- Level: Beginner
- Prerequisites: None
- Assessments: Weekly Micro Assessments; Full Assessment in the Final Week
Week 1: AI Basics in Real Estate
Learning Outcome: Understand AI's role in real estate.1.1 Overview of real estate challenges.
1.2 AI applications in property valuation and marketing.
1.3 Smart property management systems.
Practical Component
Explore property value prediction models.
Week 2: Predictive Models for Real Estate Trends
Learning Outcome: Learn to forecast real estate trends using AI.1.4 Analyzing historical real estate data.
1.5 Predicting market trends with AI.
1.6 Identifying investment opportunities.
Practical Component
Build a predictive model for housing prices.
Week 3: Enhancing Tenant Experiences
Learning Outcome: Use AI to improve tenant interactions.1.7 AI-powered tenant support systems.
1.8 Chatbots for property inquiries.
1.9 Virtual tours with AI enhancements.
Practical Component
Create a chatbot for a property management system.
Week 4: Smart Building Systems
Learning Outcome: Automate building management with AI.1.10 AI for energy management.
1.11 Predictive maintenance of building systems.
1.12 AI for enhanced security systems.
Practical Component
Implement a simple energy optimization system.
Week 5: Ethical AI in Real Estate
Learning Outcome: Address ethical and regulatory issues in AI.1.13 Avoiding biases in property valuations.
1.14 Ensuring data privacy for tenants.
1.15 Compliance with real estate regulations.
Practical Component
Analyze ethical AI challenges in real estate.
Week 6: Final Project
Learning Outcome: Develop an AI solution for a real estate challenge.1.16 Define a use case (e.g., property management).
1.17 Build and refine your solution.
1.18 Present the project to peers.
Practical Component
Deliver an AI solution for smart property management.