|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/cloud-out-loud/
课程评论：没有评论
课程名称：Cloud Out Loud - 多云环境下的人工智能/机器学习与大数据 课程概述： 本课程旨在帮助学习者掌握三大主要云平台（AWS、Azure和Google Cloud）的专业架构知识，特别适合初学者或希望成为多云专家的人士。课程内容涵盖了云中的人工智能和机器学习，以及大数据和数据分析在这些领域的重要性。 学习内容包括： - 云架构需求的确定方法 - 云系统设计的基本原则，如解耦、冗余、负载均衡等 - 各类云系统的类型，包括公有云、私有云和混合云 - 云服务的种类，涵盖IAAS、PAAS、SAAS、CAAS和FAAS等 - 从基础到解决方案架构师的AWS学习 - 从基础到Google Cloud专业架构师的学习 - Azure云平台的多个方面及其与AWS和Google Cloud的比较 - 提供针对AWS、Azure和GCP的多种应用类型的参考架构 - 比较不同云中的组成部分，如数据库选择、文件存储和数据湖选项、网络组件 - 三大云中的安全问题（包括零信任原则）、身份和访问管理、认证、授权和多因素认证 - 如何在不同云中实施大数据，包括数据湖、数据管道/ETL和数据仓库 - 各种云中的物联网系统 - 合规性/治理问题及如何使用云组件简化合规过程 - 探索混合/多云架构问题及迁移 - 了解DevOps、CI/CD及DevSecOps的概念及其在云系统中的重要性 - 如何获得AWS、Google Cloud和Azure的认证 - 学习三大云中的监控、测试和安全策略 - 理解部署策略及其对您需求的适配 - 测试原理及如何有效地将测试集成到CI/CD管道中 此外，课程还提供众多工具、技巧、电子书、链接及其他关于云的信息资源。 请注意，内容的创建时间早于我目前在Google Cloud的就业时间，特此告知以符合公司政策。
Featuring:- The three main clouds to Professional Architect level - AWS, Azure and Google Cloud- AI and ML in the cloud (and why Big Data/Data Analytics is so important for AI and ML)- Cloud decision tree for AWS and for Azure! Perfect for beginners - or those who know one cloud and wish to become multi-cloud experts! Learn about:How to determine requirements of your Cloud ArchitectureGeneral principles of designing Cloud systems, such as de-coupling, redundancy, load balancing etc.Learn about the types of Cloud systems including public, private and hybridLearn what types of services are provided in the cloud - IAAS, PAAS, SAAS, CAAS, FAAS and more.Learn AWS from 101 to Solution Architect Professional levelLearn Google Cloud from 101 to Google Cloud Professional Architect levelLearn many aspects of Azure Cloud and how it compares to AWS and Google CloudReference architectures for many application types in AWS, Azure and GCP and how to determine the best components in those architectures to meet your requirementsCompare components in the different clouds:Database options in AWS vs Azure vs GCPFile storage and data lake options in the three clouds comparedNetwork components compared across all three cloudsSecurity issues in the three main clouds (including Zero trust principles)Identity and Access Management, Authentication, Authorization and MFABig data - how to implement it in the different clouds Data lakesData pipelines/ETLData warehousingIOT systems in the different cloudsCompliance/Governance issues and how to use Cloud components to make Compliance easyExplore Hybrid/Multi-cloud architecture issues and migrationsLearn all about DevOps, CI/CD and DevSecOps - what it is and why you need it for Cloud systemsHow to get certified in AWS, Google Cloud and AzureLearn about monitoring, testing and security in all three cloudsLearn deployment strategies and which meet your needs bestLearn principles of testing and how to build testing into your CI/CD pipeline effectivelyPlus many Tools, tricks, ebooks, links and other sources of information about the cloudPLEASE NOTE that I am now employed by Google Cloud! This content was created before I became employed by Google Cloud but I have to make sure you know I am employed by Google Cloud at this point so that you are aware, as it is company policy.
