Designed for people who want to use AI in service of real environmental progress.  

You are interested in AI and machine learning, but also care deeply about where those tools are applied, what they can change, and who they affect. One of the worlds first programs in AI and Climate Science helps you build the technical depth, climate understanding, and honest judgment to contribute meaningfully, while deepening how you think, question your assumptions, and take responsibility for the systems your work touches.

This Bachelor of Science in AI & Sustainability (Online) helps you build strong technical foundations while developing the clarity, curiosity, and integrity that meaningful environmental work demands. From day one, you work on real-world challenges through the phases of Orientation, Calibration, Elevation, and Activation, growing as a technical practitioner and as a person who takes responsibility for the impact of their work.

Study mode:

• Fully remote
• Affordable Tuition from 486 EUR / Month
• Self-Paced, While Working
• Language of instruction: Fully taught in English or German

Who is this Program for?

• Aspiring Sustainability Data Analysts: You want to build the foundations for roles that turn climate and environmental data into clear insights, honest reporting, and practical next steps that create real impact.
• Data Practitioners moving into Climate Work: You already have some exposure to analytics or coding and want to apply machine learning more effectively in environmental and sustainability contexts.
• Purpose-Driven Tech Innovators: You want to use AI in ways that respect complexity, support better choices, and stay grounded in long-term environmental responsibility, knowing that how you build matters as much as what you build.
• Mission-Driven Career Changers: You are finding your path and want a structured way into climate-focused tech work, with learning designed to build both competence and purpose.

What You Learn:

A curriculum that combines AI, data science, climate literacy, and planet-centric innovation. As the urgency of climate and sustainability challenges grows, the ability to apply AI and data science responsibly has never mattered more.

• Build Strong Data and AI Foundations: Build confidence through statistics & data analysis, math foundations for AI and data structures & algorithms so you can work with data in a structured, reliable, and honest way.
• Apply Machine Learning to Environmental Challenges: Practice the methods behind forecasting, pattern detection, and decision support so you can apply machine learning to climate and sustainability challenges with both confidence and care.
• Ground your work in Real Environmental Context: Build the climate literacy needed to apply AI meaningfully. Explore Foundations of climate science, nature-based solutions, and circular economy to understand the systems your technical work is meant to support.
• Build Responsibility into every System: Study systems thinking for sustainable development, science-based sustainable management, and planet-centric thinking to make choices that are thoughtful, transparent, and grounded in real-world impact on people and planet.