Programme Parameters
Graduate / Intermediate
3 Days (4.5 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Learn to transform waste into valuable resources using Circular Life Cycle Assessment (LCA) and cutting-edge sustainability strategies. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
Learn to transform waste into valuable resources using Circular Life Cycle Assessment (LCA) and cutting-edge sustainability strategies.
📋 Course Objectives
1. Apply AI Enablement methods to authentic research and industry problems.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in AI Enablement
• R&D engineers and working professionals applying AI Enablement in industry
• Academics and educators building research or teaching capacity in AI Enablement
🚀 Key Learning Outcomes
• A demonstrable AI Enablement project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Life Cycle Assessment Fundamentals
• ISO 14040 and 14044 and the four phases they define
• Functional unit and system boundary as the choices that determine the answer
• Attributional against consequential modelling and the questions each answers
Building the Data Layer
• Foreground and background data, with ecoinvent as the common background
• Data quality, uncertainty and the pedigree approach to scoring it
• openLCA or Brightway as the working tool, and reproducible model files
From Flows to Indicators
• Impact categories beyond carbon: water, eutrophication, toxicity, land use
• Characterisation methods such as ReCiPe and the effect of method choice
• Normalisation and weighting, and why weighting is a value judgement
Waste as a Resource
• End-of-life allocation: cut-off, avoided burden and the circular footprint formula
• Recycling, cascading and the quality loss at each cycle
• Circularity indicators such as MCI and what they fail to capture
Designing and Communicating
• Comparative assertions and the critical review requirement that attaches
• Hotspot analysis and burden shifting between categories
• Green claims regulation and the line between a result and greenwashing
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | RStudio |
Frequently Asked Questions
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