Artificial Intelligence for Cloud Computing
By Theo Riven
Length3h 58m
About this audiobook
Discover how artificial intelligence and cloud computing work together to power modern digital innovation.
Artificial Intelligence for Cloud Computing is a practical guide for beginners, students, developers, AI learners, and technology professionals who want to understand how cloud platforms support machine learning, data processing, and intelligent applications. The book begins with the foundations of cloud computing, including service models, storage, virtual machines, scalability, and cloud infrastructure.
Readers will then explore artificial intelligence and machine learning basics, cloud-based AI workflows, data pipelines, model deployment, automation, security, and real-world cloud AI use cases. Written in clear and accessible language, this book helps readers understand how cloud systems make AI more scalable, flexible, and practical.
Whether you are building AI projects, learning cloud technologies, or preparing for a career in modern computing, this guide provides a structured path into cloud-powered artificial intelligence.
Audiobook details
GenreTechnology
Length3 hrs 58 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateJun 12, 2026
LanguageEnglish
Table of contents
1Chapter 1: Foundations of Cloud Computing for AI Enthusiasts
2What Is Cloud Computing? A Simple Breakdown
3Core Concept 1: Virtualization—The Magic of Sharing Resources
4Why It Matters for AI
5Simple Example
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6How It Works Under the Hood
7Core Concept 2: Scalability—Growing Without Limits
8Why It Matters for AI
9Simple Example
10How It Works Under the Hood
11Other Essential Concepts: Building Blocks for AI
12Major Cloud Providers: AWS, Azure, and GCP
13Amazon Web Services (AWS)
14Microsoft Azure
15Google Cloud Platform (GCP)
16Real-World Applications: Cloud Foundations in AI
17Hands-On: Setting Up Your First Cloud Account
18Step 1: Create an AWS Account
19Step 2: Explore the AWS Management Console
20Step 3: Launch Your First Free-Tier VM
21Step 4: Run a Simple AI Test
22Exploring Free Tiers: Maximizing Zero-Cost Learning
23Tips and Common Mistakes to Avoid
24Summary of Key Takeaways
25Exercises and Challenges
26Chapter 2: Introduction to Artificial Intelligence and Machine Learning Basics
27What Is Artificial Intelligence? The Big Picture
28Key Branches of AI
29Simple Example: AI in Daily Life
30What Is Machine Learning? Learning Without a Teacher... Sometimes
31Core Components of ML
32Why ML Matters for Beginners
33Types of Machine Learning: Supervised, Unsupervised, and Beyond
34Supervised Learning: Learning with Labels: Simple Example
35Unsupervised Learning: Finding Hidden Patterns: Simple Example
36Reinforcement Learning: Learning by Reward: Comparison Table
37Neural Networks: The Brain-Inspired Powerhouse
38How Neural Networks Work
39From Basics to Deep: Simple Example
40The Role of Data: Preparation and Visualization: Why Visualize?
41Hands-On: Simple Python Scripts for Data Visualization
42Exercise 1: Basic Plotting with Matplotlib
43Exercise 2: Advanced Viz with Seaborn (Pairplot for All Features)
44Exercise 3: Supervised ML Viz—Decision Boundaries
45Real-World Applications: AI and ML in Action
46Supervised Learning: Healthcare Diagnostics
47Unsupervised Learning: Marketing Personalization
48Neural Networks: Autonomous Vehicles
49Reinforcement Learning: Stock Trading Bots
50Actionable Steps: Implementing ML Basics on Your Cloud Setup
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