Azure AI Fundamentals (AI-900) Syllabus
Azure AI Fundamentals (AI-900)
40-Hour Comprehensive Online Course with Hands-on Labs, Projects & Exam Preparation
Duration
40 Hours
Format
Online (Live + Labs)
Level
Beginner
Includes
Labs, Projects, Mock Tests
Week 1 - AI Foundations & Azure Basics (10 Hours)
Module 1: Introduction to AI (2 hours)
2 hours📚 What You'll Learn:
- Define artificial intelligence and its core concepts
- Differentiate between Narrow AI, General AI, and Superintelligent AI
- Identify real-world AI applications across various industries
- Understand the ethical implications and responsible use of AI
- Recognize current limitations and future possibilities of AI
Multiple Choice Questions Preview:
1. Which type of AI is designed to perform a specific task, such as facial recognition?
2. Which of the following is NOT a principle of responsible AI?
Interview Questions Preview:
1. What is the difference between Narrow AI and General AI?
Answer: Narrow AI (or Weak AI) is designed and trained for a specific task (like voice assistants or recommendation systems). General AI (or Strong AI) refers to systems that possess the ability to perform any intellectual task that a human can do, which currently doesn't exist beyond theoretical research.
2. Can you explain the concept of "algorithmic bias" in AI systems?
Answer: Algorithmic bias occurs when an AI system produces systematically prejudiced results due to erroneous assumptions in the machine learning process. This often stems from biased training data or flawed algorithm design, leading to unfair outcomes for certain groups of people.
Module 2: Azure Cloud Fundamentals for AI (2 hours)
2 hours📚 What You'll Learn:
- Understand Microsoft Azure cloud computing platform
- Navigate Azure regions, resource groups, and subscriptions
- Set up and manage Azure accounts and costs
- Use Azure Portal and Azure CLI for basic operations
- Identify Azure services relevant to AI workloads
Multiple Choice Questions Preview:
1. What is the primary purpose of Azure Resource Groups?
Interview Questions Preview:
1. How would you explain Azure regions and availability zones to a non-technical stakeholder?
Answer: Azure regions are geographical locations around the world where Microsoft has data centers. Each region contains multiple availability zones, which are physically separate data centers with independent power, cooling, and networking. This design ensures high availability and protects applications from data center-level failures.
Module 3: Azure AI Services Overview (3 hours)
3 hours📚 What You'll Learn:
- Navigate and use Azure AI Studio effectively
- Differentiate between various Azure Cognitive Services
- Understand Azure OpenAI capabilities and use cases
- Compare prebuilt vs. custom AI models
- Configure endpoints, keys, and deployments for AI services
Module 4: Responsible AI (3 hours)
3 hours📚 What You'll Learn:
- Apply fairness, transparency, and accountability principles to AI systems
- Implement privacy and security measures in AI solutions
- Use Microsoft Responsible AI Framework in practice
- Analyze real-world AI failure cases and learn from them
- Develop AI solutions with ethical considerations
Week 2 - Computer Vision & Document Intelligence (10 Hours)
Module 5: Computer Vision Fundamentals (3 hours)
3 hours📚 What You'll Learn:
- Understand core computer vision concepts and techniques
- Differentiate between image classification, object detection, and segmentation
- Identify appropriate computer vision solutions for business problems
- Explore Azure AI Vision capabilities and use cases
- Analyze real-world applications of computer vision
Module 6: Hands-on with Azure AI Vision (3 hours)
3 hours📚 What You'll Learn:
- Implement image analysis using Azure AI Vision
- Detect and classify objects in images
- Extract text from images using OCR (Optical Character Recognition)
- Implement face detection and analysis
- Build practical computer vision applications
Module 7: Document Intelligence (4 hours)
4 hours📚 What You'll Learn:
- Leverage Azure Form Recognizer for document processing
- Use prebuilt models for receipts, invoices, and business cards
- Extract document layout and structure information
- Train custom models with specific datasets
- Automate document processing workflows
Week 3 - NLP, Search, and Conversational AI (10 hours)
Module 8: Natural Language Processing Fundamentals (3 hours)
3 hours📚 What You'll Learn:
- Understand core NLP concepts and techniques
- Implement text classification and sentiment analysis
- Extract entities using Named Entity Recognition (NER)
- Perform language detection and analysis
- Apply language modeling basics to real problems
Module 9: Azure Text Analytics (3 hours)
3 hours📚 What You'll Learn:
- Implement sentiment analysis on text data
- Extract key phrases and entities from documents
- Detect and redact Personally Identifiable Information (PII)
- Perform language detection and analysis
- Build practical NLP applications using Azure Text Analytics
Module 10: Azure AI Search (2 hours)
2 hours📚 What You'll Learn:
- Understand cognitive search concepts and architecture
- Configure indexers, skills, and knowledge stores
- Build search experiences for various document types
- Implement AI-enriched search capabilities
- Create intelligent search solutions for business applications
Module 11: Conversational AI (2 hours)
2 hours📚 What You'll Learn:
- Understand conversational AI concepts and components
- Use Azure Language Service for language understanding
- Build QnA bots for knowledge base querying
- Create and deploy chatbots using Azure Bot Service
- Design effective conversational flows
Week 4 - Azure OpenAI, Automation, Deployment & Exam Prep (10 Hours)
Module 12: Azure OpenAI Fundamentals (3 hours)
3 hours📚 What You'll Learn:
- Understand GPT models and their capabilities
- Implement text embeddings for various applications
- Apply prompt engineering techniques effectively
- Implement content moderation for AI-generated content
- Use Chat Completion API for conversational applications
Module 13: Build & Deploy an AI App (3 hours)
3 hours📚 What You'll Learn:
- Design end-to-end AI applications on Azure
- Implement backend services using Azure Functions
- Connect AI models to APIs and frontend interfaces
- Deploy applications to Azure App Service
- Monitor and maintain deployed AI applications
Module 14: Capstone Project (2 hours)
2 hours📚 What You'll Learn:
- Apply all course concepts to a real-world project
- Choose and implement one of several AI solutions
- Integrate multiple Azure AI services in a single application
- Document and present your AI solution effectively
- Prepare a portfolio-ready AI project
Module 15: Exam Preparation (2 hours)
2 hours📚 What You'll Learn:
- Review all key concepts for the AI-900 exam
- Practice with 100+ exam-style questions
- Complete mock exam simulations under timed conditions
- Apply strategies for passing the exam on first attempt
- Address final questions and concerns before the exam