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.

Overview

Section 1: Introduction

Lecture 1 Introduction to Cloud Out Loud

Lecture 2 Introduction to Cloud Architectures

Lecture 3 Cloud architectures - principles

Lecture 4 Introduction to Cloud Architectures - Resources

Section 2: Google Cloud

Lecture 5 Google Cloud 101

Lecture 6 Google Cloud Intro Lab Session

Lecture 7 Google Cloud - Next Steps

Lecture 8 Google Cloud In Depth

Lecture 9 Lecture 10: Google Cloud Pricing and Costing

Lecture 10 Google Cloud - more lectures and resources

Lecture 11 More on Google Cloud

Lecture 12 Google Cloud Other Resources - Migration, presentations etc

Section 3: AWS

Lecture 13 AWS Professional Solution Architect Training

Lecture 14 Intro to AWS

Lecture 15 AWS and Azure

Section 4: Section 4: Azure

Lecture 16 Azure Part 1

Lecture 17 Azure Part 2

Section 5: Section 5: Multi Cloud

Lecture 18 Aws, Azure and GCP Compared and what they have in common (Skip this if seen)

Lecture 19 Azure and AWS

Lecture 20 More on AWS and Azure

Lecture 21 Multi-cloud resources and information

Lecture 22 Multi Cloud

Lecture 23 Big Data

Lecture 24 Migrating to Multi Tenant Architectures

Section 6: Selecting Components in Multi-Cloud/Hybrid Environments

Lecture 25 1a Azure Choosing Components

Lecture 26 1b AWS Choosing Components

Lecture 27 Best Practices for Streaming (Components) in Multi-Cloud and Hybrid Environments

Lecture 28 Best Practices for API (Components) in Multi-Cloud/Hybrid environments

Lecture 29 Best Practices for Virtualization (Components) in Multi-Cloud/Hybrid Environment

Lecture 30 Best Practices for Data Sinks/Sources (Components) in Multi-Cloud/Hybrid

Section 7: DevSecOps in the Cloud

Lecture 31 Introduction to DevSecOps in the Cloud

Lecture 32 Introduction to DevSecOps in the Cloud

Lecture 33 Testing in the Cloud

Lecture 34 Microservices - an introduction

Lecture 35 Docker in the Cloud

Section 8: Useful stuff to help you building in the cloud

Lecture 36 Monitoring

Lecture 37 Some extra resources that may help

Section 9: Big Data

Lecture 38 Big Data Fireside Chat

Lecture 39 Data In the Cloud

Section 10: How to get work in the Cloud or in the Software Industry

Lecture 40 How to get work in the Cloud / Software / IT

Lecture 41 LinkedIn Profiles and how to use them

Section 11: Big Data, AI and ML in the cloud

Lecture 42 Big Data, AI and ML in the cloud

Lecture 43 Big Data, AI and ML in the cloud part 2

Lecture 44 Big Data, AI and ML in the cloud part 3

Lecture 45 Data In the Cloud

Lecture 46 Big Data AI and ML in the cloud - full course

Lecture 47 AI and ML Governance and Ethics

Lecture 48 AI Comparison - ChatGPT vs Gemini latest versions

Section 12: Intro to the Cloud (for beginners) - Skip this section if you know the basics

Lecture 49 Everyone is welcome here

Lecture 50 Our mission here

Lecture 51 What is the Cloud?

Lecture 52 Cloud Providers

Lecture 53 IAAS, PAAS and SAAS

Lecture 54 Databases in the Cloud

Lecture 55 Big Data in the Cloud

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