About This Course
This 3-week course shows how AI can speed up circular economy transitions—from smarter resource mapping and waste-stream intelligence to lifecycle optimization and decision-support tools. You’ll learn through real global examples and do hands-on activities to build practical skills, ending with a prototype roadmap/tool concept you can adapt to your own domain.
Aim
To equip participants with strong circular economy fundamentals and hands-on AI skills for resource mapping, material recovery, lifecycle optimization, and decision-support, so they can design prototype tools and actionable circular pathways for real-world implementation.
Course Structure
Module 1 — Foundations of Circular Economy & Intelligent Resource Mapping
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Circular economy explained simply: key models, metrics, and what’s often misunderstood
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Global examples that actually work: circular strategies from EU, Asia, and Africa
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Where circular data comes from: material flows, lifecycle datasets, waste-stream records
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Hands-on: Map a linear vs circular resource flow using real (or sample) datasets and identify improvement opportunities
Module 2 — Applying AI in Circular Economy Systems
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AI for material recovery: image recognition, sorting, classification, and quality checks
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Predictive analytics for product lifecycles and reverse logistics planning
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ML for waste-stream forecasting and resource optimization (what to predict, why it matters)
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Hands-on: Train a simple ML model for waste sorting or predictive maintenance (choose one use-case)
Module 3 — Building Circular Intelligence Tools & Pathways
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Decision-support systems for circular transition: combining AI + systems thinking
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AI-supported LCA and impact evaluation (how to quantify trade-offs, not guess)
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Dashboards for circular KPIs: circularity index, recovery rate, diversion rate, and more
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Hands-on: Design a prototype AI tool + roadmap for one circular use-case (your industry or a provided template)
Who Should Enrol?
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Researchers & students in AI, sustainability, environmental sciences
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Professionals in manufacturing, supply chain, waste management
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Data scientists/engineers exploring AI for sustainable systems
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Policymakers & consultants supporting circular transitions
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Entrepreneurs building circular products and business models









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