With the GenAI boom showing no sign of letup, the demand for AI skills will only increase with time and innovation. Microsoft Azure leads the pack with services for developing and deploying AI solutions, so professionals looking to break into this field should consider pursuing certification as an Azure AI Engineer Associate.

Azure's AI-102 exam isn't a piece of cake, but author Renaldi Gondosubroto makes it a great deal more approachable with this comprehensive study guide. Packed with expert guidance, it covers everything you'll need to know to pass the exam. You'll dive deep into all the phases of AI solutions development, from requirements definition and design to development, deployment, and integration, along with maintenance, performance tuning, and monitoring throughout.

The book also takes you through practical implementation of these systems, covering decision support, computer vision, natural language processing, knowledge mining, document intelligence, and generative AI solutions.

• Understand the core concepts of Azure AI services
• Develop and deploy AI solutions within Azure's environment
• Explore integration and security practices with Azure AI services
• Optimize and troubleshoot AI models on Azure
• Gain knowledge about building GenAI solutions on Azure and put it into practice

Table of Contents

Chapter 1. Introduction to Al Solutions on Microsoft Azure

Chapter 2. Planning and Managing Al Solutions in Microsoft Azure

Chapter 3. Storing, Interpreting, and Visualizing Data

Chapter 4. Building Decision Support Solutions with Azure Al

Chapter 5. Implementing Computer Vision Solutions with Azure Al

Chapter 6. Implementing Natural Language Processing Solutions

Chapter 7. Advanced NLP Techniques and Language Understanding

Chapter 8. Implementing Knowledge Mining and Document Intelligence Solutions

Chapter 9. Utilizing the Azure OpenAI Service for Generative Al Applications

Chapter 10. The Future of Al in Microsoft Azure

About the Author

Renaldi Gondosubroto is an accomplished Software Engineer and a developer advocate in the tech community. With over a decade of experience in developing Artificial Intelligence solutions, he has made significant contributions to numerous companies and communities. He has a Bachelor of Science in Computing and Software Systems from the University of Melbourne and a Master of Science in Computer Science from Columbia University. Outside of the industry, he is active in the academia community with a research focus on generative AI and machine learning. Having spoken at over 40 events and conferences, along with having led a chunk of workshops, he has been an international speaker for the past six years, sharing his experiences and projects. He is also currently an AWS Subject Matter Expert (SME) for its Professional and Specialty Certifications and holds all 13 AWS certifications, along with 20 Microsoft Azure Certifications, including the AI-102 certification. He aims to build open-source solutions which can both help people achieve more value in what they do and promote best practices for fellow developers.