Overview

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Build a strong foundation in artificial intelligence with Microsoft Azure while preparing for the AI-900 certification. This course introduces core AI concepts, machine learning fundamentals, responsible AI principles, and Azure AI services through practical examples and guided service walkthroughs. You will explore common AI workloads, including computer vision, natural language processing (NLP), and conversational AI, while learning how Azure supports the development of intelligent solutions. Designed for beginners, business users, and technical decision-makers, this course helps you understand how AI systems work and how to apply Microsoft Azure services to real-world scenarios. You will analyze AI use cases, classify machine learning models, interpret datasets and evaluation metrics, and build no-code machine learning workflows using AutoML and ML Designer. You will also explore Azure Cognitive Services, Text Analytics, Computer Vision, and Azure Bot Services to create intelligent applications, while understanding Microsoft's responsible AI principles for ethical AI implementation. Whether you are preparing for the AI-900 exam or looking to understand Azure AI capabilities, this course provides a structured, practical introduction to AI concepts and Azure-based intelligent solutions, enabling you to confidently evaluate and implement AI technologies in modern organizations.

Syllabus

Foundations of AI and Microsoft’s Ethical Principles

This module introduces learners to the fundamental concepts of Artificial Intelligence (AI) and its real-world applications. It explains what AI is, how machine learning models function, and the types of workloads typically handled by AI systems. Additionally, the module outlines the structure and requirements of the AI-900 certification exam and explores Microsoft’s approach to responsible AI. Learners will gain insights into AI’s ethical principles, including fairness, accountability, transparency, and security, setting the stage for informed and responsible use of AI technologies within the Microsoft Azure ecosystem.

Machine Learning Fundamentals and No-Code Tools

This module delves into the foundational concepts and practical workflows of machine learning within the Azure ecosystem. Learners explore common machine learning types, understand the structure of datasets, and evaluate models using key metrics such as AUC and FPR. The module further introduces Azure’s no-code tools such as AutoML and ML Designer, guiding learners through the complete lifecycle of model creation—from data registration to deployment—without requiring programming expertise. Through visual and automated experiences, learners will develop a solid grasp of how to build, train, and deploy models efficiently in Azure Machine Learning.

Cognitive Services and Conversational AI

This module explores how Microsoft Azure supports a wide range of AI services focused on perception and interaction. Learners will gain foundational knowledge of computer vision, natural language processing (NLP), and conversational AI workloads. They will examine practical applications, explore relevant Azure services, and understand how to build solutions using tools like Computer Vision, Text Analytics, and Azure Bot Services—enabling intelligent interactions through visual recognition, text comprehension, and conversational interfaces.