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AI-Assisted Circular Economy Pathways

Original price was: USD $99.00.Current price is: USD $59.00.

Predictive waste-to-resource modeling for cities.

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

  • Circular economy explained simply: key models, metrics, and what’s often misunderstood

  • Global examples that actually work: circular strategies from EU, Asia, and Africa

  • Where circular data comes from: material flows, lifecycle datasets, waste-stream records

  • 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

  • AI for material recovery: image recognition, sorting, classification, and quality checks

  • Predictive analytics for product lifecycles and reverse logistics planning

  • ML for waste-stream forecasting and resource optimization (what to predict, why it matters)

  • Hands-on: Train a simple ML model for waste sorting or predictive maintenance (choose one use-case)

Module 3 — Building Circular Intelligence Tools & Pathways

  • Decision-support systems for circular transition: combining AI + systems thinking

  • AI-supported LCA and impact evaluation (how to quantify trade-offs, not guess)

  • Dashboards for circular KPIs: circularity index, recovery rate, diversion rate, and more

  • Hands-on: Design a prototype AI tool + roadmap for one circular use-case (your industry or a provided template)


Who Should Enrol?

  • Researchers & students in AI, sustainability, environmental sciences

  • Professionals in manufacturing, supply chain, waste management

  • Data scientists/engineers exploring AI for sustainable systems

  • Policymakers & consultants supporting circular transitions

  • Entrepreneurs building circular products and business models

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What You’ll Gain

  • Full access to e-LMS
  • Publication opportunity
  • Self-assessment & final exam
  • e-Certificate

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Feedbacks

In Silico Molecular Modeling and Docking in Drug Development

nice to join this course with you


Alaa Alameen : 11/11/2025 at 12:47 pm

In Silico Molecular Modeling and Docking in Drug Development

Our mentor is good, he explained everything , as I diont have any idea about the topic before, i More struggled a little bit to follow his lessons
jamsheena V : 02/14/2024 at 4:08 pm

CRISPR-Cas Genome Editing: Workflow, Tools and Techniques

Thankyou so much for sharing your knowledge with us . It was truly inspirational .


Ahmad Suhail : 04/11/2025 at 11:13 am

OK


Carlos Saldaña : 02/13/2025 at 4:12 am

Medical Applications of Graphene

Mentor is well equipped with knowledge about all topics related to the medical applications of More Graphene. Presentation is very well done with good skill and Patience
LAXMI K : 09/04/2024 at 2:43 pm

In Silico Molecular Modeling and Docking in Drug Development

Some topics could be organized in different order. That occurred at the end of training in the last More day when the mentor needed to remind one by one where is the ligand where is the target. It can be helpful to label components (files) like that and label days of training respectively.
Anna Ogrodowczyk : 06/07/2024 at 2:58 pm

Artificial Intelligence for Cancer Drug Delivery

Thank you for giving this kind and knowledgeable talk


Mishaben Parmar : 05/07/2024 at 7:57 am

Large Language Models (LLMs) and Generative AI

The mentor was supportive, clear in their guidance, and encouraged active participation throughout More the process.
António Ricardo de Bastos Teixeira : 07/03/2025 at 10:04 pm