Data Science & genAI on Sustainable Development Goals (SDGs)

The Sustainable Development Goals (SDGs) are 17 global goals designed to be a "blueprint for achieving a better and more sustainable future for all." The goals to be achieved by 2030 are an urgent call for action by all countries—and by each of us.

In the first part of the course, we highlight the SDGs and analyze the SDG indicators that track the current global status. Did you know that there are 17 goals backed up and monitored by over 230 indicators? Each indicator measures the progress of all countries, sometimes over decades—a lot of data points to analyze. The lecture balances basic principles with crisp data science practice, covering Python-based analysis, visualization techniques, and cross-analysis of indicators to give you both context and hands-on skills.

In the second part, we go one step further—diving into Scope 3 emissions, the hidden emissions in a company’s value chain that often make up the majority of its footprint. To make this complex topic more engaging, we explore it through modern generative AI techniques: PowerPoint Co-Pilot to structure ideas, ChatGPT for explanations, avatars to bring concepts alive, Notebook LM for organizing knowledge, Mermaid AI for visualizations, Perplexity for deep research, and vibe coding for playful exploration. All of this comes together in a case study of our fictional winery, Riesling Inc. From vineyard to bottle, you’ll see how Scope 3 emissions accumulate and how AI helps us map and understand them.

The overall objective of the course is to give you a quick start in sustainability data science practice and inspire you to contribute towards our joint SDG goals—while also discovering how generative AI can be a powerful companion in exploring and understanding complex global challenges.