Vendeta Vendeta
Member since 2026
Gold League
8749 points
European University Challenge June 2026
Earned Jun 28, 2026 EDT
部署多代理架構
Earned Jun 27, 2026 EDT
Migrating MySQL data to Cloud SQL using Database Migration Service
Earned Jun 27, 2026 EDT
AI Boost Bites: Prompting like a Pro with Google Workspace
Earned Jun 7, 2026 EDT
[DEPRECATED] AI Boost Bites: Intro to NotebookLM
Earned Jun 7, 2026 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack
Earned Jun 7, 2026 EDT
AI Boost Bites: Tame Your Inbox with AI
Earned Jun 7, 2026 EDT
[DEPRECATED] AI Boost Bites: AI Power-Ups for Google Workspace
Earned Jun 7, 2026 EDT
AI Boost Bites: Your Personal Feedback Agent
Earned Jun 7, 2026 EDT
Google DeepMind: Train A Small Language Model
Earned Jun 1, 2026 EDT
Google DeepMind: 03 Design And Train Neural Networks
Earned Jun 1, 2026 EDT
Google DeepMind: 02 Represent Your Language Data
Earned Jun 1, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model
Earned Jun 1, 2026 EDT
運用 Gemini Enterprise 自動調度管理多代理工作流程
Earned May 29, 2026 EDT
以人為本的 AI
Earned May 29, 2026 EDT
生成式 AI 代理：實現組織轉型
Earned May 29, 2026 EDT
建立您的第一個 Gemini Enterprise 應用程式
Earned May 28, 2026 EDT
企業 AI 代理與用途
Earned May 28, 2026 EDT
AI 代理基礎知識
Earned May 28, 2026 EDT
AI 代理簡介
Earned May 28, 2026 EDT
管理 AI 代理的記憶與狀態
Earned May 27, 2026 EDT
運用工具讓 AI 代理具備所要能力
Earned May 26, 2026 EDT
AI 代理行為最佳化調整
Earned May 26, 2026 EDT
使用 Agent Development Kit (ADK) 打造您的第一個 AI 代理
Earned May 26, 2026 EDT
使用 Agent Development Kit (ADK) 打造 AI 代理
Earned May 26, 2026 EDT
部署您的第一個代理
Earned May 25, 2026 EDT
在正式環境建構及部署代理
Earned May 25, 2026 EDT
European University Challenge May 2026
Earned May 25, 2026 EDT
European University Challenge April 2026
Earned Apr 22, 2026 EDT
This month, you’ll master advanced data management, infrastructure security, and cross-platform app development. Dive into HashiCorp Vault to secure infrastructure secrets, scale global data with Cloud Spanner, and build responsive front-ends using Flutter. Top it off by setting up robust monitoring using Prometheus on Google Cloud. Ready to engineer at scale?
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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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This course offers hands-on practice with migrating MySQL data to Cloud SQL using Database Migration Service. You start with an introductory lab that briefly reviews how to get started with Cloud SQL for MySQL, including how to connect to Cloud SQL instances using the Cloud Console. Then, you continue with two labs focused on migrating MySQL databases to Cloud SQL using different job types and connectivity options available in Database Migration Service. The course ends with a lab on migrating MySQL user data when running Database Migration Service jobs.
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This video covers prompt engineering fundamentals for effective AI communication. Learn a simple framework (Persona, Task, Context, Format) to craft clear prompts, getting better, faster results from Gemini in Google Workspace. Discover how to use natural language, be specific, and iterate for optimal AI assistance.
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This video covers how to use NotebookLM as a personal research
assistant by adding sources, asking questions, and generating new content
formats based on your documents.
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This video covers how to eliminate tedious manual data entry using Gemini. Learn how to take a picture or screenshot of data (from PDFs, paper, or images) and prompt Gemini to instantly convert it into a structured Google Sheet. Discover this simple hack to save countless hours transcribing data, turning Gemini into your personal data entry assistant. Just snap, prompt, and export!
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This video covers how to use Gemini in Gmail to summarize emails, find information, and draft replies, helping you manage your inbox more efficiently.
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This video covers five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.
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This video covers how to build a personalized "Work with Me" agent using Gemini Gems, which helps streamline foundational feedback and makes your meetings more strategic and efficient.
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Complete the advanced Google DeepMind: Train A Small Language Model skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Access this lab at no-cost by signing up for the no-cost subscription. Receive 35 free credits each month!
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In this Google DeepMind course you will focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.
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In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.
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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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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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「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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建立您的第一個 Gemini Enterprise 應用程式，獲得技能徽章！將各種資料來源連接到您的應用程式，建立強大的統合式搜尋和分析引擎。掌握 Deep Research 代理、多代理構思和 NotebookLM 等進階功能，進行重點分析。
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瞭解 AI 代理如何發揮更高的業務影響力，包括根據您的 KPI 規劃要使用的代理類型，以及探索能解決實際瓶頸的用途。您也將認識各種無程式碼到高程式碼解決方案，瞭解 Gemini Enterprise 如何協助建構和自動調度合適的代理。
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本課程介紹 AI 代理的基礎知識，並探討代理的實際應用價值。代理可為開發人員、架構師和技術決策者奠定基礎，協助他們從目標導向的自主行為角度來理解 AI 系統。
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瞭解 AI 代理的概念，探索代理如何藉由自主行動及推論解決複雜問題。您將瞭解代理如何透過模型、工具和調度管理程序等技術架構，助您學習、規劃和實現目標。
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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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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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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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瞭解如何使用 Agent Development Kit (ADK)，建構複雜的 AI 代理並用於正式環境。本課程介紹 ADK 的開放原始碼框架，包括簡單的提示工程，以及程式碼優先的結構化軟體開發做法 (適用於企業級多代理系統)。
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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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This month, you’ll dive into Cloud ML APIs to analyze images and classify text while managing data security with Bucket Lock. From monitoring metrics with Prometheus to commanding the Cloud Shell, you’ll leverage essential APIs and tools to build a smarter, more secure cloud environment. Ready to scale?
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Ready to master the future of intelligence? This Google Skills game challenges you to monitor projects, create alerts, and create, deploy, and test a Cloud Run function using Google Cloud console!
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