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55.HochschuleBielefeld-UniversityofAppliedSciencesandArts
University note
Hochschule Bielefeld (HSBI) – M.Sc. Data Science (Research Master)
Program Overview
| Field | Details |
|---|
| University | Hochschule Bielefeld (HSBI) – University of Applied Sciences and Arts |
| Campus | Gütersloh |
| Degree | Master of Science (M.Sc.) |
| Program | Data Science (Research Master) |
| Study Mode | Full-time |
| Language of Instruction | English |
| Duration | 4 semesters |
| ECTS | 120 |
| Start of Studies | Winter Semester & Summer Semester |
| Admission Type | Restricted Admission (Selection Process) |
| Tuition Fee | No tuition fees (Semester contribution only) |
Program Highlights
- Fully taught in English
- Research-oriented Master's programme
- Continuous project-based learning throughout all four semesters
- Individual supervision by professors
- Collaboration with renowned companies and research institutions
- Opportunity to publish research at international conferences
- Strong focus on Artificial Intelligence and Machine Learning
- Excellent preparation for doctoral studies (PhD)
- Small class sizes (around 20 students)
Study Objectives
Graduates will develop expertise in:
- Data Mining
- Machine Learning
- Artificial Intelligence
- Generative AI
- Big Data Architectures
- Python Programming
- Scientific Research
- Agile Research Project Management
- Scientific Publications
- Ethical and Responsible AI
Curriculum
Semester 1
- Project Phase I (12 ECTS)
- Introduction to Applied Research (6 ECTS)
- Compulsory Elective Subject – Data Science (6 ECTS)
- Scientific Interchange (1 ECTS)
- Project-Specific Elective Module (5 ECTS)
Semester 2
- Project Phase II (7 ECTS)
- Agile Research Project Management (6 ECTS)
- Compulsory Elective Subject – Data Science (6 ECTS)
- Compulsory Elective Subject – Data Science (6 ECTS)
- Project-Specific Elective Module (5 ECTS)
Semester 3
- Project Phase III (12 ECTS)
- Social Implications of Data Science (6 ECTS)
- Compulsory Elective Subject – Data Science (6 ECTS)
- Scientific Interchange (1 ECTS)
- Project-Specific Elective Module (5 ECTS)
Semester 4
- Master's Thesis (24 ECTS)
- Colloquium (6 ECTS)
Core Elective Modules
Students may choose courses such as:
- Introduction to Data Science
- Big Data Architectures
- Data Mining & Machine Learning
- Artificial Intelligence
- Advanced Machine Learning
- Artificial Intelligence for Robotics
Admission Requirements
Academic Qualification
Applicants must possess a Bachelor's degree (minimum 180 ECTS) in a related field, such as:
- Computer Science
- Engineering Computer Science
- Applied Mathematics
- Statistics
- Business Information Systems
- Electrical Engineering
- Mechatronics
- Biotechnology
- Digital Technologies
- Digital Logistics
- Related STEM disciplines
The previous degree must include substantial coursework in:
- Mathematics / Statistics
- Computer Science
Minimum GPA
- German Grade 2.5 or better
English Language Requirement
Applicants must demonstrate:
- English proficiency at CEFR Level B2
A recognized English language certificate is required.
Aptitude Test
Applicants must successfully pass the university's aptitude assessment.
Application Deadlines
| Intake | Application Period |
|---|
| Summer Semester | 1 December – 15 January |
| Winter Semester | 1 June – 15 July |
The programme accepts applications for both Winter and Summer intakes.
International Application Process
Applicants with foreign university qualifications should first consult the HSBI International Office to determine the correct application portal.
Required application documents include:
- Bachelor's Degree Certificate
- Transcript of Records
- Diploma Supplement (if available)
- English Language Certificate
- Other supporting academic documents
Research Project Selection
Applicants must select:
- 1 highest-priority research project
- 2 alternative project choices
from the published Project Pool.
Motivation Video
Applicants must upload a 2-minute video in English explaining:
- Motivation for joining the programme
- Why the selected research project was chosen
The evaluation considers:
- Presentation skills
- Structured argumentation
- English communication skills
- Suitability for the selected project
Interview
Successful applicants are invited to an interview with the supervising professor.
The interview evaluates:
- Academic suitability
- Project fit
- Research potential
Successful candidates receive a Learning Agreement outlining the expectations of the research project.
Winter Semester 2026/2027 Timeline
| Activity | Date |
|---|
| Project Pool Published | 20 May 2026 |
| Online Information Day | 9 June 2026 |
| Application Deadline for Projects | 15 July 2026 |
| Learning Agreement Interviews Completed | 31 July 2026 |
Career Opportunities
Graduates can pursue careers as:
- Data Scientist
- AI Engineer
- Machine Learning Engineer
- Data Engineer
- Research Scientist
- AI Research Associate
- Big Data Engineer
- Analytics Consultant
Career pathways include:
- Applied Research
- Industry R&D
- Doctoral Studies (PhD)
- Technology Startups
- AI Product Development
Study Benefits
Students benefit from:
- Permanent research projects throughout the programme
- Collaboration with industry and research institutes
- Opportunity to publish at international conferences
- Close supervision by professors
- Small-group teaching
- Strong preparation for doctoral research
- Flexible entry in both Winter and Summer semesters
- Access to projects with renowned companies in the East Westphalia-Lippe (OWL) region
Contact
International Admissions
Email
admission@hsbi.de
Programme Coordinator
Natalja Bogdanez, M.Sc.
Email
natalja.bogdanez@hsbi.de
Phone
+49 5241 21143-35
Academic Programme Director
Prof. Dr.-Ing. Christian Schwede
Email
christian.schwede@hsbi.de
Phone
+49 5241 21143-49
Official Sources
- Programme Page: https://www.hsbi.de/en/study-programmes/data-science-research-master
- International Admissions: https://www.hsbi.de/en/international-office