Cloud Out Loud Multi-Cloud with AIML and Big Data

Cloud Out Loud – Multi-Cloud with AI/ML and Big Data, available at $39.99, has an average rating of 4.8, with 60 lectures, 5 quizzes, based on 22 reviews, and has 342 subscribers.

You will learn about 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 This course is ideal for individuals who are Anyone who wants to learn all about the Cloud. All three clouds Amazon AWS, Google Cloud, Azure or From beginner to Solution Architect Professional in all three main cloud computing environments It is particularly useful for Anyone who wants to learn all about the Cloud. All three clouds Amazon AWS, Google Cloud, Azure or From beginner to Solution Architect Professional in all three main cloud computing environments.

Enroll now: Cloud Out Loud – Multi-Cloud with AI/ML and Big Data

Summary

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

Price: $39.99

Average Rating: 4.8

Number of Lectures: 60

Number of Quizzes: 5

Number of Published Lectures: 46

Number of Published Quizzes: 5

Number of Curriculum Items: 65

Number of Published Curriculum Objects: 51

Original Price: $39.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

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

Target Audiences

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

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

Big data – how to implement it in the different clouds

Data lakes

Data pipelines/ETL

Data warehousing

IOT systems in the different clouds

Compliance/Governance issues and how to use Cloud components to make Compliance easy

Explore Hybrid/Multi-cloud architecture issues and migrations

Learn all about DevOps, CI/CD and DevSecOps – what it is and why you need it for Cloud systems

How to get certified in AWS, Google Cloud and Azure

Learn about monitoring, testing and security in all three clouds

Learn deployment strategies and which meet your needs best

Learn principles of testing and how to build testing into your CI/CD pipeline effectively

Plus many Tools, tricks, ebooks, links and other sources of information about the cloud

Course Curriculum

Chapter 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

Chapter 2: Google Cloud

Lecture 1: Google Cloud 101

Lecture 2: Google Cloud Intro Lab Session

Lecture 3: Google Cloud – Next Steps

Lecture 4: Google Cloud In Depth

Lecture 5: Lecture 10: Google Cloud Pricing and Costing

Lecture 6: Google Cloud – more lectures and resources

Lecture 7: More on Google Cloud

Lecture 8: Google Cloud Other Resources – Migration, presentations etc

Chapter 3: AWS

Lecture 1: AWS Professional Solution Architect Training

Lecture 2: Intro to AWS

Lecture 3: AWS and Azure

Chapter 4: Section 4: Azure

Lecture 1: Azure Part 1

Lecture 2: Azure Part 2

Chapter 5: Section 5: Multi Cloud

Lecture 1: Aws, Azure and GCP Compared and what they have in common (Skip this if seen)

Lecture 2: Azure and AWS

Lecture 3: More on AWS and Azure

Lecture 4: Multi-cloud resources and information

Lecture 5: Multi Cloud

Lecture 6: Big Data

Lecture 7: Migrating to Multi Tenant Architectures

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

Lecture 1: 1a Azure Choosing Components

Lecture 2: 1b AWS Choosing Components

Lecture 3: Best Practices for Streaming (Components) in Multi-Cloud and Hybrid Environments

Lecture 4: Best Practices for API (Components) in Multi-Cloud/Hybrid environments

Lecture 5: Best Practices for Virtualization (Components) in Multi-Cloud/Hybrid Environment

Lecture 6: Best Practices for Data Sinks/Sources (Components) in Multi-Cloud/Hybrid

Chapter 7: DevSecOps in the Cloud

Lecture 1: Introduction to DevSecOps in the Cloud

Lecture 2: Introduction to DevSecOps in the Cloud

Lecture 3: Testing in the Cloud

Lecture 4: Microservices – an introduction

Lecture 5: Docker in the Cloud

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

Lecture 1: Monitoring

Lecture 2: Some extra resources that may help

Chapter 9: Big Data

Lecture 1: Big Data Fireside Chat

Lecture 2: Data In the Cloud

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

Lecture 1: How to get work in the Cloud / Software / IT

Lecture 2: LinkedIn Profiles and how to use them

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

Lecture 1: Big Data, AI and ML in the cloud

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

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

Lecture 4: Big Data AI and ML in the cloud – full course

Lecture 5: AI and ML Governance and Ethics

Instructors

Michelle Sollicito
Software Consultant/Architect

Rating Distribution

1 stars: 0 votes

2 stars: 0 votes

3 stars: 0 votes

4 stars: 8 votes

5 stars: 14 votes

Frequently Asked Questions

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