Programme Parameters
Foundation
3 Weeks (30 Hrs)
Online (e-LMS)
• No prior experience required — basic computer literacy is sufficient.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
ESG & AI for Sustainable Investing is a comprehensive beginner-level program offered DSTC (DSTC) that provides in-depth training in ESG. The course covers critical areas including AI for Sustainable Investing, equipping learners with both theoretical foundations and practical expertise. Through a carefully structured curriculum, participants will develop the skills needed to tackle real-world challenges in Artificial Intelligence. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
ESG & AI for Sustainable Investing is a comprehensive beginner-level program offered DSTC (DSTC) that provides in-depth training in ESG. The course covers critical areas including AI for Sustainable Investing, equipping learners with both theoretical foundations and practical expertise. Through a carefully structured curriculum, participants will develop the skills needed to tackle real-world challenges in Artificial Intelligence.
📋 Course Objectives
1. Gain working command of practical expertise.
2. Translate AI in Sustainability & Climate theory into practical, reproducible analysis.
3. 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
• Data and computational scientists moving into practical expertise
🚀 Key Learning Outcomes
• Confidence to reason about practical expertise in real projects.
• A portfolio-grade AI in Sustainability & Climate deliverable you can defend and extend.
• 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
What ESG Data Actually Is
• Reporting standards: GRI, SASB, ISSB and the CSRD reporting regime
• Rating divergence between providers and its causes
• Materiality and double materiality as a framing for analysis
Mining Disclosure and Alternative Sources
• NLP over sustainability reports, filings and transcripts
• Controversy and incident detection from news and NGO sources
• Greenwashing detection: comparing stated commitment with observable action
Emissions and Transition Analysis
• Scope 1, 2 and 3 accounting and the estimation of missing scope 3
• Transition and physical risk assessment under scenario pathways
• Portfolio alignment metrics and implied temperature rise
Integration Into Investment Decisions
• Screening, tilting and integration approaches compared
• Factor overlap: distinguishing an ESG signal from quality or size
• Backtesting ESG strategies without survivorship and restatement bias
Disclosure, Stewardship and Accountability
• SFDR classification and anti-greenwashing supervision of funds
• Stewardship, voting and engagement evidence
• Documenting an ESG methodology a regulator can inspect
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | TensorFlow |
| Covered Tool / Platform | PyTorch |
| Covered Tool / Platform | Keras |
| Covered Tool / Platform | Scikit-learn |
| Covered Tool / Platform | Jupyter Notebook |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | Hugging Face |
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