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Hey there! You're invited to game on with Skills Boost Arcade Trivia for September 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 September Trivia Week 1 badge!
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Get hands-on with the core tools behind modern app development on Google Cloud. Start by exploring Artifact Registry to securely store, organize, and manage your container images and packages. You’ll explore key tasks like setting up repositories, configuring authentication, applying tags, and automating cleanups. Then, transition to Cloud Run to deploy stateless, containerized applications with ease. Learn how to work with environment variables, manage secrets, control traffic, and build scalable, event-driven services and earn an exclusive Google Cloud Credential!
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This challenge is designed to help you get comfortable working with data across tools like Google Sheets, BigQuery, Looker, and even Google Docs. You’ll start by learning how to find, filter, and visualize data in Sheets, and run quick-start projects using Pub/Sub, BigQuery, Dataplex, and Cloud Filestore from the command line. From there, you’ll dive deeper—writing SQL to explore real-world datasets, spotting common query errors, and troubleshooting data models in Looker. You’ll also pick up best practices to make your LookML projects easier to use and maintain. Whether you're just exploring or solving tricky issues, these labs give you the practical skills to work smarter with your data.
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This set of labs is all about helping you get hands-on with Looker and Google Cloud to turn raw data into clear, useful insights. You’ll learn how to build and organize your data models using LookML, create custom metrics and dimensions, and use derived tables to clean and shape your data. Along the way, you'll explore best practices like modularizing your code and improving query performance with caching and datagroups. Once the data’s in shape, you’ll move into Looker Studio to build reports, schedule dashboards, and set up alerts—making it easier to share what matters with your team.
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隨著企業持續擴大使用人工智慧和機器學習，以負責任的方式發展相關技術也日益重要。對許多企業來說，談論負責任的 AI 技術可能不難，如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術，本課程絕對能助您一臂之力。
您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談，協助貴機構奠定良好基礎，實踐負責任的 AI 技術。
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這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。
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這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。
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這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。
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Skills Boost Arcade Trivia September 2025 Week 1
Earned Sep 18, 2025 EDT
Level 3: Building Blocks
Earned May 26, 2025 EDT
Level 2: Data Exploration and Integration
Earned May 26, 2025 EDT
Level 1: Data Modeling and Reporting
Earned May 22, 2025 EDT
負責任的 AI 技術：透過 Google Cloud 採用 AI 開發原則
Earned Oct 28, 2024 EDT
負責任的 AI 技術簡介
Earned Oct 28, 2024 EDT
大型語言模型簡介
Earned Oct 28, 2024 EDT
生成式 AI 簡介
Earned Oct 28, 2024 EDT