Data-driven Management Decisions for Corporate Sustainability with Python

About

This course offers an introduction to using data-driven methods for corporate sustainability challenges. Students will first cover the fundamentals of data analysis project design, including scoping, data sourcing, and ethical considerations. Subsequently, the course is organized into modules covering core analytical techniques, machine learning for prediction, and emerging AI technologies.

Topics:

Introduction: Framing Sustainability as Management Decisions
Data Handling & Preparation (Pandas, NumPy)
Data Visualization for Stakeholder Communication
Data Sourcing, Web Scraping, and Ethical Collection
Introduction to Machine Learning: Linear Regression & Clustering
Practical Workshop: Building Models with Scikit-learn
Managerial Introduction to Generative AI
Project Workshop 1: Scoping and Problem Formulation
Project Workshop 2: Data Strategy and Planning
Strategic Analysis of ESG Reports
Final Project Presentations (Group 1)
Final Project Presentations (Group 2)
Conclusion: Data Science in a Responsible Leadership Toolkit

Course leader

Nesibe Manav Mitlu

Target group

To apply for the course you must either be enrolled in a bachelor's degree, have a bachelor's degree or have passed a qualifying entry examination.

To get the most out of this course, we recommend you have some familiarity with the following areas: Introductory statistics, basic coding experience and familiarity with strategy, marketing, finance, or operations management.

Fee info