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Arpit Kumar Garg

成为会员时间:2021

青铜联赛

3818 积分
Build search and recommendations applications with AI Applications Earned Dec 11, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned May 25, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned May 20, 2023 EDT
Preparing for your Professional Data Engineer Journey Earned May 12, 2023 EDT
Migration Summit 2022 Earned Jul 24, 2022 EDT
Architecting with Google Kubernetes Engine: Production Earned Jul 17, 2022 EDT
Architecting with Google Kubernetes Engine: Workloads Earned Jul 9, 2022 EDT
Architecting with Google Kubernetes Engine: Foundations - 简体中文 Earned Jul 3, 2022 EDT
Google Cloud 弹性基础设施:扩缩和自动化 Earned Nov 15, 2021 EST
开发 Google Cloud 网络 Earned Oct 28, 2021 EDT
Google Cloud 重要基础设施:核心服务 Earned Oct 22, 2021 EDT
为 Compute Engine 实现云负载均衡 Earned Oct 19, 2021 EDT
Google Cloud 重要基础设施:基础 Earned Oct 13, 2021 EDT
Google Cloud 基础知识:核心基础设施 Earned Oct 7, 2021 EDT

Complete the Build search and recommendations AI Applications skill badge to demonstrate your proficiency in deploying search and recommendation applications through AI Applications. Additionally, emphasis is placed on constructing a tailored Q&A system utilizing data stores. Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

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The GSI Migration Summit is a curated collection of hands-on labs and quests that provide coverage of infrastructure, data, and application migration. Security and analytics labs and quests have been added to provide coverage of key platform concepts and services.

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In this course, you'll learn about Kubernetes and Google Kubernetes Engine (GKE) security; logging and monitoring; and using Google Cloud managed storage and database services from within GKE. This is the second course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Reliable Google Cloud Infrastructure: Design and Process course or the Hybrid Cloud Infrastructure Foundations with Anthos course.

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In "Architecting with Google Kubernetes Engine- Workloads", you'll embark on a comprehensive journey into cloud-native application development. Throughout the learning experience, you'll explore Kubernetes operations, deployment management, GKE networking, and persistent storage. This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine- Production course.

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在本课程“Google Kubernetes Engine 架构设计:基础知识”中,您将了解 Google Cloud 的概况和原理,然后学习如何创建和管理软件容器,以及了解 Kubernetes 的架构。 这是“Google Kubernetes Engine 架构设计”系列课程的第一门课程。完成本课程后,请报名参加“Google Kubernetes Engine 架构设计:工作负载”课程。

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这是一套自助式速成课程,向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务。学员将通过一系列视频讲座、演示和实操实验,探索和部署各种解决方案元素,包括安全互连网络、负载均衡、自动扩缩、基础架构自动化和代管式服务。

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完成开发 Google Cloud 网络课程,赢取技能徽章。在此课程中,您将学习 部署和监控应用的多种方法,包括执行以下任务的方法:探索 IAM 角色并添加/移除 项目访问权限、创建 VPC 网络、部署和监控 Compute Engine 虚拟机、 编写 SQL 查询、在 Compute Engine 中部署和监控虚拟机,以及使用 Kubernetes 通过多种部署方法部署应用。

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这门自助式速成课程向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务,着重介绍了 Compute Engine。学员将通过一系列视频讲座、演示和动手实验,探索和部署各种解决方案元素,包括网络、系统和应用服务等基础架构组件。本课程的内容还包括如何部署实用的解决方案,包括客户提供的加密密钥、安全和访问权限管理、配额和结算,以及资源监控。

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完成入门级技能徽章课程为 Compute Engine 实现云负载均衡,展示以下方面的技能: 在 Compute Engine 中创建和部署虚拟机 以及配置网络和应用负载均衡器。

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这门自助式速成课程向学员介绍 Google Cloud 提供的灵活全面的基础架构和平台服务,其中着重介绍了 Compute Engine。学员将通过一系列视频讲座、演示和动手实验,探索和部署各种解决方案元素,包括网络、虚拟机和应用服务等基础架构组件。您将学习如何通过控制台和 Cloud Shell 使用 Google Cloud。您还将了解云架构师角色、基础架构设计方法以及虚拟网络配置和虚拟私有云 (VPC)、项目、网络、子网、IP 地址、路由及防火墙规则。

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“Google Cloud 基础知识:核心基础设施”介绍在使用 Google Cloud 时会遇到的重要概念和术语。本课程通过视频和实操实验来介绍并比较 Google Cloud 的多种计算和存储服务,并提供重要的资源和政策管理工具。

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