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
The three‑day, hands‑on program equips you with practical skills to create and leverage digital twins for sustainable infrastructure. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The three‑day, hands‑on program equips you with practical skills to create and leverage digital twins for sustainable infrastructure.
📋 Course Objectives
1. Put AI in Sustainability & Climate techniques to work on real datasets and case studies.
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 Sustainability & Climate
• R&D engineers and working professionals applying AI in Sustainability & Climate in industry
• Academics and educators building research or teaching capacity in AI in Sustainability & Climate
🚀 Key Learning Outcomes
• Tangible, reproducible AI in Sustainability & Climate work to show supervisors or employers.
• 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 Digital Twins & Climate‑Resilient Sustainability
Explore digital‑twin architecture for buildings, campuses and industrial sites • Identify key sustainability and climate‑risk indicators • Create system‑mapping and indicator‑matrix using Google Colab, Python and QGIS
Day 2 – AI and Simulation for Climate Impact Analysis
Model resource flows, energy demand and operational stress with SimPy/AnyLogic • Apply Python‑based AI techniques for pattern detection in climate data • Interpret simulation outcomes to inform resilience decisions
Day 3 – Climate‑Resilience Dashboards & Decision Intelligence
Transform twin and simulation data into actionable dashboards (Power BI, QGIS) • Design ESG‑ready visualisations and resilience scoring • Deliver a mini‑project: end‑to‑end climate scenario decision dashboard
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | Google Sheets |
| Covered Tool / Platform | QGIS |
| Covered Tool / Platform | Power BI |
| Covered Tool / Platform | SimPy |
| Covered Tool / Platform | AnyLogic |
Frequently Asked Questions
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