Artificial Intelligence (AI) is no longer science fiction—it's powering applications in healthcare, finance, manufacturing, marketing, education, and even entertainment. The AI-900: Microsoft Azure AI Fundamentals certification is your entry point into the world of AI and cloud-based intelligence.
This course is designed for absolute beginners—you don’t need any background in coding, data science, or cloud computing. Whether you’re a business professional looking to understand AI from a strategic perspective, a student exploring career options, or a tech enthusiast eager to learn, this course will equip you with a strong, practical foundation in AI concepts and hands-on experience using Microsoft Azure AI services.
You’ll not only prepare for the Microsoft Certified: Azure AI Fundamentals exam but also develop real-world knowledge of how AI is transforming industries and how you can be part of this transformation.
By the end of this course, you’ll be able to:
Understand the Core Concepts of Artificial Intelligence
Define AI and explain its various types and capabilities
Recognize common AI workloads like computer vision, speech, natural language processing, and predictive analytics
Differentiate between AI, Machine Learning, and Deep Learning
Grasp the Basics of Machine Learning
Understand the life cycle of a machine learning model
Learn key concepts such as features, labels, training, and evaluation
Distinguish between supervised, unsupervised, and reinforcement learning
Get Hands-On with Azure AI Services
Navigate Microsoft Azure’s AI tools without writing code
Use Azure Cognitive Services to analyze text, images, speech, and language
Explore services like Azure Machine Learning, Azure Bot Service, and Azure OpenAI
Explore Real-World AI Use Cases
Discover how organizations apply AI in customer service, marketing, healthcare, and finance
Learn to identify the right AI service for solving specific business problems
Learn the Principles of Responsible AI
Understand Microsoft’s AI ethics framework
Learn how to identify and mitigate bias, ensure fairness, and maintain transparency in AI solutions
Course Content Breakdown
Module 1: Introduction to AI Concepts
What is Artificial Intelligence?
AI vs. Machine Learning vs. Deep Learning
Real-world examples and industry applications
The impact of AI on jobs and the economy
Module 2: Machine Learning in Azure
Supervised and unsupervised learning
Model training, evaluation, and prediction
Introduction to Azure Machine Learning Studio (no-code environment)
AutoML and drag-and-drop model creation
Module 3: Computer Vision
Image classification and object detection
Face recognition and facial analysis
Optical Character Recognition (OCR)
Using Azure AI Vision and Face API
Module 4: Natural Language Processing (NLP)
Text analytics: sentiment, key phrases, and language detection
Language translation using Azure Translator
Question answering and language understanding (LUIS and Azure Language Service)
Module 5: Speech Capabilities
Speech to text and text to speech conversion
Real-time translation and voice recognition
Using Azure Speech Studio for hands-on demos
Module 6: Conversational AI
Introduction to chatbots and digital assistants
Building no-code bots using Azure Bot Framework and Power Virtual Agents
Integrating bots into websites and apps
Module 7: Responsible AI
Ethics and fairness in AI development
Privacy, security, and compliance considerations
Microsoft’s six principles of responsible AI
Module 8: Preparing for the AI-900 Exam
Exam format and question types
Study tips and practice resources
Sample exam walkthrough and tips for success
