Your path to a sustainable future!
Factsheet
- Degree
- Bachelor of Science (FHNW) in Data Science & Artificial Intelligence
Study Track Data Science & AI for Sustainability - ECTS points
- 180
- Next start
- 14.9.2026
- Place
- FHNW Campus Brugg-Windisch
The study track is part of the Data Science & Artificial Intelligence degree programme. Apply for the Bachelor’s degree in Data Science & Artificial Intelligence, and you will automatically gain access to this specialisation.
Why Data Science & Artificial Intelligence for Sustainability?
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 & Artificial Intelligence 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 & Artificial Intelligence 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.

Sustainability Data Analyst
Analyse and optimise business processes to enhance 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.
Structure and programme contents
What can you expect?
This study track is fully embedded in the curriculum of the Data Science & Artificial Intelligence degree programme. You acquire all core data science competencies required for data-driven analytics, machine learning and the development of digital solutions. In addition, you specialise in applying data science to sustainability and expand your competence profile with the following skills:
- Data analysis and modelling for climate protection, energy efficiency and sustainable cities
- Sustainability reporting and regulatory standards (e.g. ESG frameworks, SDGs, CO₂ tracking)
- Systems thinking to evaluate and optimise sustainable solutions
- Interdisciplinary collaboration with experts from environmental sciences, business and technology
Here you can find the curriculum of the Data Science & Artificial Intelligence degree programme and – on the second page – the specific modules of the study track
You can acquire the competencies of Data Science & AI for Sustainability either by attending modules or by working in an Open Learning setting. Open Learning means that you decide where, how and when you learn to develop your competency. For example, you may participate in a MOOC, watch YouTube videos, address a task within your professional work, or by completing an applied challenge as part of your studies.
Whatever learning path you choose, you will be supported by our coaches.
How will you learn?

Practical learning with challenges
Sam is interested in climate modelling. He acquires many skills in the course's practice-oriented challenges and works in interdisciplinary teams to predict CO₂ emissions. In independent research projects and interactive workshops, he learns to analyze complex systems and develop data-based solutions.

Flexible learning for entrepreneurial solutions
Annie combines her studies with her own sustainable mobility start-up enterprise. She integrates real data into her projects, models traffic systems for cities and uses open learning to acquire competencies individually and practically. Her learning journey is characterized by networking, her own initiatives and direct transfer into practice.
Questions? Students provide the answers.
Do you have questions about course content, student life or study formats? Our Data Science & Artificial Intelligence students Lukas, Damian and Lukas are available to you via WhatsApp.
Requirements and Organisational matters
Language
For programmes taught in English, the minimum English requirement for studying at the FHNW School of Computer Science is level B1. For this degree programme, however, we recommend an English level of B2.
An English placement test will be conducted before the start of the semester.
If you are placed below level B2, we recommend attending the module Specialist Coaching in English Communication.
If you would like to independently improve your English skills to reach the required level, we recommend the following resources:
Lecturers
You learn from lecturers with expertise in data science, AI, software development, sustainability and regulatory standards who integrate their applied research and industry projects directly into teaching. Personal coaches support you throughout your academic and professional development — from the first modules to your Bachelor’s thesis.
Requirements and Organisational matters
Further Computer Science Degree Programmes
Discover our fascinating further degree programmes in Computer Science in german
Weiterbildungen
Our recommendation: complete your application for the spring semester by 15 January and for the autumn semester by 31 May.
Data Science & Artificial Intelligence for SustainabilityAutumn Semester 2026
- Date
- 14.9.2026–19.12.2026, 12:55
- Duration
- 6 Semesters
- Place
- FHNW Campus Brugg-Windisch
- Final application date
- 19.9.2026
Contact us
For further information about studying at the FHNW School of Computer Science, please contact us.

Dr. Marie-Thérèse Rudolf von Rohr

Thomas Mandelz
- Phone
- +41 56 202 75 36 (Direct)
- thomas.mandelz@fhnw.ch

Study Administration and Advisory
- Phone
- +41 56 202 99 33 (Direct)
- start.informatik@fhnw.ch
Info-Events
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