Build interactive, AI-augmented LCA dashboards to quantify and communicate environmental impact.
Starting from โน2,499+GST
Register NowThis workshop equips participants to design AI-augmented Life Cycle Assessment (LCA) dashboards that translate complex impact-inventory data into decision-ready visual analytics for sustainability reporting and product design.
Understand ISO 14040/14044 LCA methodology and impact categories
Structure life-cycle inventory (LCI) data for computation
Apply machine learning to fill data gaps and predict impact factors
Build interactive dashboards with Python (Plotly/Dash) and Power BI
Communicate cradle-to-grave results to non-technical stakeholders
Sustainability analysts and ESG reporting teams
Environmental engineers and LCA practitioners
PhD scholars in industrial ecology and green manufacturing
Product designers integrating eco-design
A working AI-LCA dashboard on your own dataset
Ability to compute mid-point and end-point impact categories
Confidence integrating ML-based data-gap filling
Verified e-Certificate of Industrial Competency
Goal & scope definition, functional units, system boundaries, LCI databases (ecoinvent), and mid/end-point impact categories under ISO 14040/44.
Handling data gaps with regression and gradient-boosting, characterization factors, and automating LCI computation in Python.
Building cradle-to-grave dashboards in Plotly Dash and Power BI; scenario analysis, hotspot identification, and stakeholder storytelling.
Build interactive, AI-augmented LCA dashboards to quantify and communicate environmental impact.
This workshop equips participants to design AI-augmented Life Cycle Assessment (LCA) dashboards that translate complex impact-inventory data into decision-ready visual analytics for sustainability reporting and product design.
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