Recommended Prerequisites:
- Basic real estate knowledge (valuation, marketing, property management).
- Familiarity with digital tools (no coding required).
- Open mindset to adopting AI in real estate operations.
Course Outline:
Lesson 1: Introduction to AI & Machine Learning in Real Estate
- 1.1 Introduction to AI
- 1.2 Types of Machine Learning (ML) in Real Estate
- 1.3 Challenges & Limitations of AI
- 1.4 Use Cases
- 1.5 Case Study
- 1.6 Hands-on
Lesson 2: AI in Property Valuation & Price Prediction
- 2.1 How AI Estimates Property Values
- 2.2 Comparative Market Analysis (CMA) with AI
- 2.3 AI for Future Market Trend Forecasting
- 2.4 Use Cases
- 2.5 Case Study
- 2.6 Hands-on
Lesson 3: AI in Marketing & Lead Generation
- 3.1 AI for Real Estate Marketing & Personalization
- 3.2 AI Chatbots & Virtual Assistants
- 3.3 AI in Social Media & SEO
- 3.4 Use Cases
- 3.5 Case Study
- 3.6 Hands-on
Lesson 4: AI for Fraud Detection & Risk Management
- 4.1 AI for Detecting Real Estate Fraud
- 4.2 AI for Loan & Mortgage Risk Assessment
- 4.3 AI for Anti-Money Laundering (AML) in Real Estate
- 4.4 Use Cases
- 4.5 Case Study
- 4.6 Hands-on
Lesson 5: AI in Smart Homes & Property Automation
- 5.1 AI-Powered Smart Homes & IoT
- 5.2 AI for Energy Efficiency & Sustainability
- 5.3 AI-Enhanced Security & Surveillance
- 5.4 Use Cases
- 5.5 Case Study
- 5.6 Hands-on
Lesson 6: AI in Compliance & Ethics
- 6.1 AI’s Role in Fair Lending & Bias Detection
- 6.2 AI-Powered Legal Document Verification
- 6.3 Regulatory Challenges & Ethical Concerns
- 6.4 Use Cases
- 6.5 Case Study
- 6.6 Hands-on
Lesson 7: AI for Business Strategy & Decision-Making
- 7.1 AI in Real Estate Investment & Site Selection
- 7.2 AI-Driven Risk Management & Predictive Maintenance
- 7.3 AI in Real Estate Portfolio Optimization
- 7.4 Use Cases
- 7.5 Case Study
- 7.6 Hands-on
Lesson 8: AI Strategy & Capstone Project
- 8.1 Real-World Case Study: “End-to-End AI Implementation in Real Estate”
- 8.2 Final Project: AI Strategy Implementation
