Automated Impact Reporting: LCA & Generative AI

• Understand LCA principles and their role in sustainability.
• Learn how Generative AI enhances LCA and automates impact reporting.
• Apply AI tools to real-world scenarios for optimized environmental decision-making.
• Explore AI-driven systems for scaling environmental impact assessments across industries.

Day 1: The Foundation – Data, Frameworks, and APIs

• Sustainability reports: GRI, ISO 14040
• Understanding APIs and LLMs
• AI security and privacy practices

• Setting up Google Colab and securing API keys
• Loading sample data (facility_emissions.csv)
• Making the first API call with Python

Day 2: The Logic – Prompt Engineering & LangChain

• System vs. user prompts
• Preventing hallucinations and grounding AI
• Introduction to LangChain

• Crafting and injecting prompts with data
• Testing and refining AI responses for compliance

Day 3: The Insight – Batch Processing & Document Output

• Automating repetitive tasks with loops
• Structuring reports and human-in-the-loop review

• Automating data processing in Python
• Generating and exporting reports in Markdown

• Doctoral Scholars & Researchers: PhD candidates seeking to integrate computational workflows into their molecular research.
• Postdoctoral Fellows: Early-career scientists aiming to enhance their data-driven publication profile.
• University Faculty: Professors and HODs interested in modern bioinformatics pedagogy and tool mastery.
• Industry Scientists: R&D professionals from the Biotechnology and Pharmaceutical sectors transitioning to genomic-driven discovery.
• Postgraduate Students: Final-year PG students looking for specialized research-grade exposure beyond standard curricula.