AI-900 Azure AI Fundamentals Exam Prep In One Day Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
This fast-paced, one-day course provides a comprehensive overview of the AI-900 Azure AI Fundamentals exam domains, combining conceptual clarity with hands-on demonstrations. Designed for beginners, it covers core AI concepts, Azure cognitive services, machine learning, and responsible AI practices. With approximately 4.5 hours of structured content, this course efficiently prepares learners for the certification exam through clear explanations, real-world use cases, and practice strategies.
Module 1: AI Fundamentals & Azure Overview
Estimated time: 0.5 hours
- Define AI workloads including machine learning, computer vision, and natural language processing
- Tour the Azure AI portfolio and core tools
- Understand Azure regions and pricing tiers for AI services
Module 2: Machine Learning on Azure
Estimated time: 0.75 hours
- Explore Azure Machine Learning Studio components: workspaces, datasets, and experiments
- Use Automated ML for training classification models
- Apply Automated ML to regression and forecasting scenarios
- Deploy trained models with automated pipelines
Module 3: Computer Vision Services
Estimated time: 0.75 hours
- Analyze images using the Computer Vision API
- Perform object detection and tagging
- Extract text from images using OCR
- Automate form processing with Form Recognizer and custom models
Module 4: Natural Language Processing
Estimated time: 0.75 hours
- Extract insights using Text Analytics: sentiment analysis, key phrase extraction
- Perform named-entity recognition
- Translate text with the Translator Text API
- Build language understanding models using LUIS
Module 5: Conversational AI & Bots
Estimated time: 0.75 hours
- Design Q&A experiences with QnA Maker knowledge bases
- Build bots using the Azure Bot Framework
- Deploy and integrate bots with external channels
Module 6: Responsible AI & Security
Estimated time: 0.5 hours
- Apply Microsoft's Responsible AI principles: fairness, transparency, and explainability
- Ensure privacy and inclusiveness in AI solutions
- Secure AI services using role-based access control, keys, and private endpoints
Module 7: AI Solution Patterns & Architecture
Estimated time: 0.5 hours
- Review common AI solution architectures: edge, real-time, and batch processing
- Understand scaling and monitoring strategies
- Optimize costs in Azure AI deployments
Module 8: Exam Preparation & Practice Questions
Estimated time: 0.5 hours
- Review AI-900 exam domains and topic weightings
- Practice with realistic sample questions
- Learn elimination and test-taking strategies
Prerequisites
- Familiarity with basic computing concepts
- Understanding of cloud computing fundamentals (helpful but not required)
- Access to a Microsoft Azure account (free tier acceptable)
What You'll Be Able to Do After
- Pass the AI-900 Azure AI Fundamentals certification exam
- Identify and describe core AI and machine learning concepts
- Implement vision and language solutions using Azure Cognitive Services
- Create basic conversational bots with Azure Bot Framework and QnA Maker
- Apply responsible AI principles and security best practices in Azure environments