk you through various cloud connectivity options, with a deep dive into Cloud Interconnect, exploring its different types and functionalities. In the second module, we'll cover Cloud VPN, discussing its implementation, high availability, VPN topologies, and the Network Connectivity Center for streamline management. By the end of this course, you will be able to explain the different connectivity options available to extend your on-premises and other cloud networks to Google Cloud, and analyze the suitability of different Google Cloud hybrid and multicloud connectivity services for specific use cases.
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Welcome to the third course of the "Networking in Google Cloud" series: Network Architecture!
In this course, you will explore the fundamentals of designing efficient and scalable network architectures within Google Cloud.
In the first module, Introduction to Network Architecture, we'll start by introducing you to the core components and concepts of network architecture, including subnets, routes, firewalls, and load balancing.
Then in the second module, network topologies, we'll dive into various network topologies commonly used in Google Cloud, discussing their strengths, and weaknesses.
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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.
Migrating between fundamentally incompatible database engines—such as moving from commercial legacy systems to cloud-native AlloyDB— is a major architectural shift. Architect this heterogeneous database migration using the DMS conversion workspace and Gemini to refactor database logic and stored procedures. Build reliable, rule-based pipelines with DMS mapping rules and ensure data fidelity via the Data Validation Tool (DVT). Develop the skills to systematically guide an enterprise migration from assessment to production cutover.
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Orchestrate the complete execution of a homogeneous database migration to Google Cloud. In this course, you will see how to use the Database Migration Service (DMS) for live replication and the Data Validation Tool (DVT) to certify data integrity. You will learn the engine specific steps for preparing sources like PostgreSQL and SQL Server for a move to an equivalent managed target such as AlloyDB and Cloud SQL. You will leave ready to oversee a seamless, validated migration, ensuring a fast, reliable, and low risk transition to a managed Google Cloud database.
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Ready to move your databases to Google Cloud? This course provides the strategy. Learn to evaluate business drivers to overcome high on-premise costs and vendor lock-in. Use Migration Center to discover assets, analyze TCO, and build a phased wave plan. You’ll learn to choose the right migration path and identify the right Google Cloud solutions for your workloads. You'll leave with a data-driven business case and a clear roadmap, ready to win executive buy-in and lead a successful migration.
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完成「在 Google Cloud 使用 Terraform 建構基礎架構」技能徽章中階課程， 即可證明自己具備下列知識與技能：使用 Terraform 的基礎架構即程式碼 (IaC) 原則、運用 Terraform 設定佈建及管理 Google Cloud 資源、有效管理狀態 (本機和遠端)，以及將 Terraform 程式碼模組化，以利重複使用和管理。
Welcome to Observability in Google Cloud, the second part of a two-part course series. It is suggested that you complete part 1, Logging and Monitoring in Google Cloud, prior to taking this course.
This course is all about application performance management tools, including Error Reporting, Cloud Trace, and Cloud Profiler.
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Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.
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This course introduces the Cloud Run serverless platform for running applications.
In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle.
You learn about service identities, how to control access to services, and how to develop and test your
application locally before deploying it to Cloud Run. The course also teaches you how to integrate
with other services on Google Cloud so you can build full-featured applications.
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歡迎參加「開始使用 Google Kubernetes Engine」課程。Kubernetes 是位於應用程式和硬體基礎架構之間的軟體層。如果您對這項技術感興趣，這堂課程可以滿足您的需求。有了 Google Kubernetes Engine，您就能在 Google Cloud 中以代管服務的形式使用 Kubernetes。
本課程的目標在於介紹 Google Kubernetes Engine (常簡稱為 GKE) 的基本概念，以及如何將應用程式容器化，以便在 Google Cloud 中執行。課程首先會初步介紹 Google Cloud，隨後簡介容器、Kubernetes、Kubernetes 架構和 Kubernetes 作業。
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這堂隨選密集課程會向參加人員說明 Google Cloud 提供的全方位彈性基礎架構和平台服務。這堂課結合了視訊講座、示範和實作研究室，可讓參加人員探索及部署解決方案元素，包括安全地建立互連網路、負載平衡、自動調度資源、基礎架構自動化，以及代管服務。
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在 「Google Kubernetes Engine 架構：基礎知識」的課程中，您將復習 Google Cloud 的配置和原則，接著是建立和管理軟體容器簡介和 Kubernetes 架構簡介。
這是 Google Kubernetes Engine 架構系列中的第一項課程。完成此課程後，請註冊 Google Kubernetes Engine 架構：工作負載課程。
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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.
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Learn how to use NotebookLM to create a personalized study guide for the Associate Cloud Engineer certification exam.
You'll review NotebookLM features, create a notebook in NotebookLM, and learn how to use a study guide to practice for a certification exam.
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This quest introduces you to Vault and teaches you how to secure, store, and tightly control access to tokens, passwords, certificates, and encryption keys to protect secrets and other sensitive data.
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這堂課程會介紹 AI 搜尋技術、工具和應用程式。主題涵蓋使用向量嵌入執行語意搜尋；結合語意和關鍵字做法的混合型搜尋機制；以及運用檢索增強生成 (RAG) 技術建構有基準的 AI 代理，盡可能減少 AI 幻覺。您可以實際使用 Vertex AI Vector Search，打造智慧型搜尋引擎。
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In this course, you learn the fundamentals of application development on Google Cloud. You learn best practices for cloud applications, and how to select compute and data options to match your application use cases. You're introduced to generative AI and how it's used to help build applications. You learn about authentication and authorization, application deployment, continuous integration and delivery, and monitoring and performance tuning for your applications running in Google Cloud. Using lectures and hands-on labs, you learn how to get started building and running applications on Google Cloud.
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完成「建構安全的 Google Cloud 網路」課程，即可獲得技能徽章。本課程將說明多項網路相關 資源，協助您在 Google Cloud 建構、調度資源和保護應用程式。
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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。這些課程會概略介紹雲端基礎知識、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，學員將能闡述這些概念並展示實用技能。學員需依序完成課程：
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
本系列的最後一堂課回顧了代管大數據服務、機器學習與這項技術的價值，以及如何獲得技能徽章，進一步展示您的 Google Cloud 技能。
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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
第三門課涵蓋雲端自動化和管理工具，以及建構安全網路。
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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。這些課程會概略介紹雲端基礎知識、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，學員將能闡述這些概念並展示實用技能。學員需依序完成課程：
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
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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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這堂隨選密集課程會向參加人員說明 Google Cloud 提供的全方位彈性基礎架構和平台服務，並將重點放在 Compute Engine。這堂課程結合了視訊講座、示範和實作研究室，可讓參加人員探索及部署解決方案元素，例如網路、系統和應用程式服務等基礎架構元件。另外，這堂課也會介紹如何部署實用的解決方案，包括客戶提供的加密金鑰、安全性和存取權管理機制、配額與帳單，以及資源監控功能。
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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.
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這堂隨選密集課程會向參加人員說明 Google Cloud 提供的全方位彈性基礎架構和平台服務，尤其側重於 Compute Engine。這堂課程結合了視訊講座、示範和實作研究室，可讓參加人員探索及部署解決方案元素，例如網路、虛擬機器和應用程式服務等基礎架構元件。您會瞭解如何透過控制台和 Cloud Shell 使用 Google Cloud。另外，您也能瞭解雲端架構師的職責、基礎架構設計方法，以及具備虛擬私有雲 (VPC)、專案、網路、子網路、IP 位址、路徑和防火牆規則的虛擬網路設定。
This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to Google Cloud while taking advantage of various services.
This course covers how to move on-premises, enterprise databases like SQL Server to Google Cloud (Compute Engine and Cloud SQL) and Oracle to Google Cloud bare metal.
完成 使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL 技能徽章入門課程，證明您具備下列技能： 使用「資料庫遷移服務」中各種可用的工作類型和連線選項， 將 MySQL 資料遷移至 Cloud SQL，以及在執行「資料庫遷移服務」工作時 遷移 MySQL 使用者資料。
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In this course, you learn to analyze and choose the right database for your needs, to effectively develop applications on Google Cloud. You explore relational and NoSQL databases, dive into Cloud SQL, AlloyDB, and Spanner, and learn how to align database strengths with your application requirements, including those of generative AI. Gain hands-on experience configuring Vector Search and migrating applications to the cloud.
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Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.
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完成 運用 Cloud Run 開發無伺服器應用程式 技能徽章中階課程， 即可證明您具備下列技能：整合 Cloud Run 和 Cloud Storage 以管理資料、 使用 Cloud Run 和 Pub/Sub 架構可復原的非同步系統、 使用 Cloud Run 建構 REST API 閘道，以及在 Cloud Run 建構及部署服務。
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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。
「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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在這堂入門課程，您將實際練習使用 Google Cloud 的基礎工具和服務。本課程包含可選擇觀賞的影片， 針對實驗室涵蓋的概念提供更多背景資訊，協助您複習。「Google Cloud 必備知識」 是適合 Google Cloud 學員的第一堂課， 即使您尚未學習或不熟悉雲端知識， 也能從這堂課獲得實務經驗，並應用於第一項 Google Cloud 專案。不管是撰寫 Cloud Shell 指令 和部署第一部虛擬機器，還是在 Kubernetes Engine 或透過負載平衡執行應用程式， 「Google Cloud 必備知識」都是認識平台基本功能的最佳入門資源。
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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。
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完成使用 BigQuery ML 為預測模型進行資料工程技能徽章中階課程， 即可證明自己具備下列知識與技能：運用 Dataprep by Trifacta 建構連至 BigQuery 的資料轉換 pipeline； 使用 Cloud Storage、Dataflow 和 BigQuery 建構「擷取、轉換及載入」(ETL) 工作負載， 以及使用 BigQuery ML 建構機器學習模型。
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完成「運用 BigQuery ML 建立機器學習模型」技能徽章中階課程，即可證明您具備下列技能： 可使用 BigQuery ML 建立及評估機器學習模型，並根據資料進行預測。
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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 Managed Service for Apache Spark 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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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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完成「使用 Natural Language API 分析情緒」任務， 瞭解 API 如何從文字判斷情緒， 即可獲得技能徽章。
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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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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。
Developing Containerized Applications on Google Cloud
Earned Jun 26, 2026 EDT
Build a Certification Study Guide: PCA Exam Prep
Earned Jun 26, 2026 EDT
Developing Applications with Cloud Run Functions on Google Cloud
Earned Jun 8, 2026 EDT
Service Orchestration and Choreography on Google Cloud
Earned Jun 8, 2026 EDT
可靠的 Google Cloud 基礎架構：設計與程序
Earned Jun 7, 2026 EDT
使用 Google Cloud Managed Service for Prometheus 監控環境
Earned Jun 6, 2026 EDT
透過 Google Cloud Observability 監控及記錄系統狀態
Earned Jun 5, 2026 EDT
在 Google Cloud 環境導入 DevSecOps 做法
Earned Jun 4, 2026 EDT
在 Google Cloud 實作 DevOps 工作流程
Earned Jun 4, 2026 EDT
Getting Started with Terraform for Google Cloud
Earned Jun 4, 2026 EDT
Troubleshooting with AI Using Cloud Assist Investigations
Earned Jun 4, 2026 EDT
Developing a Google SRE Culture
Earned Jun 4, 2026 EDT
Networking in Google Cloud: Hybrid and Multicloud
Earned Jun 2, 2026 EDT
Networking in Google Cloud: Network Architecture
Earned Jun 2, 2026 EDT
Networking in Google Cloud: Fundamentals
Earned Jun 2, 2026 EDT
透過 Gemini 運用 AI 功能管理資料庫
Earned Jun 1, 2026 EDT
Google Cloud Database Migrations: Heterogeneous
Earned Jun 1, 2026 EDT
Google Cloud Database Migrations: Homogeneous
Earned Jun 1, 2026 EDT
Google Cloud Database Migrations: Strategy
Earned Jun 1, 2026 EDT
在 Google Cloud 使用 Terraform 建構基礎架構
Earned Jun 1, 2026 EDT
建立 Google Cloud 網路
Earned Jun 1, 2026 EDT
Observability in Google Cloud
Earned May 29, 2026 EDT
Logging and Monitoring in Google Cloud
Earned May 29, 2026 EDT
Developing Applications with Cloud Run on Google Cloud: Fundamentals
Earned May 29, 2026 EDT
開始使用 Google Kubernetes Engine
Earned May 5, 2026 EDT
彈性的 Google Cloud 基礎架構：資源調度與自動化
Earned May 5, 2026 EDT
Architecting with Google Kubernetes Engine: Foundations - 繁體中文
Earned Apr 30, 2026 EDT
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Apr 23, 2026 EDT
Build a Certification Study Guide: ACE Exam Prep
Earned Apr 23, 2026 EDT
Using Vault on Google Cloud
Earned Apr 7, 2026 EDT
Vector Search 和嵌入
Earned Apr 6, 2026 EDT
Developing Applications with Google Cloud: Foundations
Earned Mar 30, 2026 EDT
建構安全的 Google Cloud 網路
Earned Mar 3, 2026 EST
Google Cloud 運算的基本概念：Google Cloud 中的資料、機器學習和 AI
Earned Nov 30, 2025 EST
Google Cloud 運算的基本概念：Google Cloud 的網路與安全性
Earned Nov 30, 2025 EST
Google Cloud 運算的基本概念：Google Cloud 基礎架構
Earned Nov 30, 2025 EST
Google Cloud 運算的基本概念：Cloud 運算基礎知識
Earned Nov 30, 2025 EST
重要的 Google Cloud 基礎架構：核心服務
Earned Nov 30, 2025 EST
Google Developer Essentials
Earned Nov 30, 2025 EST
重要的 Google Cloud 基礎架構：基本概念
Earned Nov 6, 2025 EST
實現事件驅動的即時訊息與自動化工作流
Earned Oct 19, 2025 EDT
建立及管理 AlloyDB 執行個體
Earned Oct 18, 2025 EDT
建立及管理 Bigtable 執行個體
Earned Oct 16, 2025 EDT
建立及管理 Cloud Spanner 執行個體
Earned Oct 16, 2025 EDT
[DEPRECATED] Enterprise Database Migration
Earned Oct 15, 2025 EDT
建立及管理 PostgreSQL 適用的 Cloud SQL 執行個體
Earned Oct 14, 2025 EDT
使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL
Earned Oct 14, 2025 EDT
Select a Google Cloud Database for Your Applications
Earned Oct 12, 2025 EDT
Build a Certification Study Guide: PMLE
Earned Oct 2, 2025 EDT
運用 Cloud Run 開發無伺服器應用程式
Earned Mar 22, 2025 EDT
在 Google Cloud 設定應用程式開發環境
Earned Mar 9, 2025 EDT
使用 BigQuery 進行機器學習
Earned Mar 8, 2025 EST
機器學習簡介：語言處理
Earned Mar 8, 2025 EST
Google Cloud 的 AI 和機器學習服務簡介
Earned Mar 7, 2025 EST
在 Compute Engine 導入 Cloud Load Balancing
Earned Mar 7, 2025 EST
Google Cloud 基礎知識：核心基礎架構
Earned Mar 3, 2025 EST
Google Cloud 必備知識
Earned Mar 3, 2025 EST
基本概念：基礎架構
Earned Mar 3, 2025 EST
使用 BigQuery ML 為預測模型進行資料工程
Earned Mar 3, 2025 EST
運用 BigQuery ML 建立機器學習模型
Earned Mar 3, 2025 EST
在 Google Cloud 為機器學習 API 準備資料
Earned Mar 2, 2025 EST
安全性與身分識別基礎知識
Earned Mar 1, 2025 EST
使用 Natural Language API 分析情緒
Earned Feb 26, 2025 EST
使用 Google API 分析語音和語言
Earned Feb 17, 2025 EST
在 Google Cloud 使用機器學習 API
Earned Feb 17, 2025 EST