The Self-Taught Cloud Computing Engineer: A comprehensive professional study guide to AWS, Azure, and GCP

Transform into a cloud-savvy professional by mastering cloud technologies through hands-on projects and expert guidance, paving the way for a thriving cloud computing career

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Key Features

• Gain a solid foundation in cloud computing with a structured, easy-to-follow guide
• Develop practical skills across AWS, Azure, and Google Cloud, covering compute, storage, networking, data, security, and AI
• Work on real life industrial projects, business use cases, and personal cloud career development

Book Description

As cloud computing continues to revolutionize IT, professionals face the challenge of keeping up with rapidly evolving technologies. This book provides a clear roadmap for mastering cloud concepts, developing hands-on expertise, and obtaining professional certifications, making it an essential resource for those looking to advance their careers in cloud computing.

Starting with a focus on the Amazon cloud, you’ll be introduced to fundamental AWS cloud services, followed by advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds, differentiating their unique features, along with leveraging real-life cloud project implementations on these cloud platforms. Through hands-on projects and real-world applications, you’ll gain the skills needed to work confidently across different cloud platforms. The book concludes with career development guidance, including certification paths and industry insights to help you succeed in the cloud computing landscape.

Walking through this cloud computing book, you’ll systematically establish a robust footing in AWS, Azure, and GCP, and emerge as a cloud-savvy professional, equipped with cloud certificates to validate your skills.

What you will learn

• Develop core skills needed to work with AWS, Azure, and GCP
• Gain proficiency in compute, storage, and networking services across multi-cloud and hybrid-cloud environments
• Integrate cloud databases, big data, and machine learning services in multi-cloud environments
• Design and develop data pipelines, encompassing data ingestion, storage, processing, and visualization in the clouds
• Implement machine learning pipelines in multi-cloud environment
• Secure cloud infrastructure ecosystems with advanced cloud security services

Who this book is for

This book is ideal for IT professionals looking to transition into cloud computing, as well as experienced cloud practitioners seeking to deepen their knowledge. Whether you're a beginner with basic computing experience or an industry professional aiming to expand your expertise, this comprehensive guide provides the skills and insights needed to excel in the cloud domain.

Table of Contents

1. Amazon EC2 and Cloud Compute Services
2. Amazon Cloud Storage Services
3. Amazon Cloud Networking Services
4. Amazon Cloud Database Services
5. Amazon Cloud Big Data Services
6. Amazon Cloud Machine Learning Services
7. Amazon Cloud Security Services
8. Google Cloud Foundation Services
9. Google Cloud Data Services
10. Google Cloud AI Services
11. Google Cloud Security Services
12. Azure Cloud Foundation Services
13. Azure Cloud Data Services
14. Azure Cloud AI Services
15. Azure Cloud Security Services
16. Achieving Cloud Certifications
17. Building a Successful Cloud Computing Career

Dr. Logan Song is the enterprise cloud director and chief cloud architect at Dito. With 25+ years of professional experience, Dr. Song is highly skilled in enterprise information technologies, specializing in cloud computing and machine learning. He is a Google Cloud-certified professional solution architect and machine learning engineer, an AWS-certified professional solution architect and machine learning specialist, and a Microsoft-certified Azure solution architect expert. Dr. Song holds a Ph.D. in industrial engineering, an MS in computer science, and an ME in management engineering. Currently, he is also an adjunct professor at the University of Texas at Dallas, teaching cloud computing and machine learning courses.