Overview
Description
Prepare for the AI-900 Microsoft Azure AI Fundamentals certification exam. Learn AI concepts, machine learning basics, Azure AI services, computer vision, NLP, generative AI, and responsible AI practices.
Syllabus And Exam Details
AI-900: Microsoft Azure AI Fundamentals Syllabus (2026)
The AI-900: Microsoft Azure AI Fundamentals certification exam evaluates foundational knowledge of Artificial Intelligence (AI) concepts and Microsoft Azure AI services. The syllabus focuses on understanding AI workloads, machine learning principles, computer vision, natural language processing, generative AI, and responsible AI practices.
1. Artificial Intelligence Workloads and Considerations
- Core principles of Artificial Intelligence
- Common AI workloads and real-world applications
- Predictive analytics and forecasting scenarios
- AI-powered recommendation systems
- Computer vision use cases
- Natural language processing applications
- Conversational AI and virtual assistants
- Responsible AI principles and ethical considerations
2. Machine Learning Fundamentals on Azure
- Basic machine learning concepts
- Types of machine learning models
- Supervised learning techniques
- Unsupervised learning approaches
- Classification model scenarios
- Regression model scenarios
- Clustering methods and use cases
- Model training and evaluation concepts
- Azure Machine Learning capabilities
- Automated machine learning (AutoML) overview
3. Computer Vision Features in Azure
- Image analysis solutions
- Object detection capabilities
- Optical Character Recognition (OCR)
- Face detection and recognition concepts
- Custom vision model development
- Document intelligence and data extraction
- Video analysis applications
- Azure AI Vision services
4. Natural Language Processing (NLP) Workloads
- Text analytics solutions
- Sentiment analysis techniques
- Key phrase extraction methods
- Language detection features
- Named entity recognition concepts
- Question answering systems
- Speech recognition technology
- Speech synthesis capabilities
- Translation services and multilingual support
- Azure AI Language services
5. Generative AI Fundamentals
- Introduction to generative AI
- Large Language Models (LLMs)
- Prompt engineering basics
- Generative AI applications and use cases
- Content generation capabilities
- AI copilots and assistants
- Azure OpenAI Service overview
- Retrieval-Augmented Generation (RAG) concepts
- Generative AI limitations and risks
6. Conversational AI Solutions
- Chatbot fundamentals
- Conversational AI design principles
- Azure AI Bot Service overview
- Language understanding concepts
- Virtual assistant implementation basics
- Customer support automation scenarios
- Multi-turn conversation handling
7. Responsible AI and Governance
- Fairness and transparency principles
- Reliability and safety considerations
- Privacy and security requirements
- Accountability in AI systems
- Bias detection and mitigation concepts
- Ethical AI implementation practices
- Governance and compliance fundamentals
AI-900 Exam Skills Distribution
Domain Approximate Weight AI Workloads & Responsible AI 15–20% Machine Learning Fundamentals 15–20% Computer Vision Workloads 15–20% NLP Workloads 15–20% Generative AI & Azure AI Services 20–25%