Microsoft Azure AI Fundamentals (AI-900) Certification Guide: Master AI, Machine Learning, and Azure Cloud Intelligence to Earn Your Microsoft Azure AI-900 Certification (English Edition) Kindle Edition

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Management number 220802549 Release Date 2026/05/03 List Price US$9.98 Model Number 220802549
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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. Book Description 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 you will 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. Table of Contents 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 About the Author 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. Read more

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Language English
File size 30.8 MB
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Publisher Orange Education Pvt Ltd
Word Wise Enabled
Print length 381 pages
Accessibility Learn more
Screen Reader Supported
Publication date January 9, 2026
Enhanced typesetting Enabled

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