📅 Day 1: Foundations of LCA and Environmental Data
- Importance of LCA in sustainability, ESG, and product design
- LCA phases: Goal & Scope, Inventory, Impact Assessment, Interpretation
- Life-cycle boundaries & environmental indicators (carbon, energy, water, emissions, waste)
- Scope 1/2/3 emissions and digital LCA workflows
🛠️ Hands-on:
- OpenLCA model exploration
- Carbon footprint calculation
- Data visualization
🧰 Tools Covered: OpenLCA, Brightway2, Python (Pandas, Plotly), Google Colab
📅 Day 2: AI & ML for Carbon Prediction and Hotspot Analysis
- Machine learning models: Regression & Clustering for environmental impact
- Hotspot detection and scenario-based LCA comparison
- Sensitivity, uncertainty, and optimization using AI
- Real-time data integration for dynamic sustainability decisions
🛠️ Hands-on:
- Regression & clustering models
- Hotspot analysis
- Genetic Algorithm optimization
🧰 Tools Covered: Python (Scikit-learn, DEAP), Brightway2, ThingSpeak, Google Colab
📅 Day 3: Sustainability Dashboards and AI-Enabled Decision Support
- Carbon intelligence dashboards: stage-wise emissions, hotspots, reduction potential
- ESG reporting, digital product passports, and circular economy strategies
- AI-powered LCA decision-support systems & climate scenario modeling
- Deployment considerations: data standardization, reproducibility, transparency
🛠️ Hands-on:
- Dashboard creation (Excel/Power BI/Streamlit)
- Mini project: AI-assisted carbon hotspot detection
🧰 Tools Covered: Streamlit, Excel, Power BI, Python, OpenLCA, Brightway2
