
Data, Sciencе and АI
(Starting: Winter Semester)
- Starting
- Winter Semester
- Mode of Admission:
- no admission restriction
- Study Mode:
- On campus
Five Reasons to choose this Bachelor's Program





Course Description
The B.Sc./B.A. Data, Science and AI at the University of Bayreuth combines mathematics, computer science, and AI to equip students with the skills to analyze complex data and solve real-world problems. This program fosters a deep understanding of AI methodologies, preparing graduates for leadership roles in technology, science, and industry.

The program is designed for motivated students with a strong interest in mathematics, computer science, and AI. Ideal candidates are those who seek to apply computational methods to solve complex problems across various disciplines. Students should possess analytical thinking, problem-solving skills, and a passion for technological innovation.
Special Program Features
One Program—Two Degree Tracks
You can shape your educational path to match your interests and career goals by choosing between science or humanities tracks, with an optional B.A. degree in the humanities.
A Dynamic Blend of Fields
By blending math, computer science, and AI with knowledge in life sciences, business, and humanities, this program equips you with a versatile skill set for real-world challenges.
Dynamic Campus, Inspiring Location
Bayreuth provides vibrant campus life in a city known for its cultural heritage and natural beauty, with ample opportunities for personal growth, sports, and cultural engagement.
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ZSTB: Studying at the University of Bayreuth – Digital information event on the Day of Repentance and Prayer
Have you (soon to be) graduated from high school and still have no idea what you want to study? Would you like to study in Bayreuth, but don't know exactly how to find out about degree programs and how to get a place at university? Or would you like to know what you need to consider when starting a degree program?
Requirements
Qualification Requirements
The application requirements for the study program in "Data, Sciencе and АI" are:
Abitur or equivalеnt
at least B2 (CΕFR)
at least A1 (CEFR), to be proved by the end of the second semester, at the latеst
TestAS Certificate (core module + subject module ‘Mathematics, Computer Science and Natural Sciences’) or SAT certificate (only applies to applicants holding degrees from non-EU/EEA countries).
Recommended skills and interests include strong mathematical preparation, an interest in working with computers, problem-solving abilities, and a high level of motivation and scientific curiositу.
Language Requirements
The following certificates are recognized as proof of your language proficiency.
Specification: at least 'Pass'
Specification: at least grade C
Specification: at least grade B
Application & Admission
Application Deadlines
Other EU Students Enrolment is digital via CAMPUSonline; the signed application and all documents must be uploaded by 1 October. For programmes with an aptitude assessment, enrolment is possible until 1 October after admission; for restricted programmes the deadline is announced during the admission procedure.

| Intake | Winter Semester |
| Application start | 15 April |
| Application deadline | 01 Octoberin > 11 months |
| Application mode | Uni-assist (VPD) |
German Students

| Intake | Winter Semester |
| Application start | 15 April |
| Application deadline | 01 Octoberin > 11 months |
| Application mode | Directly at university |
Other EU Students

| Intake | Winter Semester |
| Application start | 15 April |
| Application deadline | 01 Octoberin > 11 months |
| Application mode | Directly at university |
Application Procedure & Selection
Application Documents
to be submitted by the end of the second semester, at the latеst
Core module + subject module ‘Mathematics, Computer Science and Natural Sciences’
Alternatively, a SAT certificate must be provided.
Only applies to applicants holding degrees from non-EU/EEA countries.
only applies to applicants holding degrees from non-EU/EEA countriеs
Testimonials
Armed with a robust background in mathematics and computer science, along with both theoretical and practical expertise in computational, data and AI methodologies, students will be well-equipped to thrive in today’s knowledge-based economy. Furthermore, they will be poised to assume leadership roles, driving change and fostering innovation across a wide range of sectors.
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