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Data Science and Machine Learning, MSc

University of Oldenburg· Oldenburg

Medical Informatics — ریاضیات، علوم طبیعی

زبان‌های تدریس
English
شروع
Winter semester
مدت
۴ نیم‌سال
شهریه
بدون شهریه
هنوز بررسی نشده

برای بررسی، دکمهٔ «دریافت اطلاعات از سایت دانشگاه» را بزن.

شرایط زبان، مدارک، مهلت‌ها و هزینه‌ها مستقیم از وب‌سایت دانشگاه استخراج و با رنگ متمایز به تب‌ها اضافه می‌شود.

Degree
Master of Science in Data Science and Machine Learning
Course location
Oldenburg
Teaching language
• English
Languages
All modules are taught in English.
Full-time / part-time
• full-time
Programme duration
4 semesters
Beginning
Winter semester
Additional information on beginning, duration and mode of study
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
Application deadline
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.
Tuition fees per semester in EUR
None
Combined Master's degree / PhD programme
No
Joint degree / double degree programme
No
Description/content
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.
مهلت درخواست
close on 30 April for non-EU students
مشاهدهٔ صفحهٔ اصلی دوره وب‌سایت دوره
تماس

University of Oldenburg

Department of Health Services Research

Study Programme Coordination

Ammerländer Heerstr. 114–118 26129 Oldenburg

dsml@uol.deوب‌سایت دوره