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Lahar Solanki

Member since 2025

Bronze League

2347 points
使用 AppSheet 建構應用程式 Earned Jul 26, 2026 EDT
搭配使用 API 和 Cloud Storage Earned Jul 24, 2026 EDT
Arcade Voyage: Cloud Storage and Data Governance Earned Jul 24, 2026 EDT
找出並保護生態系統中的敏感資料 Earned Jul 19, 2026 EDT
在 Looker 建構 LookML 物件 Earned Jun 29, 2026 EDT
Logic Log Earned Jun 29, 2026 EDT
Looker 資料模型管理 Earned Jun 28, 2026 EDT
Build Global and Regional Load Balancing Solutions Earned Jun 27, 2026 EDT
Arcade Base Camp June 2026 Earned Jun 27, 2026 EDT
在 Compute Engine 導入 Cloud Load Balancing Earned Jun 14, 2026 EDT
Arcade Trail: Data Engineering and Information Protection Earned Jun 11, 2026 EDT
使用預訓練 API 實現語音和語言解決方案 Earned Jun 8, 2026 EDT
Arcade Voyage: Identity Management and Pre-trained AI APIs Earned Jun 8, 2026 EDT
為 Google Cloud 設定服務帳戶和 IAM 角色 Earned Jun 8, 2026 EDT
透過 Google Cloud Observability 監控及記錄系統狀態 Earned Jun 3, 2026 EDT
Arcade Adventure: App Dev and Cloud Observability Earned Jun 3, 2026 EDT
在 Google Cloud 設定應用程式開發環境 Earned Jun 2, 2026 EDT
Arcade Adventure: Modern App Deployment Earned May 31, 2026 EDT
Arcade Voyage: Data Governance and Firebase Foundations Earned May 29, 2026 EDT
Google Cloud Compute 基本操作 Earned May 22, 2026 EDT
Arcade Base Camp May 2026 Earned May 22, 2026 EDT
Google Skills Arcade Trivia January 2026 Week 1 Earned Jan 25, 2026 EST
在 Google Cloud 為機器學習 API 準備資料 Earned Dec 31, 2025 EST
機器學習運作 (MLOps) 與 Vertex AI：模型評估 Earned Dec 8, 2025 EST
Gemini 和 Imagen 實務應用：建構 AI 應用程式 Earned Dec 8, 2025 EST
生成式 AI 適用的機器學習運作 (MLOps) Earned Dec 8, 2025 EST

完成使用 AppSheet 建構應用程式課程，即可獲得技能徽章 ，瞭解如何使用 AppSheet 建構、設定及發布應用程式。

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完成「搭配使用 API 和 Cloud Storage」 技能徽章入門課程，即可證明您具備下列技能： 搭配使用 API 和 Cloud Storage 資源，包括 Cloud Storage API。

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Data is one of the most valuable assets an organization owns, making its safe handling and governance essential. In this voyage, you will master Cloud Storage fundamentals by automating bucket management via APIs and the CLI, while enforcing compliance with Bucket Lock. You will then advance to automated security, configuring Sensitive Data Protection Discovery to scan and catalog risks across BigQuery and Cloud Storage. Complete with two challenge labs, this journey equips you to secure assets across your entire cloud ecosystem.

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完成「找出並保護生態系統中的敏感資料」 技能徽章中階課程，證明您具備下列技能：使用 Sensitive Data Protection 服務 (包括 Cloud Data Loss Prevention (DLP) API) 來探索、檢查、遮蓋及去識別化 Google Cloud 生態系統的敏感資料，包括 Cloud Storage 檔案、BigQuery 資料和生成式 AI 模型回覆。

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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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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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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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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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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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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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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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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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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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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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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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Hey there! You're invited to game on with Google Skills Arcade Trivia for January Week 1! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the January Trivia Week 1 badge!

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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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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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完成「Gemini 和 Imagen 實務應用：建構 AI 應用程式」技能徽章入門課程，即可證明您具備下列技能：圖片辨識、自然語言處理、 使用 Google 強大的 Gemini 和 Imagen 模型生成圖片，以及在 Vertex AI 平台上部署應用程式。

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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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