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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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随着企业对人工智能和机器学习的应用越来越广泛，以负责任的方式构建这些技术也变得更加重要。但对很多企业而言，真正践行 Responsible AI 并非易事。如果您有意了解如何在组织内践行 Responsible AI，本课程正适合您。
本课程将介绍 Google Cloud 目前如何践行 Responsible AI，以及从中总结的最佳实践和经验教训，便于您以此为框架构建自己的 Responsible AI 方法。
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这是一节入门级微课程，旨在解释什么是负责任的 AI、它的重要性，以及 Google 如何在自己的产品中实现负责任的 AI。此外，本课程还介绍了 Google 的 7 个 AI 开发原则。
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这是一节入门级微学习课程，探讨什么是大型语言模型 (LLM)、适合的应用场景以及如何使用提示调整来提升 LLM 性能，还介绍了可以帮助您开发自己的 Gen AI 应用的各种 Google 工具。
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这是一节入门级微课程，旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。
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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
Responsible AI: 和 Google Cloud 一起践行 AI 原则
Earned Oct 28, 2024 EDT
负责任的 AI 简介
Earned Oct 28, 2024 EDT
大型语言模型简介
Earned Oct 28, 2024 EDT
生成式 AI 简介
Earned Oct 28, 2024 EDT