Udemy – AI-102: Microsoft Certified Azure AI Engineer Associate 2025-9

AI-102: Microsoft Certified Azure AI Engineer Associate. This course is a comprehensive, hands-on training program that prepares individuals to succeed in the Microsoft certification exam. Focusing on designing, building, and deploying practical AI solutions on the Microsoft Azure platform, this course goes beyond theoretical concepts and teaches essential skills through clear explanations, Python coding examples, and hands-on labs. Participants are introduced to various Azure AI services, including generative AI, computer vision, natural language processing, speech, and knowledge mining, and learn how to build intelligent and effective applications. The course also emphasizes implementing responsible AI principles, prompt engineering, fine-tuning models, and seamlessly integrating solutions into production pipelines. For developers, data scientists, and AI engineers looking to advance their careers and prove their expertise, this program provides a solid foundation for passing the exam and building distinctive, impactful solutions.

What you will learn

• Understand the core concepts of artificial intelligence, machine learning, and generative AI on the Azure platform.
• Plan, build, deploy, and manage AI solutions using Azure AI Foundry services.
• Select and implement the right Azure service for solutions including generative AI, computer vision, and natural language processing.
• Develop Python applications that interact with Azure AI services and APIs.
• Fine-tune models, employ prompt engineering, and implement RAG (Retrieval-Augmented Generation) solutions.

This course is suitable for people who:

• Students and professionals preparing for the AI-102: Azure AI Engineer Associate certification exam.
• Developers who want to learn how to build and deploy AI solutions using Azure.
• Data scientists, engineers, and solution architects looking to enhance their AI skills with hands-on Azure experience.
• Professionals interested in implementing responsible AI practices in their applications.