Data Science and Machine Learning, MSc University of Oldenburg

All modules are taught in English.

The Data Science and Machine Learning programme concentrates on data science research activities with a focus on life and natural sciences, including medicine.

Students in the programme acquire professional and interdisciplinary skills to meet the challenges of digital transformation in society and at the university. They master the methodological foundations of complex data analysis with a strong focus on machine learning methods, and they develop a comprehensive understanding of developing, implementing, and analysing data-driven algorithms on both technical and conceptual levels. The programme enables students to gain specific expertise in applying analytical methods across three specialisation areas and effectively communicate insights to domain experts. We offer the following three specialisations:

• Theoretical Foundations of Machine Learning in Mathematics and Natural Sciences
• Data Science and Machine Learning in Medicine and Health Care
• Data-Driven Speech and Hearing Sciences

Students will experience a high proportion of guided but independent research directly in the laboratories of the university.

Reasons to study Data Science and Machine Learning

• Get to know, apply and develop state-of-the art machine learning methods across a broad variety of different data modalities
• Specialise in one of three areas of specialisation (theoretical foundations, health care, hearing science) and learn how to address data-bound problems in these domains
• Develop expertise that is sustainable and relevant to society
• English-taught programme with many international students
• Interdisciplinary background of teachers and students
• Small groups with 30 students per year
• Optional integrated language courses and internship
• Extensive support structures (tutorials, learning workshops etc.)

Career perspectives

Graduates will be excellently qualified for specialist and management positions in various fields of activity involving the collection, management, processing, analysis and interpretation of digital data, as well as for academic research. Possible career fields include:

• data scientist with a focus on data analysis and model development and validation
• data analyst specialising in data cleaning and preparation
• data engineer specialising in the development and management of data pipelines
• machine learning engineer specialising in the selection, adaptation and further development of machine learning (including deep learning) methods for various information processing tasks

Contacts with companies and start-ups will also be promoted.

The University of Oldenburg offers in-person teaching, which requires students to be present in Oldenburg.

The programme is a full-time programme. Part-time studies can be arranged on an individual basis.

Classes start mid-October.

Lecture-free periods can be used for internships, independent study, or holidays:

• summer break: beginning of August to mid-October
• winter break: beginning of February to mid-April

International applicants:
Applications via uni-assist open on 15 March and close on 30 April for non-EU students and on 15 July for EU students. (To ensure a smooth admission process, we strongly recommend submitting your documents by 15 June.)

Applicants with a German Bachelor's degree:
The application period via the university opens on 1 June and closes on 15 July.

The programme (120 CP total) consists of 42 CP in core modules for methodological foundations, 48 CP in a specialisation including 12 CP in a group project and 30 CP for the Master's thesis.  

Core: Compulsory modules: 30 CP

• Introduction to Data Science
• Applied Deep Learning
• Machine Learning
• Statistical Learning
• Interdisciplinary Lecture Series Data Science & Data Ethics

Core: Elective modules: choose 12 CP

• Exploring Research Data Management
• Trustworthy Machine Learning
• Machine Learning II
• Advanced Topics in Applied Deep Learning
• Time Series Analysis
• Introduction to IT Security
• Designing Explainable Artificial Intelligence
• Applied AI – Multimodal-Multisensor Interfaces I: Foundations, User Modelling, and Common Modality Combination
• Applied AI – Multimodal-Multisensor Interfaces II: Language Processing, Software, Commercialisation, and Emerging Directions
• Internship
• Current topics in Data Science and Machine Learning
• German or Academic English courses

_______

Specialisation: Theoretical Foundations of Machine Learning in Mathematics and Natural Sciences

Compulsory modules: 18 CP

• Theoretical Foundations of Machine Learning and Data Science
• Group Project

Elective modules (choose 18 CP + additional 12 CP from the core area)

• Mathematical Foundations of Statistical Learning
• Introduction to Numerical Methods for Partial Differential Equations 
• Computational Physics
• Modelling of Complex Systems
• Current Topics in Theoretical Foundations of Machine Learning in Mathematics and Natural Sciences
• Information Processing and Communication

_______

Specialisation: Data Science and Machine Learning in Medicine and Health Care

Compulsory modules: 30 CP

• Medical Data Pipelines
• Medical Data Analysis with Deep Learning
• Big Data Analytics and Clinical Decision Support
• Group Project

Elective modules: choose 18 CP

• Special Topics in "Medical Informatics"
• Medical Technology
• Medical Basics
• Bioinformatics & Omics
• Current Topics in Data Science in Medicine and Health Care

_______

Specialisation: Data-Driven Speech and Hearing Sciences

Compulsory modules: 30 CP

• Digital Signal Processing
• Hearing and Communication Acoustics
• Algorithms for Speech Processing
• Group Project

Elective modules: choose 18 CP

• Information Processing and Communication
• Introduction to Neurophysics
• Processing and Analysis of Biomedical Data
• Human Computer Interaction
• Current Topics in Data-Driven Speech and Hearing Sciences

Master's thesis: 30 CP

In the core and in all three specialisations, three modules (6 CP each) are integrated for the recognition of an optional study abroad in the third semester. The group project can also be performed abroad.

The Internship module (6 CP) in the compulsory elective area of the core area enables a professional internship lasting 180 hours, in which students experience data science and machine learning in practical application. The internship can take place at public institutions, private companies, scientific institutions and other organisations in Germany or abroad.

No tuition fees

Approx. EUR 400 per semester

You should expect to spend about EUR 950 per month to cover personal expenses (accommodation, health insurance, food).

Applicants are eligible for admission if they have completed a Bachelor's degree of at least 180 ECTS credits (three year full-time study) in the fields of data science, mathematics, statistics, physics, computer science, business informatics or a closely related field. All applicants must prove the following upon application:

• 30 credit points (900 hours) in mathematics and computer science including at least
  • 20 credit points in mathematics, of which
    • 5 credit points in probability theory or statistics
    • 5 credit points in analysis or linear algebra 
  • 10 credit points in computer science, of which
    • 5 credit points in the field of algorithms
    • 5 credit points in a higher programming language (preferably Python)

Students without a degree in the fields of data science, mathematics, statistics, physics, computer science, or business informatics must prove an additional 15 credit points (450 hours) in data science. Competencies in data science can also be proven with work experience in the field.

If students can prove 20 credit point in mathematics and 10 credit points in computer science and do not miss more than five credit points in the areas of statistics and algorithms/programming, they may catch up on missing competencies in an additional module.

Please note that one ECTS credit point equals 30 hours of work including courses, preparation, self-study and exams.

Students will be admitted based on a ranking order. The admissions committee will evaluate the applicant based on the documents presented. The degree of eligibility depends upon the sum of the points from categories A and B. The maximum number of points is six.

Category A:

Grade average of qualified Bachelor's degree:

1.00 to 1.5: 4 points
1.51 to 1.75: 3.5 points
1.76 to 2.0: 3 points
2.01 to 2.25: 2.5 points
2.26 to 2.5: 2 points
2.51 to 2.75: 1.5 points
2.76 to 3.0: 1 point

For the conversion of marks from abroad, see:
https://www.uni-oldenburg.de/en/students/recognition/conversion-foreign-grades/.

Category B:

Further points can be obtained through additional qualifications. Please include relevant documents in your application (e.g. employer's reference, internship certificate, supervisor's certificate). These are evaluated by the admissions committee using the criteria outlined below:

• Relevant professional or scientific activity in the field of data science or machine learning (work experience, internships, Bachelor's thesis; at least three months full-time work) – one point per activity, max. two points in total.

Documents to be included in the application:

The following documents must be enclosed with the application in German or English. (Documents in other languages will need to be accompanied by certified translations):

• Bachelor's degree and transcript of records
• completed specific eligibility form (to be found on course website and in application portal)
• proof of mastery of English (see language requirements)
• if applicable,
  • certificates concerning relevant internships or work experience
  • the subject of the Bachelor's thesis

We do not ask for letters of recommendation or letters of motivation!

Applicants whose native language is not English must produce a proof of English proficiency. English proficiency can be proven by a Bachelor's degree with English as the language of instruction from an EU country. Otherwise a certified proof of English language skills at a B2 level is needed (not older than two years). If you provide a proof of C1 level or higher, it may be six years old at most. A test from a language centre of a German university is accepted. The admissions committee can accept other evidence provided it demonstrates sufficient language qualification.

Further details on the English language requirements (including a reference table for the different tests) can be found on the website of the university.

Knowledge of German is not necessary for admission.

The university offers free language courses during the semester and during the semester breaks (as intensive courses). You can have German or academic English courses count as 6 credits towards your degree.

International applicants:
Applications via uni-assist open on 15 March and close on 30 April for non-EU students and on 15 July for EU students. (To ensure a smooth admission process, we strongly recommend submitting your documents by 15 June.)

Applicants with a German Bachelor's degree:
The application period via the university opens on 1 June and closes on 15 July.

Check funding opportunities here: https://uol.de/p15263en.

Students are permitted to work alongside their studies. If you are a student from a non-EU country, you are allowed to work 120 full or 240 half workdays per year.

We offer many student jobs. These jobs are usually offered (once the students have studied here for a few months) in the areas of tutorials and research assistant work.

The international office of the university also has contacts to companies that are willing to employ international students.

Please keep in mind that finding a student job is much easier if you speak some German.

The student union ("Studentenwerk") owns and runs several different student accommodation buildings around the city. Although student rooms in Germany are typically rented unfurnished, the "Studentenwerk" also provides furnished rooms for international students at affordable rates. They also help with finding private accommodation for international students.

There are also several ways to find private accommodation including:

• local newspapers, e.g. the NWZ
• Websites like www.wg-gesucht.de, where apartment listings can be narrowed down by desired criteria, such as number of flatmates or facilities available
• The "Schwarzes Brett" (notice board) on Stud.IP and several boards in the student canteen / "Mensa" building on campus (if you are still looking once you arrive in Oldenburg)

• Individual study and career counselling by the programme coordinator
• Study and Career Counselling Service of the university
• Career Day of the university

The International Office and the Study and Career Counselling Service of the university offer many events and support for international students.

Carl von Ossietzky University of Oldenburg was founded in 1973, making it one of Germany‘s young universities. Its goal is to find answers to the major challenges society faces in the 21st century – through interdisciplinary, cutting-edge research.

The pathways on the Oldenburg campus are short: the university's academic staff and administrative staff work closely together, using an interdisciplinary approach. Many are integrated into special research areas, research groups, and European clusters of excellence.

The university cooperates closely with more than 200 other universities worldwide and is also affiliated with non-university institutes in the areas of research, education, culture, and business.

The University of Oldenburg prepares 16,000 students for professional life. It offers a broad range of disciplines, from language studies, cultural studies, and the humanities to educational sciences, art and musicology, the economic and social sciences, mathematics, computer science, and the natural sciences as well as the medicine and health science programmes.

The development of the excellent research performance of Oldenburg has started to attract the Max-Planck, Helmholtz, Leibniz, and Fraunhofer Associations, which have established research groups and junior researcher groups in Oldenburg particularly in the last few years.

The University of Oldenburg is a centre of research with national and international appeal. All academic fields have developed concise criteria for excellence, organised according to quality, effectiveness, efficiency, and originality and in compliance with international standards. The university creates space for scientific networking within the university and beyond. Interdisciplinary and social responsibility are identity-forming hallmarks of research in Oldenburg. Scientific networking also leads to an efficient transfer of research results in the programmes.

Oldenburg looks back on more than 900 years of history and is now, with its +170,000 inhabitants, a centre of cultural, scientific and economic life in the region of North-West Germany.

Oldenburg is a good place to live. A mix of entertainment and culture – bars, restaurants and trendy venues as well as theatres and a number of museums – create a big-city feeling. Yet it is a safe place where you can get around easily on your bicycle, as most students do. The city has a well-developed bus system. Student fees cover public transport in the city itself and all over Germany. The green city is also directly connected to the European rail network.

For further information, please visit the following website: https://www.oldenburg.de/.

This is how the mayor of Oldenburg sees the city:

"Oldenburg is a modern and growing city with a tremendous quality of life and more than 170,000 inhabitants. Irrespective of whether you want to enjoy Oldenburg as a tourist, come as a student or plan to live and work in our beautiful city – you are always welcome!

We invest in new housing, more places in daycare centres and, of course, in a necessary infrastructure with streets, educational institutions or the prerequisites for the digital future. All the above-mentioned points are important conditions for participation in events and life in our city.

For many years, these topics have been the focus of my work, and successes are visible in many places. At the moment, numerous flats and houses are built in all districts of Oldenburg. Since 2014, we have invested more than 130 million EUR in care facilities. Other objectives of our work are a good cultural and educational offer as well as a strong commitment to climate protection.

Oldenburg offers an abundance of leisure activities as well as support for education and integration. With the Carl von Ossietzky University, the Jade University of Applied Sciences, the Private University of Applied Sciences for Business and Engineering as well as more than 70 schools of general education, vocational colleges, technical colleges and private schools, we are the region's centre of education. Our thriving economy also offers excellent prospects to companies.

These are just some examples of a successful and positive urban development which makes Oldenburg such a lively and attractive city. Convince yourself – Oldenburg is always worth a visit!"

Excerpt from: https://www.oldenburg.de/sprachversionen/gb.html