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Massimo Asuni

Member since 2024

Diamond League

197637 points
Implement Cloud Next Generation Firewall Earned Oct 16, 2026 EDT
Secure GKE with Cloud Next Generation Firewall Earned Oct 16, 2026 EDT
Design and Implement Network Security in Google Cloud Earned Oct 15, 2026 EDT
Security Best Practices in Google Cloud Earned Oct 14, 2026 EDT
使用 Agent Development Kit (ADK) 打造您的第一個 AI 代理 Earned Oct 13, 2026 EDT
[CEPF L300 Course]: Application Modernization Earned Oct 12, 2026 EDT
Manage Scalable Workloads in GKE Earned Oct 6, 2026 EDT
在 Cloud Storage 建立串流資料湖泊 Earned Oct 5, 2026 EDT
[CEPF L300 Course]: Infrastructure Modernization Earned Oct 1, 2026 EDT
MLOps with Agent Platform: Manage Features Earned Sep 2, 2026 EDT
在 Google Cloud 實作 CI/CD 管道 Earned Sep 1, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model Earned Aug 31, 2026 EDT
安全性與身分識別基礎知識 Earned Aug 31, 2026 EDT
Select a Google Cloud Database for Your Applications Earned Aug 31, 2026 EDT
Developing Applications with Cloud Run Functions on Google Cloud Earned Aug 28, 2026 EDT
在 Google Cloud 部署 Kubernetes 應用程式 Earned Aug 28, 2026 EDT
設定組織專用的 Gemini Code Assist Earned Aug 27, 2026 EDT
使用 Cloud Run 部署及擴充 AI 模型 Earned Aug 27, 2026 EDT
透過直覺式程式開發和 MCP,建構智慧雲端應用程式 Earned Aug 27, 2026 EDT
搭配多代理系統使用 Agent Skills Earned Aug 26, 2026 EDT
使用 ADK 和 MCP 建構協作式多代理系統 Earned Aug 26, 2026 EDT
運用 Gemini Code Assist 簡化應用程式開發作業 Earned Aug 25, 2026 EDT
使用 Gemini Code Assist 開始開發應用程式 Earned Aug 21, 2026 EDT
雲端架構:設計、實作與管理 Earned Aug 20, 2026 EDT
使用企業資料庫建構 AI 代理 Earned Aug 19, 2026 EDT
AgentOps:在 Google Cloud 實作 AI 代理 Earned Aug 19, 2026 EDT
Orchestrate Workflows with the Data Agent Kit Earned Aug 19, 2026 EDT
Build Agent Skills with Google Earned Aug 19, 2026 EDT
代理式策略:探索、設計與原型建立 Earned Aug 19, 2026 EDT
管理 AI 代理的記憶與狀態 Earned Aug 18, 2026 EDT
與 Google Antigravity 一同啟航:運用 AI 打造電玩遊戲 Earned Aug 18, 2026 EDT
瞭解 Google Cloud 代理 Earned Aug 18, 2026 EDT
Gemini Enterprise 簡介 Earned Aug 18, 2026 EDT
在 Google Cloud 實作 Cloud 安全防護措施:基礎知識 Earned Aug 17, 2026 EDT
在 Google Cloud 使用 Terraform 建構基礎架構 Earned Aug 13, 2026 EDT
Govern Agent Access with Gemini platform Earned Aug 7, 2026 EDT
Secure your Agents with Gemini Enterprise Agent Platform Earned Aug 7, 2026 EDT
Govern agents with Agent Gateway, Agent Registry, and Policies Earned Aug 7, 2026 EDT
Improve Agent Search findings on Gemini platform Earned Aug 6, 2026 EDT
Use a Third-Party Identity Provider with Workforce Identity Federation Earned Aug 6, 2026 EDT
Deploy Gemini to Transform Enterprises Earned Aug 6, 2026 EDT
Plan Change Management for Gemini Deployments Earned Aug 5, 2026 EDT
Evaluate and Improve Agent Development Kit Agents Earned Aug 5, 2026 EDT
Cost Estimation and Optimization for Agentic Solutions Earned Aug 5, 2026 EDT
Hill Climb Generative and Agentic Systems Earned Aug 5, 2026 EDT
Upgrade to the Latest Gemini Models Earned Aug 5, 2026 EDT
Evaluate Agents on Gemini Enterprise Agent Platform Earned Aug 5, 2026 EDT
Evaluate Generative and Agentic Systems Earned Aug 5, 2026 EDT
Craft ADK Agents with Persistent Memories Earned Aug 5, 2026 EDT
Build Enterprise Agents with Code Execution on Gemini platform Earned Aug 4, 2026 EDT
Build Agents with the Agent Development Kit Earned Aug 3, 2026 EDT
Accelerate Development with Antigravity Earned Aug 3, 2026 EDT
Build with the Managed Agents API on Gemini platform Earned Aug 3, 2026 EDT
Accelerate Agent Development with Antigravity and Agents CLI Earned Aug 3, 2026 EDT
Add Agents to Gemini Earned Jul 10, 2026 EDT
Deploy an Agent with Agent Development Kit (ADK) Earned Jul 7, 2026 EDT
運用 Gemini Enterprise Agent Platform 部署多代理系統 Earned Jul 7, 2026 EDT
Extend Gemini with controlled generation and Tool use Earned Jul 7, 2026 EDT
Deploy Gemini with Workspace Data Sources and Model Armor Earned Jul 6, 2026 EDT
運用工具讓 AI 代理具備所要能力 Earned Jun 1, 2026 EDT
AI 代理行為最佳化調整 Earned Jun 1, 2026 EDT
使用 Agent Development Kit (ADK) 建造 AI 代理:工程設計 Earned Jun 1, 2026 EDT
部署多代理架構 Earned Jun 1, 2026 EDT
部署您的第一個代理 Earned Jun 1, 2026 EDT
在正式環境建構及部署代理 Earned Jun 1, 2026 EDT
運用 Gemini Enterprise 自動調度管理多代理工作流程 Earned Jun 1, 2026 EDT
以人為本的 AI Earned Jun 1, 2026 EDT
在 Google Cloud 運用生成式 AI 翻新網站 Earned May 25, 2026 EDT
[DEPRECATED] Custom Search with Embeddings in Vertex AI Earned May 15, 2026 EDT
Build search and recommendations applications with AI Applications Earned May 14, 2026 EDT
使用 BigQuery ML 為預測模型進行資料工程 Earned May 4, 2026 EDT
[DEPRECATED] Generative AI Fundamentals Earned Apr 29, 2026 EDT
在 Google Cloud 打造生成式 AI 應用程式 Earned Apr 29, 2026 EDT
使用 Gemini 多模態功能和多模態 RAG 檢查複合型文件 Earned Apr 28, 2026 EDT
Vector Search 和嵌入 Earned Apr 27, 2026 EDT
[Depricated] Build, Train and Deploy ML Models with Keras on Google Cloud Earned Apr 22, 2026 EDT
[DEPRECATED] Feature Engineering Earned Apr 22, 2026 EDT
Introduction to Gemini Enterprise for Customer Experience Earned Apr 10, 2026 EDT
Generative AI for Business Leaders Earned Apr 7, 2026 EDT
Build and Deploy Customer Experience Agents Earned Apr 3, 2026 EDT
Working with Notebooks in Vertex AI Earned Mar 31, 2026 EDT
Model Armor:保護您部署的 AI 應用程式 Earned Feb 18, 2026 EST
透過 Gemini in BigQuery 提升工作效率 Earned Feb 18, 2026 EST
在 BigQuery 使用 Gemini 模型 Earned Feb 18, 2026 EST
透過 BigQuery 機器學習執行推論作業 Earned Feb 17, 2026 EST
運用 BigQuery ML 建立機器學習模型 Earned Feb 17, 2026 EST
AI Boost Bites:個人意見回饋代理 Earned Feb 17, 2026 EST
Build a Certification Study Guide: PMLE Earned Feb 2, 2026 EST
AI 基礎架構:部署類型 Earned Dec 18, 2025 EST
Google Security Operations - Deep Dive Earned Nov 12, 2025 EST
[Deprecated]Google Security Operations - Fundamentals Earned Nov 11, 2025 EST
AI 基礎架構:Cloud TPU Earned Nov 10, 2025 EST
AI 基礎架構:Cloud GPU Earned Nov 7, 2025 EST
AI 基礎架構:AI Hypercomputer 簡介 Earned Nov 7, 2025 EST
Introduction to reCAPTCHA Earned Nov 7, 2025 EST
Manage Security in Google Cloud Earned Sep 2, 2025 EDT
Networking in Google Cloud: Hybrid and Multicloud Earned Aug 25, 2025 EDT
Networking in Google Cloud: Load Balancing Earned Aug 4, 2025 EDT
Networking in Google Cloud: Network Security Earned Aug 4, 2025 EDT
Networking in Google Cloud: Network Architecture Earned Aug 4, 2025 EDT
Networking in Google Cloud: Routing and Addressing Earned Aug 1, 2025 EDT
Networking in Google Cloud: Fundamentals Earned Aug 1, 2025 EDT
Build a Certification Study Guide: PCSE Exam Prep Earned Jul 30, 2025 EDT
GCC Tech Learning Packs - TPU/GPU - SME Academy Earned Jul 28, 2025 EDT
透過 Vertex AI 建構及部署機器學習解決方案 Earned Jul 28, 2025 EDT
AI 世界的安全防護簡介 Earned Jul 23, 2025 EDT
開發人員的負責任 AI 技術:隱私權與安全性 Earned Jul 22, 2025 EDT
開發人員的負責任 AI 技術:可解釋性與透明度 Earned Jul 22, 2025 EDT
開發人員的負責任 AI 技術:公平性與偏誤 Earned Jul 22, 2025 EDT
機器學習運作 (MLOps) 與 Vertex AI:模型評估 Earned Jun 30, 2025 EDT
生成式 AI 適用的機器學習運作 (MLOps) Earned Jun 30, 2025 EDT
[DEPRECATED] Modernizing Retail and Ecommerce Solutions with Google Cloud Earned Jun 9, 2025 EDT
Vertex AI Search for Commerce Earned May 30, 2025 EDT
Serverless Data Processing with Dataflow: Foundations Earned May 30, 2025 EDT
Conversational AI on Vertex AI and Dialogflow CX Earned May 26, 2025 EDT
生成式 AI 代理:實現組織轉型 Earned May 23, 2025 EDT
生成式 AI 應用程式:徹底改變工作方式 Earned May 22, 2025 EDT
生成式 AI:掌握幕後技術與環境 Earned May 21, 2025 EDT
生成式 AI:瞭解基礎概念 Earned May 16, 2025 EDT
生成式 AI:不只是聊天機器人 Earned May 15, 2025 EDT
建立及管理 AlloyDB 執行個體 Earned May 14, 2025 EDT
Agentspace Implementation Bootcamp 2025 On-Demand Earned May 9, 2025 EDT
部署與管理 Apigee X Earned May 5, 2025 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned May 2, 2025 EDT
Google Workspace 疑難排解 Earned Apr 30, 2025 EDT
Google Workspace 資料治理 Earned Apr 30, 2025 EDT
Developing Applications with Cloud Run on Google Cloud: Fundamentals Earned Apr 22, 2025 EDT
Google Workspace 核心服務 Earned Apr 7, 2025 EDT
Google Workspace 安全性 Earned Mar 25, 2025 EDT
[CEPF L300 Course]: Infrastructure Modernization Earned Mar 21, 2025 EDT
[DEPRECATED] Deploy Google Agentspace Earned Mar 4, 2025 EST
運用 Gemini Enterprise 加速知識交流 Earned Mar 4, 2025 EST
Google Workspace 的使用者和資源管理功能 Earned Feb 26, 2025 EST
DEPRECATED Planning for a Google Workspace Deployment Earned Feb 24, 2025 EST
API Security with the Apigee API Platform Earned Feb 10, 2025 EST
在 Compute Engine 導入 Cloud Load Balancing Earned Jan 13, 2025 EST
建構適用於 AWS 專家的 Google Cloud 基礎架構 Earned Dec 23, 2024 EST
Quiz: GDC Air-Gapped Practitioner Fundamentals Earned Dec 23, 2024 EST
AI Services and GDC Deployments and Operations Earned Dec 18, 2024 EST
Compute, Network, and Storage Services Configuration in GDC Earned Dec 18, 2024 EST
GDC Platform Introduction Earned Dec 9, 2024 EST
API Design and Fundamentals with the Apigee API Platform Earned Dec 9, 2024 EST
Google Cloud IAM and Networking for AWS Professionals Earned Dec 6, 2024 EST
生成式 AI 在醫療照護領域的應用 Earned Nov 29, 2024 EST
Google Cloud Fundamentals for AWS Professionals Earned Nov 18, 2024 EST
Google Cloud 的 AI 和機器學習服務簡介 Earned Oct 30, 2024 EDT
Google Kubernetes Engine 成本效益最佳化 Earned Oct 17, 2024 EDT
設定 Google Cloud 網路 Earned Oct 17, 2024 EDT
Planetary Scale Earth Observation with Google Earth Engine Earned Sep 10, 2024 EDT
Security Practices with Google Security Operations - SIEM Earned Sep 10, 2024 EDT
Google Cloud Security for the Public Sector Earned Sep 9, 2024 EDT
Build Streaming Data Pipelines on Google Cloud Earned Sep 6, 2024 EDT
[DEPRECATED] Google Cloud Data Solutions for the Public Sector Earned Sep 4, 2024 EDT
Google Cloud AI and ML Solutions for the Public Sector Earned Aug 30, 2024 EDT
使用 Gemini 和 Streamlit 開發生成式 AI 應用程式 Earned Aug 29, 2024 EDT
建立 Google Cloud 網路 Earned Aug 7, 2024 EDT
Observability in Google Cloud Earned Aug 6, 2024 EDT
在 Google 試算表使用函式、公式及圖表 Earned Jul 31, 2024 EDT
實現雲端協作與生產力工作流 Earned Jul 15, 2024 EDT
Vertex AI Studio 簡介 Earned Jun 14, 2024 EDT
建立圖像說明生成模型 Earned Jun 14, 2024 EDT
Transformer 和 BERT 模型 Earned Jun 14, 2024 EDT
注意力機制 Earned Jun 14, 2024 EDT
編碼器-解碼器架構 Earned Jun 14, 2024 EDT
圖像生成簡介 Earned Jun 14, 2024 EDT
使用 Gemini:端對端 SDLC Earned May 17, 2024 EDT
使用 Gemini:DevOps 工程師 Earned May 16, 2024 EDT
使用 Gemini:資安工程師 Earned May 15, 2024 EDT
使用 Gemini:網路工程師 Earned May 15, 2024 EDT
使用 Gemini:數據資料學家和分析師 Earned May 15, 2024 EDT
使用 Gemini:雲端架構師 Earned May 15, 2024 EDT
使用 Gemini:應用程式開發人員 Earned May 15, 2024 EDT
在 Agent Platform 設計提示 Earned Apr 24, 2024 EDT
負責任的 AI 技術:透過 Google Cloud 採用 AI 開發原則 Earned Apr 22, 2024 EDT
負責任的 AI 技術簡介 Earned Apr 22, 2024 EDT
大型語言模型簡介 Earned Apr 22, 2024 EDT
生成式 AI 簡介 Earned Apr 22, 2024 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Apr 5, 2024 EDT
在 Google Cloud 設定應用程式開發環境 Earned Mar 8, 2024 EST
Logging and Monitoring in Google Cloud Earned Mar 8, 2024 EST
開始使用 Google Kubernetes Engine Earned Mar 6, 2024 EST
可靠的 Google Cloud 基礎架構:設計與程序 Earned Mar 6, 2024 EST
Getting Started with Terraform for Google Cloud Earned Mar 5, 2024 EST
Google Sheets - Advanced Topics Earned Feb 25, 2024 EST
[DEPRECATED] Google Meet Earned Feb 25, 2024 EST
[DEPRECATED] Google Chat Earned Feb 24, 2024 EST
[DEPRECATED] Google Slides Earned Feb 24, 2024 EST
[DEPRECATED] Google Sheets Earned Feb 24, 2024 EST
[DEPRECATED] Google Docs Earned Feb 24, 2024 EST
[DEPRECATED] Google Drive Earned Feb 24, 2024 EST
[DEPRECATED] Google Calendar Earned Feb 24, 2024 EST
[DEPRECATED] Gmail Earned Feb 24, 2024 EST
彈性的 Google Cloud 基礎架構:資源調度與自動化 Earned Feb 20, 2024 EST
使用 Google Cloud 作業套件調度資源 Earned Feb 20, 2024 EST
Google Cloud 的可靠性與安全性 Earned Feb 20, 2024 EST
運用 Google Cloud 翻新基礎架構和應用程式 Earned Feb 19, 2024 EST
運用 Google Cloud 人工智慧推動創新 Earned Feb 19, 2024 EST
運用 Google Cloud 探索資料轉換功能 Earned Feb 18, 2024 EST
透過 Google Cloud 進行數位轉型 Earned Feb 18, 2024 EST
Google Cloud 必備知識 Earned Feb 16, 2024 EST
重要的 Google Cloud 基礎架構:核心服務 Earned Feb 15, 2024 EST
Build a Certification Study Guide: PCA Exam Prep Earned Feb 14, 2024 EST
Google Cloud 基礎知識:核心基礎架構 Earned Feb 13, 2024 EST
Build a Certification Study Guide: ACE Exam Prep Earned Feb 12, 2024 EST
重要的 Google Cloud 基礎架構:基本概念 Earned Feb 9, 2024 EST

This training course, the third course in the Configure Next Generation Firewall Series, shows you how to secure your VPC infrastructure using Cloud Next Generation Firewall (NGFW). Learn how to implement hierarchical and network policies, scope firewall rules, and configure intrusion detection and prevention to counter threats.

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This training course, the final course in the Configure Next Generation Firewall Series, shows you how to secure your GKE infrastructure using Cloud Next Generation Firewall (NGFW) policies. You learn how to use Cloud NGFW policies to protect clusters and individual node pools.

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Complete the intermediate Design and Implement Network Security in Google Cloud skill badge course to demonstrate skills in the following: Isolate a compromised VM via firewall rules and establish secure bastion access.Migrate tagged and untagged VPC firewall rules to a global network firewall policy.Troubleshoot outbound DNS resolution for a Google Compute Engine instance due to a misconfigured Cloud NAT.

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.

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使用 Agent Development Kit (ADK) 建構、設定及執行您的第一個 AI 代理,將自身代理知識化為實際成果。 在這堂實作課程,您會設立完整的 ADK 開發環境,並使用 Python 程式碼和 YAML 設定打造代理,然後透過多個介面執行。您也會瞭解定義代理行為的核心參數,將課程 1 的學習成果轉化為實際運作的程式碼。

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This Application Modernization course consists of a series of advanced-level labs designed to validate your proficiency in modernizing a customer's legacy software using Google Cloud. Each lab presents a set of the required tasks that you must complete with minimal assistance. You must score 80% or higher for each lab to complete this course, and fulfill your CEPF L300 Application Modernization requirement. If a green upgrade banner appears at the top of the page, follow the prompts to upgrade before continuing. If no banner is shown, you are already on the latest version. Required Labs: You only need to complete the labs marked as 'Required' to complete the course. Optional labs have no tag next to their titles; while recommended, they are not required. For technical issues with a Challenge Lab, please raise a Buganizer ticket using this CEPF Buganizer template: go/cepfl300labsupport

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Discover how to modernize, manage, and observe applications at scale using Google Kubernetes Engine. This course uses lectures and hands-on labs to help you explore and deploy using Google Kubernetes Engine (GKE), GKE Fleets, Cloud Service Mesh, and Config Controller capabilities that will enable you to work with modern applications, even when they are split among multiple clusters hosted by multiple providers.

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完成「在 Cloud Storage 建立串流資料湖泊」任務,即可獲得技能徽章。 本課程中,您將綜合運用 Pub/Sub、Dataflow 和 Cloud Storage, 在 Google Cloud 建立串流資料湖泊。

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This Infrastructure Modernization course consists of a series of advanced-level labs designed to validate your proficiency in modernizing a customer's IT infrastructure using Google Cloud. Each lab presents a set of the required tasks that you must complete with minimal assistance. The labs in this course have replaced the previous L300 Infrastructure Modernization Challenge Lab. If you have already completed the Challenge Lab as part of your L300 accreditation requirement, it will be carried over and count towards your L300 status. You must score 80% or higher for each lab to complete this course, and fulfill your CEPF L300 Security requirement. If a green upgrade banner appears at the top of the page, follow the prompts to upgrade before continuing. If no banner is shown, you are already on the latest version. Required Labs: You only need to complete the labs marked as 'Required' to complete the course. Optional labs have no tag next to their titles; while recommended, they are not…

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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 Agent Platform Feature Store's streaming ingestion at the SDK layer.

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完成在 Google Cloud 實作 CI/CD 管道技能徽章中階課程,即可獲得技能徽章。 您將透過本課程學習如何使用 Artifact Registry、Cloud Build 和 Cloud Deploy,並且操作 Google Cloud 控制台、Google Cloud CLI、Cloud Run 和 GKE。本課程會介紹如何建構持續整合 管道、儲存及保護構件、掃描安全漏洞、驗證 已核准的發布版本是否有效。此外,您還會實際操作,將應用程式 同時部署至 GKE 和 Cloud Run。

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In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.

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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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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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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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完成 在 Google Cloud 部署 Kubernetes 應用程式 技能徽章中階課程,即可證明您具備下列技能: 設定及建構 Docker 容器映像檔、建立及管理 Google Kubernetes Engine (GKE) 叢集、運用 kubectl 有效 管理叢集,以及運用強大的持續推送軟體更新做法來部署 Kubernetes 應用程式。

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本課程專為 Google Cloud 開發人員和 DevOps 工程師設計,建議的修習對象為熟悉 Google Cloud 控制台基本操作,且需要為組織設定 Gemini Code Assist 者。課程將介紹 Gemini Code Assist 的優點、比較不同版本的功能,並展示如何在組織內設定及管理 Gemini Code Assist。

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AI 推論是指下列流程:使用經過訓練的機器學習模型,應用習得的模式,對未見過的新資料進行預測。這門課程適合有興趣在 Cloud Run 快速部署 AI 推論服務的開發人員、資料科學家和機器學習工程師。如果您熟悉雲端式無伺服器應用程式部署解決方案,不過可能未曾使用 Google Cloud 無伺服器產品執行 AI 推論,這門課程相當適合您。 課程包含範例,呈現如何使用 GPU 部署 AI 推論模型,以及整合生成式 AI 應用程式與資料儲存服務。

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完成「透過直覺式程式開發和 MCP,建構智慧雲端應用程式」課程,即可獲得技能徽章。在本課程中,您將學會如何利用 Google AI 程式設計助理和 MCP 伺服器的強大功能。

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完成「搭配多代理系統使用 Agent Skills」技能徽章進階課程,即可證明您具備下列技能:使用 ADK 建構多代理系統、將代理連結代理對代理 (A2A) 通訊協定、使用 Model Context Protocol (MCP) 整合外部工具,以及將完整的多代理解決方案部署至 Agent Engine。 查看 Gemini Enterprise Agent Ready (GEAR) 計畫的其他內容。

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瞭解如何使用 Google 的 Agent Development Kit (ADK) 和 Model Context Protocol (MCP),設計、協調及部署多代理系統。本課程將以旅遊規劃服務為例,說明如何透過自訂防護機制,調度管理專用代理網路。完成本課程後,您將瞭解如何運用設計模式和部署策略,打造穩固且可擴充的 AI 工作流程。

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本課程適合各程度的開發人員,主要介紹 Gemini Code Assist 的核心功能與特色。這項 Google Cloud AI 輔助協作工具是應用程式開發的好幫手,提供程式碼智慧建議、自動補全、即時偵錯和重構輔助等實用功能。您將瞭解 Gemini Code Assist 如何大幅提升工作效率和程式碼品質,並助您省下寶貴時間,專心處理較具效益且更有趣的工作。

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完成「使用 Gemini Code Assist 開始開發應用程式」課程,即可獲得技能徽章。在本課程中,您將學會如何利用 Google AI 程式設計助理的強大功能。

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完成 雲端架構:設計、實作與管理 課程即可獲得 技能徽章,證明您具備下列技能: 使用 Apache 網路伺服器部署可公開存取的網站、使用開機指令碼設定 Compute Engine VM、 使用 Windows 防禦主機和防火牆規則設定安全的 RDP、建構 Docker 映像檔並部署至 Kubernetes 叢集,然後進行更新,以及建立 Cloud SQL 執行個體並匯入 MySQL 資料庫。 這個技能徽章課程是絕佳的 資源,可讓您瞭解Google Cloud 認證專業雲端架構師認證測驗涵蓋的主題。

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運用 MCP Toolbox for Databases 建構可存取企業資料庫的 AI 代理。您將定義安全的資料庫互動工具,並實作智慧查詢功能 (運用向量嵌入和結構化查詢)。

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瞭解 AgentOps 做法,將生成式 AI 代理從原型轉為正式產品。本課程涵蓋端對端觀測能力、在 CI/CD 管道中自動執行品質檢查,以及保護代理基礎架構,確保企業符合法規。探索 Gemini Enterprise Agent Ready (GEAR) 計畫的其他內容。

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This course brings AI-driven, natural-language data engineering into the IDE and CLI workflows you already use. Built on the Agent Development Kit (ADK), the Data Agent Kit connects to a wide array of Google Cloud services, including BigQuery, Spanner, BigLake, Dataproc, and Managed Airflow. By using it, you can collapse days of pipeline scaffolding, data build tool (dbt) authoring, and orchestration wiring into prompt-driven sessions. As an intermediate-to-advanced practitioner, you will learn to build a data agent with the Agent Development Kit (ADK). You'll wire up the Model Context Protocol (MCP) layer, and use your agent to explore catalogs, transform data, train models, and orchestrate scheduled pipelines on Google Cloud.

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Close the gap between general AI capabilities and your domain knowledge through Agent Skills. This course walks you through the full lifecycle of custom skill building, from local scaffolding and testing to enterprise scaling and sharing using Google's agent ecosystem, including Google Antigravity, ADK, and Skill Registry. Additionally, you use Google Agents CLI toolkit to attach skills to standalone 24/7 cloud agents, equipping your team with reliable, autonomous digital coworkers.

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步入代理式策略的未來:探索、設計與原型建立本課程可協助您精通 Google 代理式 AI 轉型框架,並將聊天機器人轉變為自動化團隊夥伴。您將透過零售應用實例,瞭解如何量化商業價值、排定 AI 專案的優先順序、規劃關鍵使用者歷程,並透過 Google AI Studio 和 Gemini Enterprise 等無程式碼工具建構可運作的原型。此課程提供穩定的學習藍圖,可協助企業和技術主管帶領組織踏入代理式 AI 的時代。

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您已建構能回覆查詢的基本 LLM 代理,是時候讓代理有狀態。利用工作階段狀態建構能維持對話脈絡、記住使用者偏好,並提供個人化體驗的代理。將代理從無狀態的回覆者轉為智慧助理。

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在本課程中,您將學習如何在 Google Antigravity 中自動調度管理代理程式,以驚人的速度建構軟體。這堂實作課程會先引導您安裝 Antigravity 並開始使用,接著,您將使用 Firebase 啟用服務,以透過 Antigravity 建構應用程式。最後,您將提示 Antigravity 中的代理程式平行運作,打造出 Voyager 電玩遊戲。

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本課程提供 Google Cloud 代理平台的完整說明,包括 Vertex AI Agent Builder、Gemini Enterprise、Conversational Agents,以及 Agent Development Kit。學員將瞭解每項產品的獨特功能,區分各特定用途適用的最佳解決方案,並掌握建立搜尋和即時通訊應用程式的基礎知識。

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本課程介紹 Gemini Enterprise,這個強大的平台結合 AI 代理、企業搜尋功能、Gemini Notebook 和智慧資料存取權,可協助組織解決營運難題。學員將透過實際案例和練習,瞭解 Gemini Enterprise 功能如何滿足實際業務需求、描述其架構,以及此平台如何管理不同職務的資料存取與隱私權事宜。

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完成 在 Google Cloud 實作 Cloud 安全防護措施:基礎知識 技能徽章中階課程, 即可證明您具備下列技能:運用 Identity and Access Management (IAM) 建立及指派角色、 建立及管理服務帳戶、啟用虛擬私有雲 (VPC) 網路中的私人連線、 運用 Identity-Aware Proxy 限制應用程式存取權、 運用 Cloud Key Management Service (KMS) 管理金鑰和已加密資料,以及建立私人 Kubernetes 叢集。

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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。

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In this challenge lab, you will act as a cloud engineer supporting the Cymbal Pools finance team. Your mission is to deploy a BigQuery-enabled agent to Agent Runtime to help process invoice data using natural language. Rather than building from scratch, you inherit an unsecured deployment. You must establish basic data governance by configuring the Agent Development Kit (ADK), deploying the agent with a dedicated SPIFFE identity, identifying permission blocks, and applying least-privilege IAM roles so the agent can safely query and update the BigQuery database from the Agent Runtime Playground.

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As organizations rapidly deploy AI workforces, securing these autonomous systems becomes paramount. Secure Your Agents with Gemini Enterprise Agent Platform is a practical, security-first course designed to help you establish centralized, zero-trust control and comprehensive visibility over your AI ecosystem. Instead of relying on theoretical frameworks, this course teaches you how to defend AI agents the way they are actually attacked—layer by layer, with identity and access at the absolute foundation.

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This course covers the technical side of governing an AI agent workforce using Agent Gateway, Agent Registry, and Policies. It discusses the overall architecture of centralized agent governance, focusing on managing agent sprawl and securing communication with internal systems. The course explores the infrastructure and enterprise networking required to deploy the Agent Gateway, including automated deployment with Terraform and configuring private egress via Private Service Connect. It offers guidance towards establishing a zero-trust security perimeter using unique agent identities with mTLS, per-tool authorization with REQUEST_AUTHZ, and granular CEL policies. Furthermore, it empowers administrators to implement content security guardrails using Model Armor and Cloud DLP to mitigate semantic threats like prompt injection and data leakage. Finally, the course explains how to manage tool discovery through the Agent Registry and ensure end-to-end observability and threat detection using…

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This course covers techniques for boosting and filtering search results, as well as the implementation of meta tags for advanced search control.

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This course provides learners the knowledge to configure Workforce Identity Federation to grant Google Cloud and Gemini access to users that authenticate using a third-party Identity Provider. The curriculum includes theory and demo videos covering workforce identity pools, OIDC and SAML providers, attribute mapping, IAM policies, and troubleshooting guidance.

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This course covers the technical side of deploying Gemini. It discusses the overall architecture of Gemini, decisions to be made when provisioning the app infrastructure, and integrating enterprise data via Data Stores, Connectors. and Actions. The course also explores the kinds of agents that can be added to Gemini. It offers guidance towards establishing a security perimeter using IAM, VPC Service Control, Context-Aware Access, and semantic controls deployed with Model Armor in Gemini platform. Finally, it empowers administrators to fine-tune the end-user experience through comprehensive configuration options, and explains how administrators keep AI deployments secure, compliant, and performant through OpenTelemetry instrumentation and prompt logging.

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This course will guide you through designing customer engagements that result in successful, well-utilized Gemini deployments. Study the art of change management, how to identify and engage sponsors, recruit early adopters, help your customer identify and address cultural change challenges and skills gaps, and effectively deliver project communications. Additionally, learn how to support your customer to plan, offer, conduct, and evaluate end-user training, leverage partner resources, and create essential project documents.

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Complete the Evaluate and Improve Agent Development Kit Agents skill badge to demonstrate your ability to use ADK's evaluation tools to "hill climb" — making measurable, iterative improvements to an agent. You will run an initial evaluation to establish a baseline, apply optimization techniques, and re-evaluate the agent to measure your success.

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In this course, you’ll learn how to estimate and manage GenAI solution costs, focusing on the unique unit economics of AI versus traditional cloud billing. You will learn to: Understand Metering: Master the four Google Cloud GenAI metering categories and the token economy driving costs. Estimate Costs: Build defensible estimates using the Pricing Calculator for models, context caching, and agentic components. Optimize Spend: Leverage controls—such as input/output token reduction, caching, RAG efficiency, and model routing—while balancing cost, quality, and latency. Implement Governance: Apply FinOps best practices, including budgets, quotas, cost attribution, and Provisioned Throughput management to control spend.

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In this course, you'll learn the disciplined process of hill climbing to transform your generative and agentic systems into reliable, high-performing tools. You'll examine the iterative 8-step loop by diagnosing system failures through trajectory analysis and applying precise interventions across the model, prompt, tool, and framework layers. By the end of this course, you'll be prepared to optimize system architecture and automate the hill climbing cycle while balancing quality, cost, and latency as first-class metrics.

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In this course, you'll learn how to establish a rigorous upgrade regression testing pipeline, safely deploy models using A/B testing and/or shadow mode, and address legacy prompt technical debt. You'll also learn the latest about Gemini 3 parameters including thinking levels and thought signatures, as well as new capabilities like media resolution controls and streaming function calls.

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In this course, you learn to evaluate, diagnose, and optimize AI agents on the Gemini Enterprise Agent Platform (GEAP). You begin where most teams begin: the agent runs, but you have no eval cases, no test data, and no production traffic to grade it with. From there you follow the Quality Flywheel, the evaluate-analyze-optimize loop at the center of GEAP. You instrument the agent so it emits the telemetry GEAP reads, generate eval cases by simulation, choose the metrics that grade them, run offline evaluations, monitor live traffic and alert on quality drift, then cluster failures and optimize. A final module covers build-time evaluation with the Agent Development Kit (ADK), which runs on your machine before you deploy.

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Throughout this course, you'll learn how to establish rigorous evaluation criteria, perform evaluations, design objective rubrics, calibrate autoraters, and simulate evaluation data. You'll gain the skills needed to design, execute, and scale a comprehensive evaluation plan that aligns system capabilities with organizational KPIs. This course is designed for technical practitioners, machine learning engineers, and software architects who build and deploy generative and agentic applications.

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This course explores architecting stateful AI agents that use short-term memory within a session or long-term memory services. Additionally, it covers giving agents existing expertise through skills. It details the core pillars of context engineering to facilitate personalized, continuous conversational experiences with expert agents.

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In this course, you explore the Code Execution feature of the Gemini platform, which lets AI agents safely generate and run Python code in isolated sandbox environments. You learn how the Agent Sandbox fits into the broader platform architecture, how to configure and operate Code Execution sandboxes using the Agent Platform SDK, and how to integrate code execution into agent workflows with the Agent Development Kit (ADK) in Gemini platform.

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In this course, you'll learn to use the Agent Development Kit (ADK) to build systems where multiple AI agents collaborate on complex tasks. You'll start with the ADK agent model: how ADK represents agents, tools, and runners, and how a single agent is configured and run. You'll then make tools the model can call, persist session state across agents, and instrument the execution lifecycle with callbacks and plugins. Next, you'll orchestrate multiple agents using ADK's template workflow agents and graph-based workflows, and ground them in enterprise data through multi-source retrieval and MCP integrations. Finally, you'll deploy a multi-agent system to Agent Runtime as a managed service and register and share it through Gemini Enterprise so users across an organization can reach it.

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Complete the Accelerate Development with Antigravity skill badge to demonstrate your proficiency in using the Antigravity IDE for developing agentic workflows. You will be tasked with configuring an MCP server, authoring custom agent skills and rules, prototyping with the Agents CLI, and deploying to the Google Cloud Agent Runtime. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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In this course, you'll learn to build and run enterprise agents on the Managed Agents API, the managed agent runtime on Gemini platform. Three conceptual lessons give you the mental model. You'll learn why a real business task needs an agent rather than a chat model. You'll examine how the platform splits into a control plane that defines agents and a data plane that runs them. You'll learn how to assemble an agent from a definition, a sandboxed environment, mounted data, tools, and skills. Furthermore, you'll learn how to run it with background interactions, a streamed reason-act loop, resilient typed results, and state that persists across turns. You then put that model to work in a hands-on lab, where you build, run, and harden a retail merchandising agent for Cymbal Retail from an empty project to a production-shaped deployment. By the end, you'll be able to design, build, and operate a managed agent of your own.

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In this course, you’ll learn to simplify the creation of autonomous enterprise agents using the Agent Development Kit (ADK) in Gemini platform and you will learn how to leverage the power of Antigravity and the Agents CLI to transform your agent development workflow. In this course, you will explore practical techniques to automate repetitive tasks and significantly accelerate the creation of robust, enterprise-grade agents, ensuring scalability and efficiency in your AI projects.

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In this challenge lab, you will demonstrate your ability to add agents to Gemini. You will build an agent with Agent Designer, and you will build a no-code agent with Agent Development Kit, deploy it to Agent Engine, and add it to Gemini.

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In this challenge lab, you will demonstrate your ability to author agents using Agent Development Kit (ADK), deploy those agents to Agent Engine, and use them from a web app. Complete the challenge lab to earn a Google Cloud skill badge.

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本課程說明如何使用 Google Agent Development Kit 建構複雜的多代理系統。您將建構配備工具的虛擬服務專員,並透過從屬關係和流程定義互動方式。您將在本機執行代理,並部署至 Gemini Enterprise Agent Platform 的 Agent Runtime,將其做為代管代理流程執行;Agent Runtime 則處理基礎架構決策和資源調度作業。請注意,這些實驗室是根據這項產品的預先發布版製成。我們會進行維護更新,因此這些研究室將可能出現延遲。

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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!"

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In this challenge lab, you act as a Security Engineer deploying a secure Gemini environment for Cymbal Bank. You will ground Gemini in web search and internal Workspace sources to ensure accurate, contextual responses. To maintain compliance, you will configure Model Armor policies to filter sensitive data and block threats like prompt injections and malicious URLs. Finally, you will manage specific end-user features to customize the AI experience safely

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您已建立具有進階設定功能的代理,可開始賦予代理實際應用能力。為代理配備工具,使代理能搜尋網路、執行程式碼、查詢資料庫和執行自訂動作。將代理從聰明的回覆者,轉變為能採取行動的得力助手。

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您已經成功打造第一個代理,是時候迎接更進階的挑戰。在本課程中,您將學習如何應用進階指令、選擇模型、建立規劃能力及結構化輸出模式,藉此將基本 AI 代理轉為高明又精確的助理,讓您的技能更上一層樓。加入社群論壇,提出問題並參與討論

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完成「使用 Agent Development Kit (ADK) 建造 AI 代理:工程設計」技能徽章中階課程,即可證明您具備下列技能: 提出實際的語言模型研究問題、建構簡單的權杖化工具、準備資料集來訓練 Transformer 語言模型,以及執行小型語言模型的訓練迴圈。

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完成進階的「部署多代理架構」技能徽章課程,證明您具備以下技能: 使用 ADK 建構多代理系統、將代理連結代理對代理 (A2A) 通訊協定、使用 Model Context Protocol (MCP) 整合外部工具,以及將完整的多代理解決方案部署至 Agent Engine。

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將代理從 localhost 移至正式環境。本課程將說明如何將 ADK 代理部署至 Vertex AI Agent Engine 和 Cloud Run,並透過 Memory Bank 視情況啟用跨工作階段記憶。

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運用 Google 的 Agent Development Kit (ADK) 和 Google Cloud 的強大基礎架構,探索多代理系統的架構和部署作業。您將學習設計階層式代理樹狀結構和確定性工作流程代理,同時找出理想的託管環境 (從無伺服器 Cloud Run 到高效能 GKE),確保您的 AI 代理安全、具備擴充性且可部署於正式環境。

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完成運用 Gemini Enterprise 自動調度管理多代理工作流程技能徽章的入門課程,即可證明您具備下列技能:使用 Gemini Enterprise 支援的代理型助理,整合第一方和第三方來源的資料;開發多媒體行銷素材資源;以及自動執行跨系統的業務行動。技能徽章課程透過實作實驗室和挑戰評量,檢驗學員對於特定產品的實作知識。完成課程或直接進行挑戰實驗室,即可取得徽章。徽章可證明您的專業能力、提升專業形象,開創更多職涯發展機會。前往個人資料頁面,追蹤您獲得的徽章。

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探索從任務導向工作流程到人本 AI 自動化調度管理的重要轉變。您將學習如何策略性區分擴增和自動化,以及如何平衡機器效率與人類直覺。

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使用生成式 AI 為使用者提供更好的搜尋流程,強化網站的瀏覽體驗。在本課程中,您會瞭解如何使用 Vertex AI Search,讓網站使用者能享有生成式搜尋體驗,進一步發掘網站內容。身為網站編輯,您也會學習如何使用生成式 AI 輸出建議,迅速有效地翻譯及調整內容。

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This course explores Google Cloud technologies to create and generate embeddings. Embeddings are numerical representations of text, images, video and audio, and play a pivotal role in many tasks that involve the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions. Specifically, you’ll use embeddings for tasks like classification, outlier detection, clustering and semantic search. You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) systems and question-answering solutions, on your own proprietary data using Google Cloud’s Vertex AI.

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Complete the Build search and recommendations AI Applications skill badge to demonstrate your proficiency in deploying search and recommendation applications through AI Applications. Additionally, emphasis is placed on constructing a tailored Q&A system utilizing data stores. Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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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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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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大型語言模型 (LLM) 誕生之後,生成式 AI 應用程式帶來的嶄新使用者體驗,可說是幾乎前所未有。身為應用程式開發人員,您要如何在 Google Cloud,運用生成式 AI 建立出色的互動式應用程式? 本課程將帶您瞭解生成式 AI 應用程式,以及如何使用提示設計和檢索增強生成 (RAG),透過 LLM 建構強大的應用程式。我們也會介紹可用於正式環境的生成式 AI 應用程式架構。您將建構採用 LLM 和 RAG 的對話應用程式。

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完成 使用 Gemini 多模態功能和多模態 RAG 檢查複合型文件 技能徽章中階課程,即可證明您具備下列技能: 透過 Gemini 多模態功能,使用多模態提示從文字和影像資料擷取資訊、生成影片說明,以及擷取影片以外的額外資訊; 透過 Gemini 的多模態檢索增強生成 (RAG) 功能,為含有文字和圖片的文件建構中繼資料、取得所有相關文字分塊,以及顯示引用資料。

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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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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 explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.

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This course explores the different products and capabilities of Gemini Enterprise for Customer Experience, including CX Agent Studio, Agent Assist and CX Insights. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.

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A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.

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In this course you will discover the exciting new features and capabilities of Customer Experience Agent Studio (CX Agent Studio), design AI agents from the CLI using MCP servers, learn how to evaluate your agent's performance and implement the Quality Hill Climbing process. You will also find out how to set up your agent's memory to store, retrieve, and use information across conversation turns and implement callbacks for logging or authentication, configure guardrails to protect against malicious attempts and ensure aligned responses, and deploy the agent to various channels. Additionally, you will explore the possible integrations between CX Agent Studio and CCaaS services and providers, including first party digital channel integrations with Google Telephony Platform (GTP), widgets and APIs, escalations to human agents through Google Cloud CCaaS and Gemini Enterprise for Customer Experience, and third party telephony and CCaaS integrations with providers such as Twillio or Salesfor…

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This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.

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本課程將複習 Model Armor 的基本安全功能,讓您具備使用這項服務的能力。您將瞭解 LLM 的相關安全風險,以及 Model Armor 如何保護 AI 應用程式。

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本課程會說明 Gemini in BigQuery,這是一套由 AI 輔助的功能,可協助「從資料到 AI」的工作流程。這些功能包含資料探索和準備、程式碼生成和疑難排解,以及工作流程探索和視覺化。本課程將透過概念解說、應用實例和實作實驗室,協助資料從業人員提升工作效率,並加速開發 pipeline。

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本課程將示範如何在 BigQuery 運用 AI/機器學行模型,以執行生成式 AI 任務。透過涉及顧客關係管理的應用實例,您將瞭解運用 Gemini 模型解決業務問題的工作流程。為了便於理解,本課程還提供了採用 SQL 查詢和 Python 筆記本的程式設計解決方案,指導您逐步操作。

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瞭解如何將 BigQuery 機器學習用於推論、資料分析師應使用這項工具的原因、相關應用實例,以及支援的機器學習模型。您也將瞭解如何在 BigQuery 建立和管理這些機器學習模型。

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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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這部影片說明如何使用 Gemini Gem 建構個人化的「工作夥伴」代理,簡化基本意見回饋,讓會議更具策略性且更有效率。

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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.

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這堂課程會完整說明如何在 Google Cloud 部署、管理及最佳化調整 AI 和高效能運算 (HPC) 工作負載。藉由一系列課堂和實務示範,您會瞭解不同的部署策略,從使用 Google Compute Engine (GCE) 的高度可自訂環境,到 Google Kubernetes Engine (GKE) 等代管解決方案。具體來說,您會學到如何建立叢集及部署 GKE,以便執行推論工作。

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Take these next steps to learn more about the Google Security Operations Platform. Build on fundamental knowledge to go deeper on customization and tuning.

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This course covers the baseline skills needed for the Google Security Operations Platform. The modules will cover specific actions and features that security engineers should become familiar with to start using the toolset.

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歡迎來到 Cloud TPU 課程。我們將探討在各種情境下使用 TPU 的優缺點,並比較不同的 TPU 加速器,協助您選擇合適的工具。您將瞭解如何盡可能提高 AI 模型的效能和效率,以及互通的 GPU/TPU 對於打造靈活的機器學習工作流程有多重要。我們會透過引人入勝的內容和實際演示,一步步引導您有效運用 TPU。

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想瞭解 AI 背後的強大硬體嗎?本單元將深入解析針對效能最佳化的 AI 電腦,說明其重要性。我們將探討 CPU、GPU 和 TPU 如何大幅加速 AI 任務運算,分析各自的特點,以及 AI 軟體如何充分利用這些硬體效能。單元結束後,您將清楚掌握如何根據 AI 專案挑選合適的 GPU,並做出明智的 AI 工作負載決策。

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準備開始使用 AI Hypercomputer 了嗎?這門課程可讓您快速上手!我們將介紹這個架構的基本概念,以及此架構如何幫助 AI 處理 AI 工作負載。您將瞭解 Hypercomputer 內的不同元件,例如 GPU、TPU 和 CPU,以及如何視需求選擇合適的部署方法。

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This course equips learners with the information they need to deploy reCAPTCHA in their websites, mobile applications, and web application firewalls (WAF). The course covers roles and permissions needed to integrate various reCAPTCHA features such as keys, assessments, and IP address allowlists, as well as the steps involved in preparing their cloud environment for reCAPTCHA integration. Learners will then have the opportunity to integrate reCAPTCHA into a cloud security architecture with Cloud Armor Bot Management.

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This course provides foundational knowledge for securing your Google Cloud environment. You will learn Google Cloud's security model, including Zero Trust principles and the Shared Fate model. You will configure identity services like Cloud Identity and Workforce Identity Federation, manage access control using Identity and Access Management (IAM) roles, conditions, and policies, and implement network security controls such as VPCs, Cloud Firewall tiers, and VPC Service Controls to build a secure perimeter. As the foundation of the Security in Google Cloud learning path, this course establishes the core principles required for two subsequent specialized tracks: the five-course Security Best Practices in Google Cloud series and the four-course Mitigate Threats in Google Cloud series.

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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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This training course builds on the concepts covered in the Networking in Google Cloud: Fundamentals course. Through presentations, demonstrations, and labs, participants explore and implement Cloud Load Balancing.

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Welcome to the fourth course of the "Networking in Google Cloud" series: Network Security! In this course, you'll dive into the services for safeguarding your Google Cloud network infrastructure. The first module, Distributed Denial of Service (DDoS) Protection, covers how to fortify your network against Distributed Denial of Service (DDoS) attacks, ensuring uninterrupted availability of your services. In the second module, Controlling Access to VPC Networks, you'll learn the network access control, enabling you to define permissions for who can access your resources and how. Finally, in the third module, Advanced Security Monitoring and Analysis, we'll explore how to proactively detect and respond to potential threats, keeping your Google Cloud environment secure and resilient. By the end of this course, you'll have a comprehensive understanding of Google Cloud network security.

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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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Welcome to the second course in the networking and Google Cloud series routing and addressing. In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities. Module one will lay the foundation by exploring network routing and addressing in Google Cloud, covering key building blocks such as routing IPv4, bringing your own IP addresses and setting up cloud DNS. In Module two will shift our focus to private connection options, exploring use cases and methods for accessing Google and other services privately using internal IP addresses. By the end of this course, you'll have a solid grasp of how to effectively route and address your network traffic within Google Cloud.

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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. 

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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Security Engineer certification exam. You'll review Gemini Notebook features, create a notebook, and learn how to use a study guide to practice for the certification exam.

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This is an opportunity for Technical Cloud Googlers to enhance their TPU/GPU skills and knowledge through a deep dive program covering the following focus areas/ individual tracks: TPU/GPU Networking GKE Expertise Slurm Expertise TPU/GPU Storage Best Practices Common transformer/LLM frameworks (Huggingface/triton/etc) Monitoring and logging for TPU/GPU    

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完成 透過 Vertex AI 建構及部署機器學習解決方案 課程,即可瞭解如何使用 Google Cloud 的 Vertex AI 平台、AutoML 和自訂訓練服務, 訓練、評估、調整、解釋及部署機器學習模型。 這個技能徽章課程適合專業數據資料學家和機器學習 工程師,完成即可取得中階技能徽章。技能 徽章是 Google Cloud 核發的獨家數位徽章, 用於肯定您在 Google Cloud 產品和服務方面的精通程度, 代表您已通過測驗,能在互動式實作環境應用相關知識。完成這個技能徽章課程 和結業評量挑戰實驗室,就能獲得數位徽章, 並與親友分享。

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人工智慧 (AI) 帶來轉型可能,但全新資安挑戰也隨著出現。本課程介紹資料安全和保護的策略,可幫助相關領域的領導者,在企業內部安全地管理 AI。您可以瞭解如何建立框架,主動辨別和減輕 AI 特有的風險、保護機密資料、確實法規遵循,並打造堅韌的 AI 基礎架構。我們提供四個不同產業的案例,帶您探索如何實際應用這些策略。

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本課程涵蓋「AI 隱私權」和「AI 安全性」這兩個重要主題。我們將介紹實用的方法和工具,協助您運用 Google Cloud 產品和開放原始碼工具,導入 AI 隱私權和安全性的建議做法。

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本課程旨在說明 AI 的可解釋性和透明度概念、探討 AI 透明度對開發人員和工程師的重要性。課程中也會介紹實務方法和工具,有助於讓資料和 AI 模型透明且可解釋。

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本課程旨在說明負責任 AI 技術的概念和 AI 開發原則,同時介紹各項技術,在實務上找出公平性和偏誤,減少 AI/機器學習做法上的偏誤。我們也將探討實用方法和工具,透過 Google Cloud 產品和開放原始碼工具,導入負責任 AI 技術的最佳做法。

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本課程針對評估生成式和預測式 AI 模型,向機器學習從業人員介紹相關的基礎工具、技術和最佳做法。模型評估是機器學習的重要領域,確保這類系統能在正式環境中提供可靠、準確且成效優異的結果。 學員將深入瞭解多種評估指標與方法,以及適用於不同模型類型和工作的應用方式。此外,也會特別介紹生成式 AI 模型帶來的獨特難題,並提供有效的應對策略。透過 Google Cloud Vertex AI 平台,學員將瞭解在模型挑選、最佳化和持續監控方面,該如何導入穩健的評估程序。

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本課程旨在提供必要的知識和工具,協助您探索機器學習運作團隊在部署及管理生成式 AI 模型時面臨的獨特挑戰,並瞭解 Vertex AI 如何幫 AI 團隊簡化機器學習運作程序,打造成效非凡的生成式 AI 專案。

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In this course, you will learn about the various services Google Cloud offers for modernizing retail applications and infrastructure. Through a series of lecture content and hands-on labs, you will gain practical experience deploying cutting-edge retail and ecommerce solutions on Google Cloud.

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This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.

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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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In this course you will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.

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「生成式 AI 代理:實現組織轉型」是 Gen AI Leader 學習路徑的第五堂也是最後一堂課程。本課程將探討組織如何運用自訂生成式 AI 代理,解決特定的業務難題。您將動手練習建構基本的生成式 AI 代理,同時探索這類代理的各種元件,例如模型、推論迴圈和工具。

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「生成式 AI 應用程式:徹底改變工作方式」是 Generative AI Leader 學習路徑的第四門課程。本課程將介紹 Google 的生成式 AI 應用程式,例如 Gemini for Workspace 和NotebookLM,也會引導您瞭解各種概念,像是建立基準、檢索增強生成、建構有效的提示詞,以及打造自動化工作流程等。

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「生成式 AI:掌握幕後技術與環境」是 Gen AI Leader 學習路徑的第三門課程。生成式 AI 正在改變我們的工作方式,以及與周遭世界的互動模式。身為領導者,您要如何駕馭其強大的功能,創造實際的業務成果?在本課程中,您將認識建構生成式 AI 解決方案時的各個層面、Google Cloud 產品與服務,以及選擇解決方案時應考量的因素。

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生成式 AI:瞭解基礎概念是 Gen AI Leader 學習路徑的第二門課程。在本課程中,您將瞭解 AI、機器學習和生成式 AI 的差異,以及各種類型的資料如何協助生成式 AI 解決業務難題,進而掌握生成式 AI 的基礎概念。您還能深入瞭解 Google Cloud 因應基礎模型限制的策略,以及開發、部署安全且負責任的 AI 技術時面臨的主要挑戰。

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「生成式 AI:不只是聊天機器人」是 Gen AI Leader 學習路徑的第一門課程,沒有先修條件。本課程旨在帶領您超越對聊天機器人的基本認識,探索生成式 AI 能為貴組織帶來的真正潛力。您將瞭解基礎模型和提示工程等概念,這些都是發揮生成式 AI 威力的關鍵。本課程也會引導您思考重要事項,協助您為貴組織制定成功的生成式 AI 策略。

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完成建立及管理 AlloyDB 執行個體技能徽章入門課程, 即可證明自己具備下列技能:執行主要 AlloyDB 作業 和工作、從 PostgreSQL 遷移至 AlloyDB、管理 AlloyDB 資料庫,以及 使用 AlloyDB 資料欄引擎加快數據分析查詢。

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This learning path, designed for customer-facing Googlers in Cloud GTM who are working on Agentspace implementation, will help them better assist customers you are working with in implementing Agentspace. Who should attend? This course is ideal for Googlers in Cloud GTM who are working with customers on Agentspace implementations. By the end of this course, you will be able to assist customers you are working with in implementing Agentspace. Prerequisites In order to fully benefit from this advanced level course, you should complete the following training before attending the Agentspace Implementation Bootcamp: Accelerate Knowledge Exchange with Agentspace (2 hours) - Includes the advanced level Extend Agentspace assistant capabilities with Conversational Agents lab. Deploy Agentspace labs - Use this link to earn the skills badge Includes the Deploy and query Google Agentspace: Learning Lab (1.5 hours) and the Deploy Google Agentspace with Data Stores and an action: Challenge Lab (1.5…

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完成部署與管理 Apigee X技能徽章課程,即可獲得技能徽章。 您將瞭解 Apigee X 架構、如何在 Google Cloud 專案佈建 Apigee X 組織、 如何透過 Apigee API 和 UI 管理 Apigee X,以及如何運用 Cloud Armor 和 Apigee 的威脅防護政策 來保護您的 API。

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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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這堂課程會說明 Google Workspace 管理員如何解決常見的 Google Workspace 問題。學員會練習診斷及解決 Gmail、Google 日曆和雲端硬碟的問題,熟悉管理控制台的操作方式,分析稽核記錄來解決安全性問題,收集資訊並使用可用資源來解決及回報技術性問題。

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本課程可助您培養在 Google Workspace 環境管理資料的技能。首先,您會瞭解如何在 Gmail 和雲端硬碟,運用資料遺失防護規則防止資料外洩。接著,您將學習使用 Google 保管箱保留、保存及檢索資料。再來,我們會說明如何設定資料地區和匯出方式,以遵守法規要求。最後,您會學習運用標籤區分資料,更安全有條理地管理資料。

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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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本課程旨在讓學員全面瞭解 Google Workspace 核心服務。學員將瞭解如何啟用、停用及設定這些服務,包括 Gmail、日曆、雲端硬碟、Meet、Chat 和文件。接著,他們將學習如何部署及管理 Gemini,為使用者提供強大助力。最後,學員將瞭解 AppSheet 和 Apps Script 的應用實例,學習如何自動處理工作,並擴充 Google Workspace 應用程式的功能。

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本課程說明如何保護 Google Workspace 環境。學員將導入高強度密碼政策和兩步驟驗證,控管使用者存取權,然後使用安全調查工具,主動找出並應對安全風險。接著,學員將管理第三方應用程式存取權和行動裝置,確保安全無虞。最後,學員將強制執行電子郵件安全性和法規遵循措施,保護機構資料。

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This Infrastructure Modernization course consists of a series of advanced-level labs designed to validate your proficiency in modernizing a customer's IT infrastructure using Google Cloud. Each lab presents a set of the required tasks that you must complete with minimal assistance. The labs in this course have replaced the previous L300 Infrastructure Modernization Challenge Lab. If you have already completed the Challenge Lab as part of your L300 accreditation requirement, it will be carried over and count towards your L300 status. You must score 80% or higher for each lab to complete this course, and fulfill your CEPF L300 Security requirement. Course Status: New required labs will be released between June and September 2026. You must use the latest version of the course to access these labs and ensure your progress is tracked correctly. If a green upgrade banner appears at the top of the page, follow the prompts to upgrade before continuing. If no banner is shown, you are already …

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In this skill badge, you will demonstrate your ability to deploy Google Agentspace and set up data stores and actions. To learn these skills, we encourage you to take the course Accelerate Knowledge Exchange with Agentspace.

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Gemini Enterprise 結合 Google 的搜尋和 AI 輔助功能,企業員工只要在單一搜尋列輸入關鍵字,就能查找文件儲存空間、電子郵件、對話、支援單處理系統和其他資料來源中的特定資訊。Gemini Enterprise 助理還能協助人員腦力激盪、研究資訊、列出文件大綱及執行其他動作,例如邀請同事加入日曆活動,加快完成知識型工作及各種協作作業。(請注意,Gemini Enterprise 先前稱為 Google Agentspace,本課程可能會提及產品舊稱。)

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本課程介紹 Google Workspace 的使用者和資源管理功能,學員將瞭解如何根據組織需求來設定組織單位、管理各類型的 Google 群組、培養有關管理 Google Workspace 網域設定的專業知識,最後學會如何最佳化及整理 Google Workspace 環境內的資源。

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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series. In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area. You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training. This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.

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In this course, you learn how to secure your APIs. You explore the security concerns you will encounter for your APIs. You learn about OAuth, the primary authorization method for REST APIs. You will learn about JSON Web Tokens (JWTs) and federated security. You also learn about securing against malicious requests, safely sending requests across a public network, and how to secure your data for users of Apigee. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the second course of the Developing APIs with the Apigee API Platform series. After completing this course, enroll in the API Development with the Apigee API Platform course.

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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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完成 建構適用於 AWS 專家的 Google Cloud 基礎架構 課程即可獲得技能徽章。在這個課程,您將學會如何設定 IAM 權限、 使用 Kubernetes 自動調度管理工作負載、透過 Compute Engine 託管網頁應用程式, 以及設定負載平衡機制。

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This quiz tests your GDC Air-Gapped Practitioner Fundamentals knowledge.

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The course explores advanced services such as machine learning, and operational topics such as application deployment, monitoring, and troubleshooting. In addition, we’ll introduce GDC software upgrades, logging, billing, and cost monitoring.

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The course examines service resources or workload components that exist in projects. You’ll learn about Kubernetes in GDC, Artifact Registry, GDC Object Storage, Database Service, Networking, and Key Management and Security.

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This course provides an introduction to the GDC platform—which enables you to host, control, and manage infrastructure and services directly on your premises. GDC air-gapped is one component of Google Distributed Cloud offering which aligns to Google’s digital sovereignty vision. It supports public-sector customers and commercial entities that have strict data residency, security or privacy requirements.

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In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API lifecycle, and how the Apigee API platform helps you manage all aspects of the lifecycle. You learn how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers. Through a combination of lessons, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the first course of the Developing APIs with the Apigee API Platform series. After completing this course, enroll in the API Security with the Apigee API Platform course.

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This is the first course of a four-course series for cloud architects and engineers with existing AWS knowledge, and it compares Google Cloud and AWS solutions and guides professionals on their use. This course focuses on Identity and Access Management (IAM) and networking in Google Cloud. The learners apply the knowledge of access management and networking in AWS to explore the similarities and differences with access management and networking in Google Cloud. Learners get hands-on practice building and managing Google Cloud resources.

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本課程專為專業醫護人員設計,深入淺出地介紹人工智慧的最新突破:生成式 AI,以及這項技術的推手:大型語言模型 (LLM)。您將瞭解生成式 AI 在醫療照護領域的實際應用,並掌握訣竅,針對特定目標撰寫有效的提示詞。

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Google Cloud Fundamentals for AWS Professionals introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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本課程介紹 Google Cloud 的 AI 和機器學習 (ML) 功能,著重說明如何開發生成式和預測式 AI 專案。我們也會探討「從資料到 AI」整個生命週期都適用的技術、產品和工具,並透過互動式練習,協助資料科學家、AI 開發人員和機器學習工程師精進專業知識。

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完成 Google Kubernetes Engine 成本效益最佳化 技能徽章中階課程, 即可證明您具備下列技能:建立及管理多租戶叢集、依據命名空間監控資源使用量、 設定自動調度叢集和 Pod 資源以提升效能、設定負載平衡以最佳化 資源分配,以及導入有效性和完備性探測,確保應用程式維持健康並符合成本效益。

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完成「設定 Google Cloud 網路」課程,即可獲得技能徽章。 您將瞭解如何在 Google Cloud Platform 執行基本的網路工作,包括建立自訂網路、新增子網路防火牆規則,還有建立 VM 並測試 VM 之間的通訊延遲。

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Learn how public sector agencies and academic researchers leverage Google Earth Engine to distill meaningful insights from petabytes of Earth Observation at planetary scale. Google Earth Engine is a fully managed geospatial platform that has enabled research for more than a decade in environmental areas such as forestry, agriculture, water, and sustainability.

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Learn the technical aspects you need to know about Chronicle and how it can help you detect and action threats.

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Work Safer With Work Safer, public sector organizations can benefit from a cloud first, zero trust security model that provides always up-to-date protection against cyber-attacks. The endpoint security covers mobile devices, desktop devices, Chromebook laptops, and meeting room hardware giving an elevated user experience for all users. DDoS mitigation and network threat intelligence in Google Cloud This session discusses mitigation techniques provided by Google Cloud to protect workloads from distributed denial-of-services (DDoS) attacks using Google Cloud Armor and its advanced threat intelligence features. Mitigation topics covered in this course include Adaptive Protection, bot management, rate limiting, and managed protection. Assured Controls in Google Workspace Assured Controls helps you meet compliance standards in regulated markets such as the public sector. Learn how you can control provider actions related to your data.

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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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Enterprise data sharing made easy with Dataplex and Analytics Hub Learn how to share data securely in your lakehouse with minimized data duplication and more data governance through Dataplex and Analytics Hub - enterprise data management made easy. Creating Data Pipelines with Data Fusion In this session, we will explore using Data Fusion to create code-free point and click pipelines that can ETL high-volumes of data with support for popular data sources, including file systems and object stores, relational and NoSQL databases, and SaaS systems.

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Building a Conversational Interface with Dialogflow CX Building conversational interfaces will enable you to engage your constituents in delightful new ways. This section will provide an overview of Dialogflow CX, which provides a range of new capabilities, languages, and functions. Scaling Equity and Access with Enterprise Translation Hub Accurate, timely and cost effective document translation has long been a challenge to providing equitable and accessible service to all constituents. In this section, explore Google's Enterprise Translation solutions which provide scalable document translation leveraging best in class Artificial Intelligence and Machine Learning, while retaining the critical human in the loop for final post editing review.

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完成 使用 Gemini 和 Streamlit 開發生成式 AI 應用程式 技能徽章中階課程,即可證明您具備下列技能: 生成文字、透過 Python SDK 和 Gemini API 呼叫函式,以及運用 Cloud Run 部署 Streamlit 應用程式。 您將瞭解如何以不同方式透過提示請 Gemini 生成文字、使用 Cloud Shell 測試及疊代 Streamlit 應用程式,隨後封裝成 Docker 容器並在 Cloud Run 中部署。

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完成 建立 Google Cloud 網路 課程即可獲得技能徽章。這個課程將說明 部署及監控應用程式的多種方法,包括查看 IAM 角色及新增/移除 專案存取權、建立虛擬私有雲網路、部署及監控 Compute Engine VM、編寫 SQL 查詢、在 Compute Engine 部署及監控 VM,以及 使用 Kubernetes 透過多種方法部署應用程式。

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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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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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完成「實現雲端協作與生產力工作流」課程,即可獲得入門級技能徽章。本課程將介紹 Google 的協作平台, 帶您瞭解如何使用 Gmail、日曆、Meet、雲端硬碟、試算表和 AppSheet。

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本課程會介紹 Vertex AI Studio。您可以運用這項工具和生成式 AI 模型互動、根據商業構想設計原型,並投入到正式環境。透過身歷其境的應用實例、有趣的課程及實作實驗室,您將能探索從提示到正式環境的生命週期,同時學習如何將 Vertex AI Studio 運用在多模態版 Gemini 應用程式、提示設計、提示工程和模型調整。這個課程的目標是讓您能運用 Vertex AI Studio,在專案中發揮生成式 AI 的潛能。

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本課程說明如何使用深度學習來建立圖像說明生成模型。您將學習圖像說明生成模型的各個不同組成部分,例如編碼器和解碼器,以及如何訓練和評估模型。在本課程結束時,您將能建立自己的圖像說明生成模型,並使用模型產生圖像說明文字。

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這堂課程將說明變換器架構,以及基於變換器的雙向編碼器表示技術 (BERT) 模型,同時帶您瞭解變換器架構的主要組成 (如自我注意力機制) 和如何用架構建立 BERT 模型。此外,也會介紹 BERT 適用的各種任務,像是文字分類、問題回答和自然語言推論。課程預計約 45 分鐘。

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本課程將介紹注意力機制,說明這項強大技術如何讓類神經網路專注於輸入序列的特定部分。此外,也將解釋注意力的運作方式,以及如何使用注意力來提高各種機器學習任務的成效,包括機器翻譯、文字摘要和回答問題。

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本課程概要說明解碼器與編碼器的架構,這種強大且常見的機器學習架構適用於序列對序列的任務,例如機器翻譯、文字摘要和回答問題。您將認識編碼器與解碼器架構的主要元件,並瞭解如何訓練及提供這些模型。在對應的研究室逐步操作說明中,您將學習如何從頭開始使用 TensorFlow 寫程式,導入簡單的編碼器與解碼器架構來產生詩詞。

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本課程將介紹擴散模型,這是一種機器學習模型,近期在圖像生成領域展現亮眼潛力。概念源自物理學,尤其深受熱力學影響。過去幾年來,在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中,擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論,並說明如何在 Vertex AI 上訓練和部署這些模型。

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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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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具,可協助工程師透過 Google Cloud 管理基礎架構。您將學到如何透過提示讓 Gemini 尋找和瞭解應用程式記錄檔、建立 GKE 叢集,以及研究如何打造建構環境。在實作研究室中,您也會瞭解 Gemini 如何改良開發運作的工作流程。 Duet AI 已更名為 Gemini,是我們新一代的模型。

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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 保護雲端環境和資源。您將學到如何將工作負載範例部署到 Google Cloud 中的環境,以及運用 Gemini 找出並修復安全性設定錯誤。在實作研究室中,您也會體驗到 Gemini 如何改良雲端安全防護機制。 Duet AI 已更名為 Gemini,這是我們的新一代模型。

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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,可協助網路工程師建立、更新及維護虛擬私有雲網路。您將瞭解如何透過提示讓 Gemini 為網路工作提供指引,獲得比搜尋結果更具體的資訊。在實作研究室中,您也會體驗到 Gemini 如何簡化 Google Cloud 虛擬私有雲網路的作業。 Duet AI 已更名為 Gemini,這是我們的新一代模型。

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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,可協助分析客戶資料及預測產品銷售情形。您也會學習如何在 BigQuery 中使用客戶資料識別、分類及開發新客戶。透過使用實作研究室,您可以體驗 Gemini 如何改良資料分析和機器學習工作流程。 Duet AI 已更名為 Gemini,這是我們的新一代模型。

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本課程介紹的 Gemini 是採用生成式 AI 技術的協作工具,可協助管理員在 Google Cloud 佈建基礎架構。您將瞭解如何透過提示讓 Gemini 解釋基礎架構、部署 GKE 叢集,以及更新既有的基礎架構。在實作研究室中,您也會體驗到 Gemini 如何改良 GKE 的部署工作流程。 Duet AI 已更名為 Gemini,這是我們的新一代模型。

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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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完成 在 Agent Platform 設計提示 技能徽章入門課程,即可證明您具備下列技能: 在 Agent Platform 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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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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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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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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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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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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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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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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This course builds on some of the concepts covered in the earlier Google Sheets course. In this course, you will learn how to apply and customize themes In Google Sheets, and explore conditional formatting options. You will learn about some of Google Sheets’ advanced formulas and functions. You will explore how to create formulas using functions, and you will also learn how to reference and validate your data in a Google Sheet. Spreadsheets can hold millions of numbers, formulas, and text. Making sense of all of that data can be difficult without a summary or visualization. This course explores the data visualization options in Google Sheets, such as charts and pivot tables. Google Forms are online surveys used to collect data and provide the opportunity for quick data analysis. You will explore how Forms and Sheets work together by connecting collected Form data to a spreadsheet, or by creating a Form from an existing spreadsheet.

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In this course, we introduce you to Google Meet, Google’s video conference software included with Google Workspace. You learn how to create and manage video conference meetings using Google Meet. You explore different ways to open Google Meet and add people to a video conference. You also learn how to join meetings from different sources like calendar events or meeting links. We discuss how Google Meet can help you better communicate, exchange ideas, and share resources with your team wherever they are. You learn how to customize the Google Meet environment to fit your needs and how to effectively use chat messages during a video conference. You also explore different ways to share resources, such as by using calendar invites or attachments. You learn about using host controls in Google Meet to manage participants and utilize interactive moderation features. You also learn how to record and live stream video conferences.

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In this course, we introduce you to Google Chat, Google’s chat software included with Google Workspace. You will learn about messaging individuals and groups in Google Chat. You will also discover customization options, collaboration features and how Google Chat integrates with other Google Workspace products. We will explore the use of spaces in Google Chat, showing you how to create, manage, search, and join them. Additionally, you will understand the distinctions between using a space and a group chat. You also explore Google Chat apps and learn how to search for and use apps within Google Chat. Aside from course videos, you will complete hands-on activities to practice what you’ve learned. Consider inviting a colleague or two to interact with you in Google Chat as you complete the activities.

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With Google Slides, you can create and present professional presentations for sales, projects, training modules, and much more. Google Slides presentations are stored safely in the cloud. You build presentations right in your web browser—no special software is required. Even better, multiple people can work on your slides at the same time, you can see people’s changes as they make them, and every change is automatically saved. You will learn how to open Google Slides, create a blank presentation, and create a presentation from a template. You will explore themes, layout options, and how to add and format content, and speaker notes in your presentations. You will learn how to enhance your slides by adding tables, images, charts, and more. You will also learn how to use slide transitions and object animations in your presentation for visual effects. We will discuss how to organize slides and explore some of the options, including duplicating and ordering your slides, importi…

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In this course we will introduce you to Google Sheets, Google’s cloud-based spreadsheet software, included with Google Workspace. With Google Sheets, you can create and edit spreadsheets directly in your web browser—no special software is required. Multiple people can work simultaneously, you can see people’s changes as they make them, and every change is saved automatically. You will learn how to open Google Sheets, create a blank spreadsheet, and create a spreadsheet from a template. You will add, import, sort, filter and format your data using Google Sheets and learn how to work across different file types. Formulas and functions allow you to make quick calculations and better use your data. We will look at creating a basic formula, using functions, and referencing data. You will also learn how to add a chart to your spreadsheet. Google Sheets spreadsheets are easy to share. We will look at the different ways you can share with others. We will also discuss how to track changes…

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With Google Docs, your documents are stored in the cloud, and you can access them from any computer or device. You create and edit documents right in your web browser; no special software is required. Even better, multiple people can work at the same time, you can see people’s changes as they make them, and every change is saved automatically. In this course, you will learn how to open Google Docs, create and format a new document, and apply a template to a new document. You will learn how to enhance your documents using a table of contents, headers and footers, tables, drawings, images, and more. You will learn how to share your documents with others. We will discuss your sharing options and examine collaborator roles and permissions. You will learn how to manage versions of your documents. Google Docs allows you to work in real time with others on the same document. You will learn how to create and manage comments and action items in your documents. We will review a few of the G…

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Google Drive is Google’s cloud-based file storage service. Google Drive lets you keep all your work in one place, view different file formats without the need for additional software, and access your files from any device. In this course, you will learn how to navigate your Google Drive. You will learn how to upload files and folders and how to work across file types. You will also learn how you can easily view, arrange, organize, modify, and remove files in Google Drive. Google Drive includes shared drives. You can use shared drives to store, search, and access files with a team. You will learn how to create a new shared drive, add and manage members, and manage the shared drive content. Google Workspace is synonymous with collaboration and sharing. You will explore the sharing options available to you in Google Drive, and you will learn about the various collaborator roles and permissions that can be assigned. You’ll also explore ways to ensure consistency and save time…

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With Google Calendar, you can quickly schedule meetings and events and create tasks, so you always know what’s next. Google Calendar is designed for teams, so it’s easy to share your schedule with others and create multiple calendars that you and your team can use together. In this course, you’ll learn how to create and manage Google Calendar events. You will learn how to update an existing event, delete and restore events, and search your calendar. You will understand when to apply different event types such as tasks and appointment schedules. You will explore the Google Calendar settings that are available for you to customize Google Calendar to suit your way of working. During the course you will learn how to create additional calendars, share your calendars with others, and access other calendars in your organization.

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Gmail is Google’s cloud based email service that allows you to access your messages from any computer or device with just a web browser. In this course, you’ll learn how to compose, send and reply to messages. You will also explore some of the common actions that can be applied to a Gmail message, and learn how to organize your mail using Gmail labels. You will explore some common Gmail settings and features. For example, you will learn how to manage your own personal contacts and groups, customize your Gmail Inbox to suit your way of working, and create your own email signatures and templates. Google is famous for search. Gmail also includes powerful search and filtering. You will explore Gmail’s advanced search and learn how to filter messages automatically.

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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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各種規模的機構都開始運用雲端的強大功能和靈活性,徹底改變營運方式。不過,有效管理及擴充雲端資源可能是相當複雜的工作。本課程將探討在雲端中的現代營運、可靠性和韌性的基礎概念,以及 Google Cloud 如何協助您達成這些目標。本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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組織將資料和應用程式遷移至雲端後,必須因應快速變化的安全性挑戰。本課程將探討雲端安全性的基礎知識、Google Cloud 融入安全考量設計的基礎架構價值,以及縱深防禦策略。此外,還會著重說明如何透過 AI 輔助作業和法規遵循工具,協助組織滿足嚴格的全球法規要求。 本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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許多傳統企業使用舊版系統和應用程式,無法滿足現今客戶的期望。企業主管經常需要在維護老舊的 IT 系統,以及投資新產品/服務之間做出選擇。本課程將探討這些挑戰,並提供解決方案,說明如何運用雲端技術克服難題。 本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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人工智慧 (AI) 和機器學習 (ML) 象徵著資訊技術的重大演進,正迅速改變各行各業。在「運用 Google Cloud 人工智慧推動創新」課程中,我們會探討組織如何運用 AI 和機器學習技術,翻轉業務流程。 本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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雲端技術是強大的資產,與資料搭配後,將成為創新和提升客戶體驗的催化劑。「運用 Google Cloud 探索資料轉換功能」課程將探討機構如何運用雲端,讓資料更易於存取、做為行動依據和更有價值。 這門課程是 Cloud Digital Leader 學習路徑的一部分,旨在協助個人在職務上成長,並打造企業的未來。

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數位轉型是現代組織必經的關鍵旅程,而建立穩固的雲端運算基礎,是跨出有意義創新的第一步。本課程「透過 Google Cloud 進行數位轉型」,將會介紹核心技術和策略框架,協助組織革新營運方式,並探討基本的雲端概念、全球網路基礎架構和共同責任模式,幫助主管在雲端之路上自信前行。本課程是 Cloud Digital Leader 學習路徑的一部分,旨在促進個人職能發展,並打造企業的未來。

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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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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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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Architect certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.

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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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Learn how to use Gemini Notebook to create a personalized study guide for the Associate Cloud Engineer certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook , and learn how to use a study guide to practice for a certification exam.

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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。

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