BSc Computer Science
A rigorous grounding in algorithms, systems, software and applied artificial intelligence.
- Qualification
- allgemeine Hochschulreife oder ein als gleichwertig anerkannter ausländischer Abschluss
- Academic credits
- 120
- Study mode
- Online / Hybrid / Campus
- Language of instruction
- Deutsch / English
- Duration
- 4 Semester
- Start
- 1. Oktober 2027
- Tuition
- 2.450 EUR pro Semester, insgesamt 9.800 EUR
- Application deadline
- 15. Juli 2027
Overview
A rigorous grounding in algorithms, systems, software and applied artificial intelligence. The programme combines scientific foundations with project-based engineering practice, delivered in structured semesters with supervised teaching.
Curriculum
Illustrative curriculum. The officially approved module structure will be published once programme documentation is available.
Semester 1
- Programming
- Data Structures
- Discrete Mathematics
- Computer Systems
Semester 2
- Algorithms
- Operating Systems
- Databases
- Computer Networks
Semester 3
- Software Engineering
- Web Technologies
- Distributed Systems
- Cloud Computing
Semester 4
- Artificial Intelligence
- Machine Learning
- Cybersecurity
- Data Science
- Final Project
Learning outcomes
- Apply scientific method to technical problems
- Design, model and evaluate complex systems
- Communicate results to specialist and international audiences
- Assess technological developments in ethical and legal terms
Admission requirements
- Recognised secondary qualification or equivalent — higher education entrance qualification including mathematics and one natural science (overall grade 2.5 or better)
- Evidence of proficiency in the language of instruction — English C1 (IELTS 7.0 / TOEFL iBT 95) or German C1 (TestDaF 4x4 / DSH-2), depending on the language of instruction
- Complete application documentation — transcripts, language certificate, CV and identity document
Career opportunities
- Development and design roles in technology-driven organisations
- Research and development in institutes and industry
- Project and systems responsibility in interdisciplinary teams
- Progression to master's or doctoral study
Virtual laboratories
Practical engineering education requires laboratory work. TU Eisenfeld develops virtual laboratory environments in which students work with realistic models, measurement data and control tasks.
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