AI-900: Microsoft Azure AI Fundamentals

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About Course

Course Overview

The AI-900 Azure AI Fundamentals course introduces learners to the core concepts of Artificial Intelligence (AI) and how they are implemented using Microsoft Azure AI.

It provides a foundational understanding of AI workloads, including:

  • Machine Learning
  • Computer Vision
  • Natural Language Processing (NLP)
  • Generative AI
  • Responsible AI principles

Unlike advanced technical certifications, AI-900 is designed to be accessible to both technical and non-technical audiences, making it the entry point into the AI ecosystem.

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What Will You Learn?

  • Understand core AI concepts and workloads
  • Identify real-world AI use cases
  • Explain Machine Learning fundamentals
  • Describe Azure AI services and capabilities
  • Understand Generative AI and its impact
  • Apply Responsible AI principles
  • Make informed AI adoption decisions

Course Content

Module 1: Introduction to Artificial Intelligence
📖 Overview Understand what AI is, its evolution, and how it is transforming industries. 🔍 Key Topics What is Artificial Intelligence? AI workloads and scenarios AI in business and society Common AI myths vs reality 🎯 Outcome Build a conceptual foundation of AI and its role in digital transformation.

Module 2: Fundamentals of Machine Learning
📖 Overview Learn how machines learn from data using predictive models. 🔍 Key Topics Supervised Learning vs Unsupervised Learning Regression vs Classification Model training and evaluation Overfitting and underfitting 🎯 Outcome Understand how data drives predictions and decision-making.

Module 3: Computer Vision Fundamentals
📖 Overview Explore how AI interprets and understands images and video. 🔍 Key Topics Image classification Object detection Facial recognition Optical Character Recognition (OCR) 🎯 Outcome Understand how AI can “see and interpret visual data.”

Module 4: Natural Language Processing (NLP)
📖 Overview Learn how AI understands and processes human language. 🔍 Key Topics Text analysis Sentiment analysis Language translation Speech recognition 🎯 Outcome Understand how AI enables human-like interaction with systems.

Module 5: Generative AI Fundamentals
📖 Overview Explore how AI creates new content such as text, images, and code. 🔍 Key Topics Large Language Models (LLMs) Prompt engineering basics AI copilots and assistants Real-world use cases 🎯 Outcome Understand the transformational power of Generative AI.

Module 6: Responsible AI
📖 Overview Learn the ethical and governance considerations of AI systems. 🔍 Key Topics Fairness Reliability & safety Privacy & security Transparency Accountability 🎯 Outcome Develop awareness of ethical AI design and governance.

Simulation Scenario: “AI Adoption for a South African Public Sector Department”
🧩 Scenario Context: A government department wants to: Improve citizen service delivery Automate document processing Use AI chatbots for public engagement 🧠 Tasks: Identify AI workloads Recommend Azure AI services Evaluate risks (Responsible AI) Design a high-level AI solution 🚀 Outcome: Learners transition from: 👉 Theory → Practical AI decision-making

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