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Killua HunterX

Member since 2026

Silver League

1163 points
透過 BigQuery 建構資料倉儲 Earned Jul 15, 2026 EDT
Arcade Base Camp June 2026 Earned Jun 30, 2026 EDT
Arcade Trail: Data Engineering and Information Protection Earned Jun 30, 2026 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned Jun 30, 2026 EDT
Skill Up Summer Earned May 28, 2026 EDT
Arcade Voyage: Data Governance and Firebase Foundations Earned May 28, 2026 EDT
Arcade Trail: Cloud Security and DevOps Foundations Earned May 27, 2026 EDT
Arcade Adventure: Modern App Deployment Earned May 22, 2026 EDT
Arcade Trail: Data Migration Earned Apr 30, 2026 EDT
Arcade Voyage: Modern Application Development Earned Apr 30, 2026 EDT
Arcade Adventure: GKE Operations and Networking Earned Apr 20, 2026 EDT
Arcade Base Camp April 2026 Earned Apr 20, 2026 EDT
Works Meet Play: Skills Spawn Earned Apr 18, 2026 EDT
使用 Apps Script 整合 BigQuery 資料與 Google Workspace Earned Apr 11, 2026 EDT
運用 BigQuery 導入多模態向量搜尋 Earned Apr 11, 2026 EDT
在 Google Cloud 實作 CI/CD 管道 Earned Apr 11, 2026 EDT
在 Google Cloud 實作 Sensitive Data Protection Earned Apr 11, 2026 EDT
使用 Apps Script 及 AppSheet 進行開發作業 Earned Apr 11, 2026 EDT
使用 Gemini 和 Streamlit 開發生成式 AI 應用程式 Earned Apr 8, 2026 EDT
透過 Google Cloud 建構網站 Earned Apr 8, 2026 EDT
使用 Knowledge Catalog 建構資料網格 Earned Apr 8, 2026 EDT
運用 Gemini 分析多模態資料並推論 Earned Apr 8, 2026 EDT
在 Compute Engine 導入 Cloud Load Balancing Earned Apr 6, 2026 EDT
Google DeepMind：訓練小型語言模型 Earned Apr 6, 2026 EDT
使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL Earned Apr 6, 2026 EDT
透過直覺式程式開發和 MCP，建構智慧雲端應用程式 Earned Apr 6, 2026 EDT
Dialogue Design Earned Apr 5, 2026 EDT

完成 透過 BigQuery 建構資料倉儲 技能徽章中階課程，即可證明您具備下列技能： 彙整資料以建立新資料表、排解彙整作業問題、利用聯集附加資料、建立依日期分區的資料表， 以及在 BigQuery 使用 JSON、陣列和結構體。

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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!

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Raw data is only useful if it is clean, structured, and secure. In this track, you’ll start by processing and preparing data using Dataprep, Dataflow templates, and Apache Spark. You'll learn how to clean up datasets so they are ready for machine learning models. From there, you'll focus on security by working with tools that find and mask sensitive information like personal IDs and credentials. You'll practice redacting critical details and creating safe, de-identified copies of your data in Cloud Storage. By finishing the hands-on challenge labs, you’ll show you can handle big data workflows while keeping confidential information completely safe.

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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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A season to build, experiment, and grow—one skill at a time. You’ll start with the fundamentals of networking, creating the foundation that connects everything together. From there, you’ll step into automation and application development using Cloud Scheduler, App Engine, and machine learning APIs. By the end, you’ll have a more confident, hands-on understanding of how modern applications are built, connected, and run on the cloud.

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Working with data and applications requires the right balance of governance and agility. In this voyage, you’ll use Dataplex to organize, secure, and assess data quality while exploring concepts like data mesh. Alongside, you’ll get hands-on with Firebase—building serverless apps, working with Firestore, and managing data in real time—bringing together modern data management and application development.

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Securing applications and streamlining delivery go hand in hand in modern cloud environments. In this trail, you’ll work with tools like Cloud KMS, Identity-Aware Proxy, and service accounts to manage access and protect resources. You’ll also explore private Kubernetes clusters, artifact management, and build CI/CD pipelines with Cloud Build—bringing together the essentials of cloud security and DevOps in practice.

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Building and running applications on Google Cloud can take many forms—and this adventure brings them together. Get hands-on with App Engine, Cloud Run, Kubernetes Engine, and Compute Engine as you deploy applications, manage scaling, and explore modern architectures, including the shift from monolithic to microservices.

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A lot of cloud work comes down to moving data, managing access, and making sense of what’s happening behind the scenes. In this trail, you’ll migrate a MySQL database to Google Cloud, work with IAM permissions using gcloud, and analyze network traffic with VPC Flow Logs. You’ll also store and manage media files, prepare data with Dataprep, and build reports using Looker Studio and LookML. There’s even a lab on measuring Speech-to-Text accuracy. It’s a mix of tasks that shows how data is handled, monitored, and used across different parts of Google Cloud.

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On Google Cloud, building an app usually means handling more than just the code. You’ll need to deploy it, connect services, and keep things running properly. In this voyage, you’ll host a web app, set up a deployment pipeline, and build a REST API with Cloud Run. You’ll also try out Flutter and set up a Python development environment. You’ll work with VPC networks, load balancing, and clean up unused resources along the way. It’s a practical set of tasks that reflects how apps are actually run on Google Cloud.

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Google Kubernetes Engine (GKE) is all about running and managing containerized applications without worrying too much about the underlying setup. In this adventure, you’ll get hands-on with how things actually work—managing workloads, debugging issues, and trying out autoscaling. You’ll also explore Autopilot, run load tests, and work with private clusters and network access. By the end, you’ll have a clearer sense of how GKE setups are put together and handled in practice.

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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!

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Online games can get unpredictable. One update drops, a new event goes live—and suddenly, thousands of players are logging in at the same time. That’s where the backend really gets tested. Companies like Com2uS rely on cloud infrastructure to handle exactly this kind of pressure without things falling apart. Here, you’ll work through the same building blocks—setting up networks, handling secure connections, and deploying apps with Docker and Kubernetes. You’ll add authentication, keep an eye on things with logging, and move data when needed. It’s the kind of work that keeps everything running smoothly while players just focus on the game.

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完成「使用 Apps Script 整合 BigQuery 資料與 Google Workspace」技能徽章入門課程，即可證明您瞭解如何透過 AppSheet 將 Workspace 產品連結至 BigQuery。

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完成運用 BigQuery 導入多模態向量搜尋技能徽章中階課程， 即可證明自己具備下列技能：使用 Gemini in BigQuery 生成 SQL 程式碼並偵錯、執行情緒分析、 總結文字重點並找出關鍵字、生成嵌入項目、建立檢索增強生成 (RAG) pipeline， 以及導入多模態向量搜尋。

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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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完成 在 Google Cloud 實作 Sensitive Data Protection 技能徽章入門課程，證明您具備下列技能：使用 Sensitive Data Protection 服務 (包括 Cloud Data Loss Prevention API) 來檢查、遮蓋及去識別化 Google Cloud 中的機密資料。

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完成使用 Apps Script 及 AppSheet 進行開發作業技能徽章課程，即可獲得技能徽章， 瞭解如何建構聊天機器人，以及如何使用在任何文件中使用指令碼編輯器。

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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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完成透過 Google Cloud 建構網站技能徽章課程，即可獲得入門級技能徽章。 本課程以 Get Cooking in Cloud 系列影片為基礎， 涵蓋以下主題：在 Cloud Run 部署網站在 Compute Engine 託管網頁應用程式在 Google Kubernetes Engine 建立、 部署及擴充網站使用 Cloud Build 將單體式應用程式遷移至微服務架構

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完成「使用 Knowledge Catalog 建構資料網格」技能徽章入門課程，即可證明您具備下列技能：使用 Knowledge Catalog 建構資料網格， 以利在 Google Cloud 維護資料安全性，並協助治理和探索資料。您將練習並測試自己的技能，包括在 Knowledge Catalog 為資產加上標記、指派 IAM 角色，以及評估資料品質。

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完成運用 Gemini 分析多模態資料並推論技能徽章中階課程，即可證明自己具備下列技能：使用 Gemini 2.0 Flash 分析文字、圖像、音訊 (以樂譜呈現) 和影片資料；以及依據這類複合型資訊，推導出結論及擷取洞察結果。

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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「Google DeepMind：訓練小型語言模型」技能徽章進階課程，即可證明您具備下列技能： 提出實際的語言模型研究問題、建構簡單的分詞器、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。 註冊免付費訂閱方案，即可免付費使用這個實驗室。每個月還能獲得 35 點免付費抵免額！

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完成 使用資料庫遷移服務將 MySQL 資料遷移至 Cloud SQL 技能徽章入門課程，證明您具備下列技能： 使用「資料庫遷移服務」中各種可用的工作類型和連線選項， 將 MySQL 資料遷移至 Cloud SQL，以及在執行「資料庫遷移服務」工作時 遷移 MySQL 使用者資料。

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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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78%—or nearly 8 in 10—business leaders say Google Cloud helps them stay ahead in the age of AI. A big part of that comes down to how teams build and connect intelligent systems. Here, you’ll build and manage conversational agents, and use speech-to-text and translation APIs to handle different types of input. You’ll also move from monolithic apps to microservices on GKE, connect workflows using webhooks, and use observability tools to keep track of what’s happening. IAM comes in as well to manage access where needed. It’s a practical look at how these pieces are used together in real setups.

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