Computer science thrives on innovation and scientific curiosity – from developing new algorithms to analysing the social impact of digital technologies.

We reflect this in our teaching through:

• Research-oriented teaching formats: project work, theses and seminars with a publication focus, for example in AI research, cybersecurity or environmental informatics.
• Practical application: students work in research groups and academic disciplines as early as their bachelor’s degree and apply scientific methods.
• Critical reflection: developing independent research questions and discussing results in interdisciplinary contexts.

This prepares students for lifelong learning and for responsible roles in academia, business or education.

Digital technologies shape our society – designing them requires ethical and ecological responsibility.

Our teaching therefore conveys:

• Technical and societal perspectives: courses on AI ethics, data protection and green IT, for example “Bias in Algorithms” or “Energy-Efficient Systems”.
• Practical implementation: case studies, debates and practical projects, such as developing sustainable software.
• Critical discussion: questions such as “What responsibility do developers bear?” are addressed in interactive formats.

Our goal is to enable students to design digital solutions for the common good.

Computer science is both a driver and subject of digitalisation. Our teaching therefore covers three central dimensions:

• Teaching content: we convey core competencies of digital transformation, from algorithms and data structures to AI and machine learning as well as cybersecurity and distributed systems.
• Teaching methods: digital tools such as interactive programming environments, virtual labs and collaborative platforms enable flexible, inclusive learning without losing the in-person character of our university.
• Teaching organisation: digital platforms for examinations, advising and collaboration optimise study organisation and prepare students for modern working environments.

Our goal is to educate digitally confident actors who can not only use technologies, but also shape them.

Digital technologies know no borders – and neither does our teaching. Our degree programmes have an international orientation and offer:

• English-language courses in fields such as data science, AI and software engineering, preparing students for global labour markets.
• Study-abroad semesters at partner universities worldwide, for example through Erasmus+ or double-degree programmes, as well as virtual exchange formats for international collaboration.
• Intercultural competences through courses on global challenges, such as “Digitalisation and Development Policy”, and international research projects.

This prepares students to work in multinational teams and develop digital solutions for global challenges.

Computer science benefits from different perspectives – whether in software development, data analysis or teacher education. We foster an open, respectful teaching culture that regards diversity as an asset. This includes:

• Gender-sensitive teaching: we address gender stereotypes in technology and support women in STEM through mentoring programmes and dedicated events.
• Accessible formats: digital tools and flexible teaching formats, such as video captions and adaptive learning platforms, enable inclusive learning for students from diverse backgrounds.
• Interdisciplinary bridges: cooperation with the humanities, social sciences and natural sciences creates diverse pathways into computer science.

Our goal is to reduce barriers and support talented people regardless of origin, gender or background.

Teaching thrives on dialogue – between teachers and students, as well as between academic disciplines and societal stakeholders. Our formats therefore promote:

• Teamwork: in project work and research groups, students learn to develop solutions collaboratively, for example through agile methods such as Scrum or pair programming.
• Feedback culture: regular course evaluations, open office hours and peer-feedback systems enable the continuous improvement of teaching.
• Public engagement: through public-code projects, citizen science and school partnerships, we bring computer science knowledge to the public and discuss digital issues with citizens.

This prepares students to communicate complex content clearly and make responsible decisions as a team.

A successful degree requires good framework conditions. We offer a range of support options:

• Individual advising on study progress, examinations and stays abroad – in person, by email or in digital office hours.
• Tutorials and mentoring, for example for first-year, international and teacher-education students, as well as learning spaces and exam-preparation workshops.
• Support from the student council, which enriches student life through events, networking opportunities and student advising.

Students also benefit from the “Göttingen Spirit” – close links with non-university research institutes, such as Max Planck Institutes, and a vibrant campus culture. Our goal is to support every student as effectively as possible, so that they can focus on what matters most: studying to shape their future.