Udemy – Cloud Out Loud – Multi-Cloud with AI/ML and Big Data

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 Architecture
• General principles of designing Cloud systems, such as de-coupling, redundancy, load balancing etc.
• Learn about the types of Cloud systems including public, private and hybrid
• Learn what types of services are provided in the cloud – IAAS, PAAS, SAAS, CAAS, FAAS and more.
• Learn AWS from 101 to Solution Architect Professional level
• Learn Google Cloud from 101 to Google Cloud Professional Architect level
• Learn many aspects of Azure Cloud and how it compares to AWS and Google Cloud
• Reference architectures for many application types in AWS, Azure and GCP and how to determine the best components in those architectures to meet your requirements
• Compare components in the different clouds:
  • Database options in AWS vs Azure vs GCP
  • File storage and data lake options in the three clouds compared
  • Network components compared across all three clouds
  • Security issues in the three main clouds (including Zero trust principles)
  • Identity and Access Management, Authentication, Authorization and MFA
  • Data lakes
  • Data pipelines/ETL
  • Data warehousing

  PLEASE 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.