Book Image

The Self-Taught Cloud Computing Engineer

By : Dr. Logan Song
Book Image

The Self-Taught Cloud Computing Engineer

By: Dr. Logan Song

Overview of this book

The Self-Taught Cloud Computing Engineer is a comprehensive guide to mastering cloud computing concepts by building a broad and deep cloud knowledge base, developing hands-on cloud skills, and achieving professional cloud certifications. Even if you’re a beginner with a basic understanding of computer hardware and software, this book serves as the means to transition into a cloud computing career. Starting with the Amazon cloud, you’ll explore the fundamental AWS cloud services, then progress to 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 while distinguishing their unique features. You’ll further enhance your skills through practical experience on these platforms with real-life cloud project implementations. Finally, you’ll find expert guidance on cloud certifications and career development. By the end of this cloud computing book, you’ll have become a cloud-savvy professional well-versed in AWS, Azure, and GCP, ready to pursue cloud certifications to validate your skills.
Table of Contents (24 chapters)
1
Part 1: Learning about the Amazon Cloud
9
Part 2:Comprehending GCP Cloud Services
14
Part 3:Mastering Azure Cloud Services
19
Part 4:Developing a Successful Cloud Career

Part 3:Mastering Azure Cloud Services

In this part, we will first compare the foundational cloud services – AWS, GCP, and Azure – summarizing the common features of their computer, storage, network, and database services. We will also describe the unique characteristics of the Azure cloud’s foundation services. We will then examine the Azure data services by looking at the Azure cloud’s database and big data processing services. Further, we will explore the Azure AI services, including the Azure ML workspace and Azure Cognitive Services, which are ML APIs that leverage pre-trained models. We will end this part with a look at the security services in the Azure cloud.

This part comprises the following chapters:

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