Cloud Out Loud – Multi-Cloud with AI/ML 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:
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How to determine requirements of your Cloud Architecture
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General principles of designing Cloud systems, such as de-coupling, redundancy, load balancing etc.
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Learn about the types of Cloud systems including public, private and hybrid
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Learn what types of services are provided in the cloud – IAAS, PAAS, SAAS, CAAS, FAAS and more.
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Learn AWS from 101 to Solution Architect Professional level
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Learn Google Cloud from 101 to Google Cloud Professional Architect level
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Learn many aspects of Azure Cloud and how it compares to AWS and Google Cloud
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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
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Compare components in the different clouds:
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Database options in AWS vs Azure vs GCP
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File storage and data lake options in the three clouds compared
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Network components compared across all three clouds
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Security issues in the three main clouds (including Zero trust principles)
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Identity and Access Management, Authentication, Authorization and MFA
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Big data – how to implement it in the different clouds
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Data lakes
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Data pipelines/ETL
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Data warehousing
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IOT systems in the different clouds
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Compliance/Governance issues and how to use Cloud components to make Compliance easy
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Explore Hybrid/Multi-cloud architecture issues and migrations
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Learn all about DevOps, CI/CD and DevSecOps – what it is and why you need it for Cloud systems
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How to get certified in AWS, Google Cloud and Azure
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Learn about monitoring, testing and security in all three clouds
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Learn deployment strategies and which meet your needs best
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Learn principles of testing and how to build testing into your CI/CD pipeline effectively
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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
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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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