Microsoft Azure AI Fundamentals (AI-900) Certification Guide

Empower your AI Cloud Career with Microsoft Azure AI-900 Certification

KEY FEATURES
● Complete coverage of Azure AI (AI-900) objectives with real-world Azure examples.
● Hands-on learning using Azure AI Services, Azure Cognitive, ML, and Responsible AI tools.
● Practical exam strategies, practice tests, and expert-driven insights.

DESCRIPTION
The Microsoft Azure AI Fundamentals (AI-900) certification is one of the most in-demand credentials and your gateway to understanding AI and how it drives innovation in the cloud. The Microsoft Azure AI Fundamentals (AI-900) Certification Guide takes you on a step-by-step journey from foundational AI principles to hands-on implementation using Microsoft Azure.

You will start by exploring the building blocks of AI — understanding workloads, data science fundamentals, and the difference between AI, ML, and deep learning. From there, the book dives into Azure Cognitive Services, guiding you through Vision, Language, Speech, and Decision-making capabilities with practical examples and use cases. You will also learn how to build intelligent applications that see, hear, and understand the world around them.

As your knowledge deepens, you can work with Azure Machine Learning to train, evaluate, and deploy predictive models, explore Generative AI with Azure OpenAI Service, and implement responsible AI principles to ensure that your solutions are fair, transparent, and ethical. Each chapter is structured to reinforce understanding through real-world scenarios, guided exercises, and exam-focused insights that prepare you for success.

WHAT WILL YOU LEARN
● Understand core AI workloads and essential features of intelligent systems.
● Explore Azure Cognitive Services for vision, language, and speech capabilities.
● Build, train, and deploy machine learning models using Azure Machine Learning.
● Apply Responsible AI principles to design safe, fair, and ethical solutions.
● Prepare effectively for the AI-900 exam with practical, real-world examples.
● Learn how AI solutions connect and integrate across Azure cloud services.

WHO IS THIS BOOK FOR?
This book is ideal for professionals preparing for the Microsoft Azure AI-900 certification, including Cloud Engineers, AI Developers, Data Analysts, Solution Architects, and Business Analysts who want to understand and apply the core AI concepts using Azure. It is also suitable for students and IT practitioners seeking a hands-on introduction to AI, Machine Learning (ML), and Responsible AI on the Azure platform. No prior AI or data science experience is required.

1. Introduction to Exam AI-900
2. Identify Features of Common AI Workloads
3. Identify Guiding Principles for Responsible AI
4. Identify Common Machine Learning Techniques
5. Describe Core Machine Learning Concepts
6. Describe Azure Machine Learning Capabilities
7. Identify Common Types of Computer Vision Solution
8. Identify Azure Tools and Services for Computer Vision Tasks      
9. Identifying Common NLP Workloads
10. Identify Azure Tools and Services for NLP Workloads
11. Identify Features of Generative AI Solutions
12. Identifying the Capabilities of Azure OpenAI Service
13. Practice Test and Sample Questions
14. Best Practices, Future Trends, and Tips and Tricks 
Index

Higor Luis Barbosa is a Cloud Platform Engineer, Enterprise Architect, and Instructor with 20+ years of expertise and experience in IT. Specializing in Azure, AWS, and AI, he designs scalable cloud solutions and teaches over 50,000 students worldwide. Author of Microsoft Azure AI Fundamentals (AI-900) Certification Guide, he makes complex technologies accessible and impactful.


About the Technical Reviewer
Shanthababu Pandian is a distinguished technology leader with over 23 years of experience in the IT industry, specializing in Artificial Intelligence (AI), Machine Learning (ML), Generative AI (GenAI), and Data Science. He holds a Bachelor’s degree in Electronics and Communication Engineering, three Master’s degrees— M. Tech, MBA, and M.S.—from premier Indian institutions, a Postgraduate Program in AI and ML from the University of Texas, and a Postgraduate Certification in Data Science from IIT Guwahati. He is currently pursuing a Ph.D. in Artificial Intelligence from Anna University, Chennai, reflecting his unwavering commitment to advancing research, innovation, and responsible AI.

Throughout his career, Shanthababu has delivered transformative, enterprise-scale solutions for clients in the UK and the US across healthcare, finance, and retail. His expertise spans architecting complex data ecosystems, implementing AI governance and compliance frameworks, and developing BI and AI-driven platforms that bridge cutting-edge technology with strategic business goals. As a seasoned leader, he has steered globally distributed teams, collaborated with executive stakeholders, and ensured seamless delivery through agile practices and modern cloud technologies.

A respected thought leader and mentor, Shanthababu has delivered over 50 keynote talks at national and international forums, sharing in-depth insights with both academic and industry communities. He is the author of over 100 publications and books, and a trusted Technical Reviewer for leading global publishers, having reviewed over 75 titles across AI, data engineering, cloud computing, and software development. Through his leadership, mentorship, and academic contributions, Shanthababu continues to inspire the next generation of AI and data professionals—championing innovation, ethical AI adoption, and a culture of data literacy, quality, and governance across global technological ecosystems.