Data Science for Sustainability
Your path to a sustainable future!
Key data
- Degree
- Bachelor of Science FHNW in Data Science
- ECTS points
- 180
- Study start
- Spring and Autumn Recommended application deadline for autumn semester: 31 May 2025
- Studying mode
- Flexible and individual. Full-time and Part-time.
- Teaching language
- German / English
- Place
- Brugg-Windisch
Mobile navi goes here!
This field of study is a specialization within the Data Science program. Enroll in the Bachelor's program in Data Science and you will automatically have access to this field of study.
Imagine you can not only develop artificial intelligence and analyze data, but also actively do something for the planet. This is exactly what “Data Science for Sustainability” offers. You will become a fully-fledged data scientist while also learning how to tackle sustainability issues and develop solutions for urgent environmental and social problems.
Whether energy efficiency, resource conservation or climate protection: you will work on concrete projects that show how modern analysis techniques support the transition to a more sustainable world. By combining data-driven insights and an understanding of ecological and social interrelationships, you will acquire sought-after skills that will not only benefit you professionally, but with which you can contribute to a better future.
The new “Data Science for Sustainability” degree program at the FHNW offers you a unique combination of state-of-the-art data science methods and a sound understanding of sustainability. You will be perfectly equipped for a future in which sustainable technologies and data-based innovations are crucial.
“Data Science for Sustainability” is fully embedded in the curriculum of the Data Science degree program. You will acquire all the data science skills required for data-driven analysis, machine learning and the development of digital solutions. In addition, you will specialize in the application of data science in the field of sustainability and expand your competence profile with the following skills:
- Data analysis & modeling for climate protection, energy efficiency and sustainable cities
- Sustainability reporting and regulatory standards (e.g. ESG frameworks, SDGs, CO₂ tracking)
- Systemic thinking to evaluate and optimize sustainable solutions
- Interdisciplinary collaboration with experts from environmental sciences, business and technology
This degree course offers maximum flexibility and individualization - both regarding your learning path as well as regarding content. Whether you prefer a structured approach or independent learning by completing practical projects, we offer you the right environment.
- Sustainability Data Analyst:
Analyze and optimize business processes for greater sustainability. - Machine Learning Engineer for environmental solutions:
Operationalize AI models to predict climate data. - Sustainability Consultant:
Support companies in the data-based implementation of sustainable business models. - Energy Data Specialist:
Optimize energy efficiency with intelligent data analysis and AI - Data Scientist for NGOs:
Use data science for environmental protection and social justice.
Our community is at the heart of this degree program. We connect students, coaches, companies and NGOs to exchange knowledge, share experiences and work together on innovative solutions.
- Students:
Make contacts, exchange ideas and work in teams on practical projects. - Coaches:
Receive support from experienced mentors who will guide you on your journey. - Companies & NGOs:
Benefit from direct access to partners who bring real challenges from the field and work with you on sustainable solutions.
Our community organises regular networking events, hackathons and workshops that offer you valuable insights and contacts.
The main images on the School of Computer Science website were generated using Artificial Intelligence.
Our visual identity represents a cooperation between computer science and art, using various AI tools to generate images that transcend physical limitations.
The School of Computer Science will continue to explore and advance the interface between computer science and art.