AI & LCA for Critical Minerals Recovery from E- Waste (Colab-First Edition)

Introduction to the Course

Course Objectives

• Understand the value chain of e-waste and the importance of critical minerals recovery.
• Learn how AI can be used to optimize recovery, predict yields, and monitor processes in recycling facilities.
• Acquire skills in LCA basics for assessing the environmental implications of recovery processes.
• Learn Colab-first approaches to data processing, modeling, and sustainability assessment.
• Discover approaches to compare recycling options using process metrics and LCA-based environmental metrics.
• Develop skills to generate insights ready for decision-making in circular economy and urban mining applications.

What Will You Learn (Modules)

Module 1 – Urban Mining Foundations & Simplified LCA

• Introduction to Urban Mining and Critical Minerals
• Life Cycle Thinking for E-Waste Streams
• Simplified LCA Methodology:

 Module 2 – Machine Learning for Mineral Recovery Prediction

• Feature Engineering from E-Waste Device Attributes
• Label Estimation
• Regression & Classification Models for Recovery Potential

 Module 3 – Integrating AI & LCA in a Dashboard

• Visualizing Trade-Offs
• Creating User-Friendly Dashboards

Who Should Take This Course?

This course is ideal for:

• Researchers in sustainability, circular economy, and urban mining
• Process engineers and recycling professionals in metals/materials recovery
• Materials scientists working with critical minerals and recycling pathways
• Data scientists entering climate-tech, sustainability analytics, or industrial optimization

Job Opportunities

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

• Sustainability Analyst (LCA + Data)
• Circular Economy / Urban Mining Analyst
• Process Optimization Analyst (Recycling)
• Materials Recovery Data Scientist

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:

• Applying AI & LCA for critical minerals extraction from e-waste in real-world applications
• Skills for yield modeling and comparing recycling options based on environmental metrics
• Experience with Colab-first data science and sustainability analysis for circular economy applications
• Ability to present trade-offs and suggestions for decision-making
• Portfolio-ready capstone project showcasing AI + LCA skills for urban mining