Urban Metabolism Modeling with AI

Introduction to the Course

Course Objectives

• Understand the concept of Urban Metabolism and its significance in sustainable urban planning.
• Learn how AI and Machine Learning algorithms can be used to optimize the flow of resources and energy in an urban setting.
• Develop skills in data-driven analysis of urban systems and modeling for resource optimization.
• Learn how to model system dynamics to simulate Urban Metabolism and forecast resource usage patterns.
• Understand how AI can be used to enhance sustainability, minimize environmental effects, and develop resource-efficient urban systems.
• Develop skills to apply AI-based solutions to optimize urban resources such as energy, water, and waste, and enhance overall urban resilience.

What Will You Learn (Modules)

Module 1 — Foundations & Data Understanding

• what it is and why it matters for megacities
• how different cities manage energy, water, and waste (and where they struggle)
• turning messy city systems into understandable inputs and outputs

Module 2 — AI for Resource Flow Modeling

• Forecasting, optimization, early warning, and operations support
• Machine learning for demand and flow prediction

Module 3 – Ethical Considerations and Future of AI in Space Exploration

• From models to action: simulation thinking and how digital twins support smart cities
• Visualizing flows in a way people can use
• Communicating results for policy and planning

Who Should Take This Course?

This course is ideal for:

• Urban planners and city officials working to improve sustainability and resource management in cities
• Environmental engineers and sustainability professionals focused on energy, water, and waste management
• Data scientists and machine learning engineers interested in applying AI to urban systems and resource optimization
• Researchers in environmental science, systems engineering, or smart cities
• Students in urban studies, environmental engineering, or data science programs looking to specialize in urban metabolism modeling

Job Opportunities

After completing this course, learners can pursue roles such as:

• Urban Sustainability Analyst
• Smart City Data Scientist
• Environmental Systems Engineer
• Resource Optimization Consultant (AI-driven)
• Urban Metabolism Researcher

Why Learn With Nanoschool?

At NanoSchool, we focus on career-relevant learning that builds real capability—not just theory.

• Expert-led training: Learn from instructors with real-world experience in applying skills to industry and research problems.
• Practical & hands-on approach: Build skills through guided activities, templates, and task-based learning you can apply immediately.
• Industry-aligned curriculum: Course content is designed around current tools, workflows, and expectations from employers.
• Portfolio-ready outcomes: Create outputs you can showcase in interviews, academic profiles, proposals, or real work.
• Learner support: Get structured guidance, clear learning paths, and support to stay consistent and finish strong.

Key outcomes of the course

Upon completion, learners will be able to:

• In-depth knowledge of urban metabolism and its effects on sustainability
• Practical experience with machine learning and system dynamics modeling for urban resource optimization
• Ability to apply AI to enhance urban sustainability, energy efficiency, and waste management
• Skills to design AI solutions for climate change and resource management in urban areas
• A project to demonstrate your skills to develop optimized urban metabolism models