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Anurag Priyadarshi

Member since 2026

Bronze League

3600 points
在 Google Cloud 儲存、處理與管理資料 - 控制台 Earned Aug 30, 2026 EDT
Arcade Re-Trail: Vaults & Vectors Earned Aug 30, 2026 EDT
在 Google App Engine 上部署及管理應用程式 Earned Jul 17, 2026 EDT
實現 Cloud Storage 和數據保護解決方案 Earned Jul 17, 2026 EDT
Google Cloud Compute 基本操作 Earned Jul 16, 2026 EDT
建立您的第一個 Gemini Enterprise 應用程式 Earned Jul 16, 2026 EDT
使用 Knowledge Catalog 建構資料網格 Earned Jul 16, 2026 EDT
透過 BigQuery 建構資料倉儲 Earned Jul 16, 2026 EDT
Arcade Simulator: Data Mesh Architect Earned Jul 16, 2026 EDT
在 Google Cloud 實作 Sensitive Data Protection Earned Jul 14, 2026 EDT
在 Google Cloud 為機器學習 API 準備資料 Earned Jul 14, 2026 EDT
使用預訓練 API 實現語音和語言解決方案 Earned Jul 14, 2026 EDT
為 Google Cloud 設定服務帳戶和 IAM 角色 Earned Jul 14, 2026 EDT
Arcade Voyage: Identity Management and Pre-trained AI APIs Earned Jun 30, 2026 EDT
Arcade Trail: Data Engineering and Information Protection Earned Jun 17, 2026 EDT
機器學習運作 (MLOps) 與 Vertex AI:模型評估 Earned Jun 7, 2026 EDT
生成式 AI 適用的機器學習運作 (MLOps) Earned Jun 7, 2026 EDT
透過 Google Cloud Observability 監控及記錄系統狀態 Earned Jun 4, 2026 EDT
Arcade Adventure: App Dev and Cloud Observability Earned Jun 4, 2026 EDT
在 Google Cloud 設定應用程式開發環境 Earned Jun 4, 2026 EDT
Google Cloud 資料分析基本概念 Earned Jun 4, 2026 EDT
Build Global and Regional Load Balancing Solutions Earned Jun 4, 2026 EDT
Arcade Base Camp June 2026 Earned Jun 4, 2026 EDT
Build a Certification Study Guide: ACE Exam Prep Earned Jun 3, 2026 EDT
在 Compute Engine 導入 Cloud Load Balancing Earned Jun 3, 2026 EDT
在 Looker 建構 LookML 物件 Earned Jun 2, 2026 EDT
Logic Log Earned Jun 2, 2026 EDT
Looker 資料模型管理 Earned Jun 2, 2026 EDT

Cloud Storage、Cloud Functions 和 Cloud Pub/Sub 都是 Google Cloud Platform 服務, 可用於儲存、處理及管理資料。您可以整合運用這三種服務, 打造各式各樣的資料導向應用程式。在這個技能徽章課程中, 您將使用 Cloud Storage 儲存圖片、透過 Cloud Functions 處理, 並利用 Cloud Pub/Sub 將圖片傳送至其他應用程式。

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Since last month's Arcade Trail wrapped up earlier than expected, we’re opening up this bonus game only for this month so you can grab that missed Arcade Point! You'll start on the vault side with Google Cloud Storage—managing buckets, exploring APIs, and locking down sensitive data with Bucket Lock. Then, you'll shift to event-driven vectors at the command line, triggering Cloud Run Functions and routing real-time messages through Pub/Sub. Complete with two hands-on challenge labs, this trail gets your streak back on track while building real-world storage and serverless skills.

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完成「在 Google App Engine 上部署及管理應用程式」課程,即可獲得技能徽章。本課程將說明如何搭配 Python、Go 和 PHP 使用 App Engine。

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若想獲得技能徽章,請完成實現 Cloud Storage 和數據保護解決方案 技能徽章課程,您將在此瞭解如何建立 Cloud Storage bucket、 如何使用 Cloud Storage 指令列,以及如何在區塊中使用值區鎖定功能保護物件。

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完成「Google Cloud Compute 基本操作」任務, 學習如何在 Compute Engine 中使用虛擬機器 (VM)、永久磁碟 和網路伺服器,即可獲得技能徽章。

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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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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 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 this month's Arcade Simulator where you will be a Data Mesh Architect. In this simulation, you'll first tackle BigQuery to build date-partitioned tables, solve complex join pitfalls, and master nested data structures. Then, you'll shift to decentralized governance using Dataplex Knowledge Catalog to organize assets, assign metadata, and enforce strict cloud security. Complete with two realistic challenge labs, this simulation equips you to break down data silos, scale your infrastructure, and run a secure, seamless data mesh.

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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 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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完成使用預訓練 API 實現語音和語言解決方案課程以獲得技能徽章,了解如何使用與語音相關的 API 工具來合成和轉錄語音。

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完成「為 Google Cloud 設定服務帳戶和 IAM 角色」課程,即可獲得入門級技能徽章。這門課程會介紹服務帳戶、自訂角色,以及如何使用 gcloud 設定權限。

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Keeping your cloud resources secure and making your apps smarter are two essential skills for any cloud developer. In this voyage, you’ll start with the security fundamentals, learning how to configure service accounts, manage IAM permissions using gcloud, and set up custom roles. Once you've secured your environment, you'll work with Google Cloud's pre-trained AI tools—converting text to synthetic speech, translating languages on the fly, and transcribing audio files into text. Complete with two practical challenge labs to test your skills, you'll walk away knowing how to safely manage access to your cloud project while adding powerful language and speech features to your applications.

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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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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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完成 透過 Google Cloud Observability 監控及記錄系統狀態 技能徽章入門課程, 即可證明您具備下列技能:監控 Compute Engine 中的虛擬機器、 運用 Cloud Monitoring 監管多項專案、在 Cloud Functions 延伸應用監控和記錄功能、 建立和傳送自訂應用程式指標,以及根據自訂指標設定 Cloud Monitoring 快訊。

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Writing code is just the first step; you also need to know how to deploy it smoothly and keep it running at its best. In this adventure, you’ll get started with serverless setups by running code on Cloud Run Functions and connecting your services using Google Cloud Pub/Sub. From there, you'll work on the operations side—building out clean development environments, keeping tabs on multiple projects at once, and setting up smart alerts so you can spot and fix issues early. With a couple of challenge labs thrown into the mix, you’ll walk away with the skills needed to build, monitor, and scale apps 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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瞭解如何在 Google Cloud 將原始數據轉化為明確的資料導向決策。本初級課程提供實作研究室和實際情境,引導您在 BigQuery 查詢資料、在 Looker 探索趨勢,以及透過數據分析工具製作可共用的互動式報表。

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Complete the intermediate Build Global and Regional Load Balancing Solutions skill badge course to demonstrate skills in the following: deploy and utilize an internal client VM within the same VPC network and test traffic distribution, backend infrastructure suitable for a global external application Load Balancer, and backend VM instances and load balancer components using startup scripts and network tags to host a web application service.

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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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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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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「在 Looker 建構 LookML 物件」技能徽章入門課程, 即可證明您具備下列技能: 建立新的維度和測量指標、檢視畫面和衍生資料表;根據需求設定測量指標篩選器和類型; 更新維度和測量指標; 建構及調整「探索」;將檢視表彙整至現有「探索」;以及配合業務需求決定要建立哪些 LookML 物件。

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Building a reliable platform for data analysis requires structured data modeling and clean, maintainable code. In this challenge, you’ll start with the building blocks of LookML, creating custom dimensions, measures, and derived tables to shape your data exactly how you need it. From there, you'll work on making your platform faster and easier to use by setting up caching, defining datagroups, and modularizing your code using extends. By following these development best practices, you'll walk away knowing how to build efficient, scalable data models that your team can easily rely on.

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完成 Looker 資料模型管理技能徽章中階課程,即可證明您具備下列技能:維護 LookML 專案的健全性、運用 SQL Runner 驗證資料、採用 LookML 最佳做法、改良查詢及 報表,並執行永久衍生資料表和快取政策。

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