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Ignacio Alfredo Mateluna Mendez

Member since 2025

Gold League

9270 points
Add Agents to Gemini Earned Oct 16, 2026 EDT
Govern Agent Access with Gemini platform Earned Oct 15, 2026 EDT
Secure your Agents with Gemini platform Earned Oct 15, 2026 EDT
Govern agents with Agent Gateway, Agent Registry, and Policies Earned Oct 14, 2026 EDT
Deploy Gemini with Workspace Data Sources and Model Armor Earned Oct 14, 2026 EDT
Model Armor：保護您部署的 AI 應用程式 Earned Oct 9, 2026 EDT
Improve Agent Search findings on Gemini platform Earned Oct 6, 2026 EDT
Use a Third-Party Identity Provider with Workforce Identity Federation Earned Oct 4, 2026 EDT
Deploy Gemini to Transform Enterprises Earned Oct 3, 2026 EDT
Plan Change Management for Gemini Deployments Earned Oct 3, 2026 EDT
[DEPRECATED] 運用 Gemini Enterprise 加速知識交流 Earned Jul 30, 2026 EDT
Gemini Enterprise 簡介 Earned Jun 29, 2026 EDT
在 Google 試算表使用函式、公式及圖表 Earned Jun 28, 2026 EDT
AppSheet Team Hierarchy Earned Mar 5, 2026 EST
Protect your data with Google Workspace Security Earned Mar 5, 2026 EST
Google Workspace 疑難排解 Earned Dec 1, 2025 EST
Google Workspace 安全性 Earned Nov 29, 2025 EST
Google Workspace 資料治理 Earned Nov 14, 2025 EST
Google Workspace 核心服務 Earned Oct 16, 2025 EDT
Google Workspace 的使用者和資源管理功能 Earned Sep 10, 2025 EDT
Google Workspace with Gemini：AI 工作流程的基礎 Earned Sep 4, 2025 EDT
Google Workspace 必備知識 Earned Sep 3, 2025 EDT

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 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 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 in Gemini platform 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 thr…

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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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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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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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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 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 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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A short course on defining and managing teams and organizations in Google AppSheet.

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This course empowers learners to protect their Google Workspace environment and maintain regulatory compliance. It covers essential topics like preventing unauthorized access, safeguarding sensitive data, and enhancing visibility and control. Participants will gain practical skills in threat detection, data protection, and compliance enforcement, ensuring the security and integrity of their Google Workspace environment.

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

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Workspace 是 Google 的協作應用程式 平台，由 Google Cloud 提供。在這堂入門課程中，您將 從使用者角度實作練習 Workspace 的核心應用程式。雖然 Workspace 包含的應用程式和工具元件遠比本課程介紹的還要多， 您將體驗的是主要應用程式，包括 Gmail、日曆、試算表以及 其他幾項。每個實驗室功能需要 10 至 15 分鐘來完成，但您也可以視需要花更多時間 自行探索應用程式。

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