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

Azure Cloud AI Services

Like Amazon and Google, Microsoft provides many AI tools and services for data scientists and engineers to develop ML models in the Azure cloud. Microsoft cloud AI services include Azure Machine Learning workspaces, which is a fully managed platform for data scientists to build, train, and deploy machine learning models, and Azure Cognitive Services, which helps developers build cognitive intelligence into applications, based on pre-trained AI models and APIs for common ML tasks. Azure cloud AI services integrate seamlessly with other Microsoft cloud services and tools. In this chapter, we will cover the following topics:

  • Azure Machine Learning workspace, which is an end-to-end platform for data scientists to develop ML models, including data collection, model training and deploying, and other AI capabilities.
  • Azure Cognitive Services, which enables developers to easily add cognitive features into their applications. The Azure Cognitive Services...