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
This advanced 3‑day course integrates Life Cycle Assessment (LCA), AI/ML modeling, and carbon intelligence dashboards to equip participants with the skills to analyse, predict, and optimise environmental impact across industries. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This advanced 3‑day course integrates Life Cycle Assessment (LCA), AI/ML modeling, and carbon intelligence dashboards to equip participants with the skills to analyse, predict, and optimise environmental impact across industries.
📋 Course Objectives
1. Apply AI in Energy & Utilities methods to authentic research and industry problems.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in AI in Energy & Utilities
• R&D engineers and working professionals applying AI in Energy & Utilities in industry
• Academics and educators building research or teaching capacity in AI in Energy & Utilities
🚀 Key Learning Outcomes
• A demonstrable AI in Energy & Utilities 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
Day 1 – Foundations of LCA and Environmental Data
Understand the importance of LCA in sustainability, ESG and product design • Explore LCA phases – Goal & Scope, Inventory, Impact Assessment, Interpretation • Calculate carbon footprint using OpenLCA and visualise results
Day 2 – AI & ML for Carbon Prediction and Hotspot Analysis
Build regression and clustering models to predict carbon emissions • Detect hotspots and run scenario‑based LCA comparisons • Optimise solutions with genetic algorithms and uncertainty analysis
Day 3 – Sustainability Dashboards and AI‑Enabled Decision Support
Create carbon intelligence dashboards with Excel, Power BI or Streamlit • Integrate ESG reporting, digital product passports and circular‑economy strategies • Deploy AI‑driven decision‑support systems for real‑time climate scenario modelling
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | OpenLCA |
| Covered Tool / Platform | Brightway2 |
| Covered Tool / Platform | Python |
| Covered Tool / Platform | Pandas |
| Covered Tool / Platform | Plotly |
| Covered Tool / Platform | Scikit-learn |
| Covered Tool / Platform | DEAP |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | ThingSpeak |
| Covered Tool / Platform | Streamlit |
Frequently Asked Questions
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