Workshop Registration End Date :25 Apr 2026

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Virtual Workshop

AI for LCA Automation: Real‑Time Data, NLP & Predictive Impact Modeling(25 April)

Automate the Inventory. Predict the Impact. Scale the Sustainability

Skills you will gain:

About Workshop:

AI for LCA Automation: Real‑Time Data, NLP & Predictive Impact Modeling is a 3-day professional certification workshop designed to transform traditional Life Cycle Assessment (LCA) into an AI-driven process. Using 100% free, open-source Python tools, participants will learn to automate data ingestion, monitor real-time environmental impacts, and forecast sustainability outcomes.

Aim: To empower professionals with AI, NLP, and predictive analytics tools to automate and optimize Life Cycle Assessment (LCA) for efficient, real-time sustainability monitoring and decision-making.

Workshop Objectives:

  • Automate data extraction using AI and NLP.
  • Enable real-time environmental impact monitoring.
  • Apply predictive modeling for impact forecasting and lifecycle optimization.
  • Provide hands-on experience with Python-based projects.
  • Enhance LCA practices for efficient, data-driven sustainability decisions.

What you will learn?

Day 1 | Intelligent Data Ingestion & NLP for Inventory (LCI)

  • Focus: Automating the transition from unstructured text to structured sustainability data.
  • The Future of LCI: Moving beyond manual data entry to “Plug-and-Play” automated inventories.
  • Scientific Text Mining: Using Natural Language Processing (NLP) to extract material flows and energy requirements from technical reports and papers.
  • Data Standardization: Automated unit conversion and nomenclature mapping using Python logic.
  • Building Scalable Databases: Structuring extracted data for seamless integration into LCA software.
  • Hands-on: Project: The Automated Material Parser. Use Python’s Spacy library to automatically identify and extract material quantities and process parameters from raw technical summaries.

Day 2 | Dynamic Monitoring & Real-Time Impact Dashboards

  • Focus: Bridging the gap between live industrial data and environmental impact assessment.
  • LCA in Motion: Implementing “Live LCA” methodologies for continuous environmental monitoring.
  • API Integration: Connecting LCA models to open-source APIs (e.g., electricity grid intensity, supply chain feeds).
  • Temporal Impact Assessment: Understanding how time-of-use and regional energy mixes shift carbon footprints in real-time.
  • Visualizing ESG Metrics: Building interactive, professional-grade dashboards for stakeholders.
  • Hands-on: Project: The Real-Time Carbon Dashboard. Use Pandas and Plotly to build a live-updating tracker that calculates the CO2 footprint of a process based on current energy grid data.

Day 3 | Predictive Analytics & AI-Driven Design Optimization

  • Focus: Leveraging Machine Learning to forecast impacts and optimize product lifecycles.
  • Predictive Impact Modeling: Using historical data to estimate the environmental scores of new products before production begins.
  • Smart Material Substitution: Using AI logic to suggest lower-impact alternatives based on performance requirements.
  • Sensitivity & Risk Analysis: Automated identification of “Hotspots” and future environmental risks (e.g., 2030 carbon tax scenarios).
  • Strategic Decision Support: Transitioning from “Assessment” to “Automation” in corporate sustainability strategy.
  • Hands-on: Project: The ‘What-If’ Scenario Predictor. Build a moderate-level regression model using Scikit-Learn to forecast the Global Warming Potential (GWP) of a product based on its design parameters.

Mentor Profile

Fee Plan

StudentINR 2499/- OR USD 75
Ph.D. Scholar / ResearcherINR 3499/- OR USD 85
Academician / FacultyINR 4499/- OR USD 95
StudentINR 6499/- OR USD 120

Important Dates

Registration Ends
25 Apr 2026 Indian Standard Timing 4: 30 PM
Workshop Dates
25 Apr 2026 to
27 Apr 2026  Indian Standard Timing 05:30

Get an e-Certificate of Participation!

2024Certfiacte

Intended For :

  • Researchers and Academics in environmental science, sustainability, or data analysis.
  • Professionals in environmental management, sustainability, and product development.
  • Data Scientists and Engineers interested in applying AI to sustainability.
  • LCA Practitioners seeking to automate and optimize workflows.

Career Supporting Skills

Workshop Outcomes

  • Proficiency in automating data ingestion and structuring sustainability data.
  • Ability to build real-time environmental impact dashboards.
  • Skills to apply predictive analytics for optimizing product lifecycles.
  • Hands-on experience with Python tools for LCA automation.
  • Enhanced decision-making capabilities for sustainable practices using AI-driven LCA.