Azure AI-102 Certification Essentials: Master the AI Engineer Associate exam with real-world case studies and full-length mock tests
Author:Peter T. Lee (Author)
Publisher finelybook 出版社: Packt Publishing
Publication Date 出版日期: 2025-08-14
Language 语言: English
Print Length 页数: 388 pages
ISBN-10: 1836205279
ISBN-13: 9781836205272
Book Description
Go beyond AI-102 certification by mastering the foundations of Azure AI concepts and services—reinforced through practical labs and real-world examples.
Key Features
- Solidify your understanding with targeted questions at the end of each chapter
- Assess your knowledge of key concepts with over 45 exam-style questions, complete with detailed explanations
- Get hands-on experience with GitHub projects, along with ongoing support from the author on GitHub
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Written by a seasoned solutions architect and Microsoft AI professional with over 25 years of IT experience, Azure AI-102 Certification Essentials will help you gain the skills and knowledge needed to confidently pass the Azure AI-102 certification exam and advance your career. This comprehensive guide covers all of the exam objectives, from designing AI solutions to integrating AI models into Azure services. By combining theoretical concepts with visual examples, hands-on exercises, and real-world use cases, the chapters teach you how to effectively apply your new-found knowledge.
The book emphasizes responsible AI practices, addressing fairness, reliability, privacy, and security, while guiding you through testing AI models with diverse data and navigating legal considerations. Featuring the latest Azure AI tools and technologies, each chapter concludes with hands-on exercises to reinforce your learning, culminating in Chapter 11’s comprehensive set of 45 mock questions that simulate the actual exam and help you assess your exam readiness.
By the end of this book, you’ll be able to confidently design, implement, and integrate AI solutions on Azure, while achieving this highly sought-after certification.
What you will learn
- Learn core concepts relating to AI, LLMs, NLP, and generative AI
- Build and deploy with Azure AI Foundry, CI/CD, and containers
- Manage and secure Azure AI services with built-in tools
- Apply responsible AI using Azure AI Content Safety
- Perform OCR and analysis with Azure AI Vision
- Build apps with the Azure AI Language and Speech services
- Explore knowledge mining with Azure AI Search and Content Understanding
- Implement RAG and fine-tuning with Azure OpenAI
- Build agents using Azure AI Foundry Agent Service and Semantic Kernel
Who this book is for
If you’re preparing for the Azure AI-102 certification exam, this book is for you. Developers, engineers, and career transitioners moving from traditional software development to AI-focused roles can use this guide to deepen their understanding of AI within the Azure ecosystem. This book is also beneficial for students and educators looking to apply AI/ML concepts using Azure. No prior experience in AI/ML is required as this book provides comprehensive coverage of exam topics with detailed explanations, practical examples, and hands-on exercises to build your confidence and expertise.
Table of Contents
- Understanding AI, ML, and Azure’s AI Services
- Getting Started with Azure AI: Studio, Pipelines, and Containerization
- Managing, Monitoring, and Securing Azure AI Services
- Implementing Content Moderation Solutions
- Exploring Azure AI Vision Solutions
- Implementing Natural Language Processing Solutions
- Implementing Knowledge Mining, Document Intelligence, and Content Understanding
- Working on Generative AI Solutions
- Implementing Agentic Solutions with Azure AI Agent Service
- Practical AI Implementation: Industry Use Cases, Technical Patterns, and Hands-On Projects
- Preparing for the AI-102: Azure AI Engineer Associate Certification Exam
About the Author
Peter T. Lee is a Senior Solution Architect at Microsoft, specializing in AI and data with over 25 years of IT experience spanning industries such as telecom, fintech, payments, retail, and pharmacy. Recently, his focus has been on delivering Generative AI projects, developing data extraction solutions for unstructured data, and spearheading AI initiatives in the financial, banking, insurance, and capital markets sectors. With deep expertise in cloud platforms such as Azure, AWS, and GCP, Peter excels in designing scalable and resilient architectures while enabling organizations to adopt cutting-edge AI/ML and Generative AI technologies. Holding over 18 industry certifications, he embodies a strong commitment to continuous learning and innovation.
