Cloud Out Loud - Multi-Cloud With Ai/ml And Big Data
 

AWS, Azure and GCP - Including AI/ML and Big Data - To Professional Architect Level
What you'll learn
AWS 101 to Architect Level
Google Cloud 101 to Architect Level
Azure 101 to Architect Level
Multi Cloud
Comparing the Clouds - AWS, Azure and GCP compared
Docker, Kubernetes and More
Useful Software/IT tools, guides, ebooks and information
Amazon AWS
Cloud Computing
Data Analytics, Big Data and AI/ML
Requirements
Updated 12/21/2023! Now with ML and AI content! Big Data for AI and ML content!
Anyone is welcome to learn!
Ideal for those who work in IT or Software who want to learn the cloud. Anyone can take the course but those with no IT/Software background may struggle
Description
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.
Who this course is for
Anyone who wants to learn all about the Cloud. All three clouds Amazon AWS, Google Cloud, Azure
From beginner to Solution Architect Professional in all three main cloud computing environments