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DHRUV RANE

成为会员时间:2025

黄金联赛

5911 积分
Google Skills Arcade Trivia January 2026 Week 1 Earned Jan 18, 2026 EST
Work Life Refresh Earned Jan 17, 2026 EST
Level 1: Applied Intelligence and Cloud Architecture Earned Dec 25, 2025 EST
AI Infrastructure: Networking Techniques Earned Dec 23, 2025 EST
AI Infrastructure: Storage Options Earned Dec 23, 2025 EST
AI Infrastructure: Deployment Types Earned Dec 23, 2025 EST
AI Infrastructure:Cloud TPU Earned Dec 23, 2025 EST
AI Infrastructure:Cloud GPU Earned Dec 23, 2025 EST
AI Infrastructure:AI Hypercomputer 简介 Earned Dec 23, 2025 EST
Google Cloud 云计算基础课程:Google Cloud 中的数据、机器学习和 AI Earned Dec 23, 2025 EST
Google Sheets - Advanced Topics Earned Jul 16, 2025 EDT
负责任的 AI 简介 Earned Jul 16, 2025 EDT
生成式 AI 简介 Earned Jul 16, 2025 EDT

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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Setting goals is a big part of New Year resolutions—but sustaining a healthy work-life balance is what truly makes them stick. This challenge helps you organize your inbox, manage schedules, collaborate smoothly, and track work efficiently using Google Workspace tools. Start the year with better planning, clearer communication, and workflows that support productivity without burnout.

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Intelligent systems today process everything from scanned invoices to massive data lakes, all while powering apps that users expect to work instantly. Handling that complexity calls for advanced AI, strong governance, and dependable cloud architecture. In this challenge, you’ll extract insights from documents with Document AI, organize and manage distributed data using Dataplex, and secure sensitive information with Cloud KMS. You’ll also deploy containerized apps on Kubernetes Engine, build real-time backends with Firebase, create no-code chat apps with AppSheet, and monitor live activity through Streamlit. These labs show how modern cloud solutions combine intelligence and architecture to stay efficient, secure, and ready for anything.

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Welcome to the "AI Infrastructure: Networking Techniques" course. In this course, you'll learn to leverage Google Cloud's high-bandwidth, low-latency infrastructure to optimize data transfer and communication between all the components of your AI system. By the end, you'll grasp the critical role networking plays across the entire AI pipeline from data ingestion and training to inference and be able to apply best practices to ensure your workloads run at maximum speed.

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In this course, you’ll take a comprehensive journey through the storage solutions available on Google Cloud, specifically tailored for AI and high-performance computing (HPC) workloads. You’ll learn how to choose the right storage for each stage of the ML lifecycle. You’ll explore how to optimize for I/O performance during training, manage massive datasets for data preparation, and serve model artifacts with low latency. Through practical examples and demonstrations, you’ll gain the expertise to design robust storage solutions that accelerate your AI innovation.

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This course provides a comprehensive guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud. Through a series of lessons and practical demonstrations, you’ll explore diverse deployment strategies, ranging from highly customizable environments using Google Compute Engine (GCE) to managed solutions like Google Kubernetes Engine (GKE). Specifically, you’ll learn how to create clusters and deploy GKE for inference.

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欢迎学习 Cloud TPU 课程。我们将探讨 TPU 在不同场景下的优势和劣势,并比较不同的 TPU 加速器,以帮助您选择合适的加速器。您将了解可通过哪些策略充分提高 AI 模型的性能和效率,并理解 GPU/TPU 互操作性对于创建灵活的机器学习工作流程的重要性。通过引人入胜的课程内容和实际演示,您将逐步了解如何有效利用 TPU。

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对 AI 背后的强大硬件感到好奇吗?本单元将详细讲解性能经过优化的 AI 计算机,向您展示它们为何如此重要。我们将探讨 CPU、GPU 和 TPU 如何让 AI 任务高速运行,介绍它们各自的特点,并说明 AI 软件是如何充分发挥这些硬件的性能的。学习结束后,您将清楚地知道如何为自己的 AI 项目选择合适的 GPU,从而为 AI 工作负载做出明智的决策。

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准备好探索 AI Hypercomputer 了吗?这门课程将带您轻松入门!我们将介绍相关基础知识,并阐释它们如何助力 AI 处理 AI 工作负载。您将了解超级计算机内部的各个组件,如 GPU、TPU 和 CPU,并知晓如何根据您的需求选择合适的部署方法。

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Google Cloud 云计算基础课程面向没有或很少有云计算基础或经验的人群。本课程概述了云计算基础知识、大数据和机器学习的核心概念,以及 Google Cloud 在其中的定位与应用方式。 完成本系列课程后,学员将能够清晰阐述这些概念,并掌握一些实际操作技能。 课程应按以下顺序完成: 1. Google Cloud 云计算基础课程:云计算基础知识 2. Google Cloud 云计算基础课程:Google Cloud 中的基础设施 3. Google Cloud 云计算基础课程:Google Cloud 中的网络服务和安全性 4. Google Cloud 云计算基础课程:Google Cloud 中的数据、机器学习和 AI 本课程是该系列课程的最后一门,回顾了托管式大数据服务、机器学习及其价值,以及如何通过获得技能徽章来进一步展示您在 Google Cloud 方面的技能。

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This course builds on some of the concepts covered in the earlier Google Sheets course. In this course, you will learn how to apply and customize themes In Google Sheets, and explore conditional formatting options. You will learn about some of Google Sheets’ advanced formulas and functions. You will explore how to create formulas using functions, and you will also learn how to reference and validate your data in a Google Sheet. Spreadsheets can hold millions of numbers, formulas, and text. Making sense of all of that data can be difficult without a summary or visualization. This course explores the data visualization options in Google Sheets, such as charts and pivot tables. Google Forms are online surveys used to collect data and provide the opportunity for quick data analysis. You will explore how Forms and Sheets work together by connecting collected Form data to a spreadsheet, or by creating a Form from an existing spreadsheet.

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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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