Master of Science in Data Science and Machine Learning
Interdisciplinary MSc programme specialising in machine learning for life, natural, and health sciences at University of Oldenburg.
Best for:Best for students with a strong background in mathematics, computer science, or related fields seeking to specialise in machine learning applications across life sciences, healthcare, and natural sciences.
Overview
This Master of Science programme at the University of Oldenburg focuses on data science and machine learning, with specialisations in theoretical foundations, healthcare, and speech/hearing sciences. Students gain expertise in developing, implementing, and analysing data-driven algorithms while working closely with university laboratories. The curriculum combines core modules in machine learning, deep learning, and statistical analysis with specialised electives, ensuring a strong technical foundation and practical research experience. The programme is taught entirely in English and attracts an international cohort, fostering interdisciplinary collaboration. Graduates are prepared for careers in data science, machine learning engineering, and academic research, with strong industry and startup engagement opportunities.
What you'll do
- Develop and implement machine learning models for complex data analysis across life and natural sciences.
- Conduct independent research in specialised areas such as theoretical foundations, healthcare, or speech/hearing sciences.
- Apply data-driven algorithms to solve real-world problems in interdisciplinary domains.
- Collaborate with university laboratories and industry partners on research projects.
- Participate in group projects and contribute to interdisciplinary teamwork.
- Develop expertise in data ethics and responsible AI practices.
- Complete a 30-credit master’s thesis under academic supervision.
Requirements
Degree required: Bachelor’s degree (180 ECTS credits) in data science, mathematics, statistics, physics, computer science, business informatics, or a closely related field.
Language: English; B2 level proficiency (IELTS Academic 5.5, TOEFL iBT 72, or equivalent).
Instruction: English
- 30 ECTS credits in mathematics and computer science, including 20 credits in mathematics (with 5 credits in probability/statistics and 5 in analysis/linear algebra).
- 10 ECTS credits in computer science, including 5 credits in algorithms and 5 in a higher programming language (preferably Python).
- Proficiency in Python programming.
- Basic understanding of data analysis and machine learning principles.
- Applicants must have completed a Bachelor’s degree with at least 180 ECTS credits.
- Students without a relevant degree may need to complete additional 15 ECTS credits in data science or demonstrate equivalent work experience.
- No German language skills required.
Funding & terms
Programme and admissions
Admissions not verified
A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.
- Intake
- Not confirmed by the source
- Duration
- Not confirmed by the source
- Teaching language
- Not confirmed by the source
- Taught / research mode
- Not confirmed by the source
- Study mode
- Not confirmed by the source
- Campus
- Not confirmed by the source
- Prerequisites
- Not confirmed by the source
- Application instructions
- Not confirmed by the source
- Tuition
- Not confirmed by the source
- Funding
- Not confirmed by the source
How to apply
Deadline: 15 March - 30 April (non-EU applicants) / 1 June - 15 July (EU applicants)
Applicants must submit their application through the uni-assist portal. Required documents include proof of degree, transcripts, language proficiency certificates, and evidence of required ECTS credits in mathematics and computer science. No letters of recommendation or motivation letters are required. Detailed instructions are available on the programme’s official website.
- Proof of Bachelor’s degree (transcript)
- Transcripts of all university courses
- Proof of English proficiency (B2 level)
- Proof of required ECTS credits in mathematics and computer science
- Passport or ID copy
Contact
DAAD International Master's Programmes Team· Admissions Support
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.