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Everything Under the Cloud - AI,ML,certs,data, infra,etc.

Name: Everything Under the Cloud - AI,ML,certs,data, infra,etc.
Rating: 4.8 (26 reviews)

All about AI, GenAI, Machine Learning, AWS, Azure and GCP - To Professional Architect Level

Created byMichelle Sollicito

Last updated 10/2026

English

English [Auto],

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
Google AI. AI Studio. Gemini Notebook Antigravity. Gemini enterprise GECX GEAP
Machine Learning Python Jupyter Notebooks

Course content

14 sections • 66 lectures • 33h 36m total length

Introduction to Cloud Out Loud1:04:48
Introduction to the course and to Michelle Sollicito.
Michelle Sollicito has 35+ years experience in the Software industry and is an AWS Solution Architect Professional as well as being certified in AWS Security specialty and AWS Data analytics specialty. She is also a Google Certified Professional Architect. She has a number of years experience in Microsoft technologies including 2 years in Azure Cloud, and is certified in Azure, C#, .Net and SQL Server 2014. She is also certified in many other technologies.
Michelle is a big proponent of Diversity Equity and Inclusion, hence the rainbow on the logo. Michelle has a meetup group for Out Loud Cloud proponents to learn all about the cloud and a meetup group called WITCHES allowing women to learn all about the Cloud. See resources.
Introduction to Cloud Architectures51:25
This lecture takes you through some of the resources in lecture 4 - please make sure you see ALL the resources in ALL the lectures - as I think some of the best content is in the Resources!
Cloud architectures - principles41:03
Cloud Architectures in a little more depth - mostly Google Cloud but covers others also
Introduction to Cloud Architectures - Resources0:19
This section has a number of resources that are useful to those looking at Cloud architectures or multi-cloud architectures.
Quiz 1: Architectures

Google Cloud 10132:01
Please note that this course consists of many lectures. Some of the lectures may seem to repeat the content of other lectures but my students find that hearing the same content in different ways helps with learning that content more fully. Part 1 is an introduction to the components in Google Cloud
Google Cloud 101
Google Cloud Intro Lab Session22:29
An intro session to all things Google Cloud
Google Cloud - Next Steps23:47
Part 2 goes into a little more depth in Google Cloud
Google Cloud - Next Steps - Quiz
Google Cloud In Depth38:59
Explore Google Cloud services, including Vertex AI, Firestore, Data Store, Cloud Run, App Engine, and Pub/Sub, and learn to design AI and big data architectures for multi-cloud.
Lecture 10: Google Cloud Pricing and Costing32:03
Discover Google Cloud cost optimization using billing tools and the pricing calculator, optimize data and storage costs with lifecycle policies, and apply discounts, quotas, and budget alerts.
Google Cloud - more lectures and resources0:10
More on Google Cloud41:03
Explore Google Cloud architectures for multi-cloud AI/ML and big data, using IaaS, PaaS, and SaaS, data pipelines, and tools like Pub/Sub, Dataflow, BigQuery, Looker, and Vertex AI.
Google Cloud Other Resources - Migration, presentations etc0:02
Quiz 4: Google Cloud Advanced

AWS Professional Solution Architect Training1:19:03
Navigate AWS certification paths from foundation to pro, with guidance, practice exams, and official resources to pass the solution architect professional. Learn IaaS, PaaS, SaaS concepts and AWS compute basics.
Intro to AWS38:24
Please note that this course consists of many lectures. Some of the lectures may seem to repeat the content of other lectures but my students find that hearing the same content in different ways helps with learning that content more fully.
AWS and Azure1:54:54
Navigate multi-cloud messaging, workflows, and serverless architectures across AWS, Azure, and GCP, compare hybrid and on-prem solutions, and plan a DevOps-driven migration from monoliths to microservices with infrastructure as code.
AWS Architecture quiz

Aws, Azure and GCP Compared and what they have in common (Skip this if seen)1:38:07
Round table about AWS Azure and GCP - multi cloud
Azure and AWS1:54:54
An introduction to AWS and Azure
More on AWS and Azure38:24
Mainly about AWS with some Azure
Multi-cloud resources and information0:01
This section has a number of resources that are useful to those looking at Cloud architectures or multi-cloud architectures.
Multi Cloud0:02
Coming soon..
Big Data3:26
Big Data - Big Volume, Big Variety and Big Velocity are the three main characteristics that may make your project a Big Data project. Learn here about Data Lakes, Data Warehouses and Data Lake Houses. Learn about Apache tools like Hadoop, HDFS, Spark, Hive, Pig etc.
AWS implements Hadoop as an option in EMR (Elastic Map Reduce/HDFS). It is possible to use Hive, Pig, Spark etc. in that environment, see here:

https://aws.amazon.com/emr/features/hadoop/

Here is a great overview of the Apache Hadoop overall architecture:

https://www.bizety.com/2020/06/20/hadoop-ecosystem-mapreduce-yarn-hive-pig-spark-oozie-zookeeper-mahout-and-kube2hadoop/
Migrating to Multi Tenant Architectures14:06
Migrate from a siloed monolith to a multi-tenant web architecture by automating tenant provisioning, per-tenant VPC, onboarding, and microservices with containers, lambdas, and JWT context.

1a Azure Choosing Components30:13
Learn to decide Azure deployment options, migrate or build, and choose data sources like Cosmos DB, Azure SQL Database, Azure Table Storage, blob storage, data lake, and Azure Synapse Analytics.
1b AWS Choosing Components29:02
Explore AWS compute options from Lambda to SageMaker using a decision tree. Identify container, EC2, and managed service paths, plus analytics and database choices like Athena, Redshift, DynamoDB.
Best Practices for Streaming (Components) in Multi-Cloud and Hybrid Environments49:32
Best Practices for API (Components) in Multi-Cloud/Hybrid environments29:14
Learn architectures for API creation and management across multi-cloud and on-prem, including gateway and management options like AWS API Gateway, Azure Application Gateway with API Management, and IBM API Connect.
Best Practices for Virtualization (Components) in Multi-Cloud/Hybrid Environment26:17
Learn virtualization practices across multi-cloud and hybrid environments, comparing architectures and tools like Redshift Spectrum, PolyBase, Delta Lake, Synapse, Databricks, Hudi, and one lake and fabric for fast data access.
Best Practices for Data Sinks/Sources (Components) in Multi-Cloud/Hybrid1:16:09
Explore best practices for data sinks and sources across multi-cloud and hybrid environments, including data lakes, data warehouses, Delta Lake, data fabric, data lake house, and data mesh.

Introduction to DevSecOps in the Cloud6:35
Explore DevSecOps resources in the cloud, covering Python for functions, Git for source control, and Terraform for infrastructure as code. Understand containers, Kubernetes, and unit-to-security testing.
Introduction to DevSecOps in the Cloud0:15
This section has a number of resources that are useful to those looking at DevSecOps in the Cloud including cheat sheets and docs on git, python, terraform etc.
Testing in the Cloud0:08
Microservices - an introduction15:23
Explore microservices designed as small, self-contained units that own a single business entity, deploy independently, are loosely coupled and stateless, REST-based, testable, and supported by two-pizza teams.
Docker in the Cloud2:05
Troubleshoot docker in the cloud by enabling docker desktop with elevated privileges and Hyper-V containers. Use lowercase names, avoid spaces, and keep directory paths consistent to prevent errors.

How to get work in the Cloud / Software / IT49:22
Clarify your cloud career goals, build targeted skills and certifications, craft long and short resumes and LinkedIn profiles, and actively network and apply through recruiters and freelance platforms.
LinkedIn Profiles and how to use them37:59
Learn how to leverage LinkedIn profiles to showcase your subject-area courses and ebooks, refactor your skills for cloud and modern tech roles, and use content creation to attract opportunities.

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

Now updated with info about:

Gemini Enterprise,
GEAP (Gemini Enterprise AI Platform - used to be Vertex AI),
Agent Gateway,
Gemini Argon 4,
AIStudio,
Antigravity,
Claude Fable,
Azure Fabric AI,
OpenClaw, OpenShell etc.

Pass AI Certs like:

Google Generative AI Leader (GAIL)
Google Agentic Architect
Google Machine Learning Engineer
Google Professional Architect
AWS Certified Solutions Architect – Professional
AWS Security Specialty
AWS Data Analytics Specialty
Azure (Fabric|Databricks) Data Engineer
Azure Administrator
Azure Solutions Architect Expert and DevOps Engineer Expert * most content is here

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/AI 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

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.

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

Everything Under the Cloud - AI,ML,certs,data, infra,etc.

What you'll learn

Explore related topics

Course content

Introduction4 lectures • 2hr 38min

Google Cloud8 lectures • 3hr 11min

AWS3 lectures • 3hr 52min

Section 4: Azure3 lectures • 3hr 17min

Section 5: Multi Cloud7 lectures • 4hr 29min

Selecting Components in Multi-Cloud/Hybrid Environments6 lectures • 4hr

DevSecOps in the Cloud5 lectures • 24min

Useful stuff to help you build in the cloud2 lectures • 1min

Big Data2 lectures • 49min

How to get work in the Cloud or in the Software Industry2 lectures • 1hr 27min

Requirements

Description

Who this course is for: