The MSc Data Science offers a comprehensive education in the concepts and methods of data science, incorporating knowledge and methodology from Computer Science and Mathematics. Special emphasis is placed on the sound training of fundamental (mathematical) concepts as to be able to competently assess the properties and limitations of the methods. As the programme includes compulsory courses in mathematics and computer science, we expect candidates to have a strong background in both areas. The main topics are: Machine Learning (ML), AI, and Deep Learning Statistics, Matrix Algorithms, and mathematical foundations of ML Data Structures, Algorithms and Optimisations for Big Data Data Engineering with Big Data Infrastructures and Data Wrangling The programme offers a wide range of application areas in collaboration with adjacent departments: Medicine, Economics, Engineering, Geography, Material Science, Physics and others. It provides close connections to industry and research. The field of data science as a modern interdisciplinary science underpins the process of digitalisation and the effective utilisation of data in many application areas.
The programme consists of the following course categories (called module groups) Core Data Science Methods (32 credits) Algorithms and Data Engineering Machine Learning Mathematical Foundations Advanced Data Science Methods / Elective Courses (at least 36 credits) Broad range of elective modules in mathematics and/or computer science, e.g. Quantum Algorithms, Statistics, Optimisation, Modelling, Deep Learning, etc. Scientific Project Work Data Science Project (10 credits) Seminar: Mathematics and Computer Science (4 credits each) Social Aspects of Data Science / Ethics (4 credits) Master's Thesis (30 credits) Tips on how to organise your studies can be found in our FAQs: https://www.uni-augsburg.de/en/fakultaet/fai/informatik/studienangebot/msc-dsc/#faq_contacts.
Course details verified 09 Sep 2026 — intakes, entry requirements and course facts · official source
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Winter semester
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Most universities admit on a rolling basis — we confirm the exact application deadline for your profile, free.
Admission is possible for students with a (nearly completed) Bachelor's degree in Mathematics, Computer Science and related areas. Applicants undergo an aptitude test. More specifically, we expect students to show proof of sufficient previous knowledge in the following areas: Multivariate Calculus/Analysis (at least 5 ECTS CP) Linear Algebra (at least 5 ECTS CP) Fundamentals of (Higher) Programming Languages (at least 4 ECTS CP) Practical Programming Experience (at least 4 ECTS CP), e.g. by practical exercises or a lab course Algorithms or Numerical Methods (at least 5 ECTS CP) Discrete Structures/Mathematics, Databases or Data Engineering (at least 5 ECTS CP) and Data Science or Machine Learning (at least 4 ECTS CP) For details please also see our FAQ at https://www.uni-augsburg.de/en/fakultaet/fai/informatik/studienangebot/msc-dsc/#faq_contacts.
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Typical graduate salary — Computer Science / IT, Europe
EUR 42,400–54,300/yr
· ≈ ₹44.9 L–₹57.5 L/yr
This is an indicative early-career range for the whole Computer Science / IT field in Europe,
from official graduate-outcome data — not a figure for this programme or university, and not a guarantee of
what you will earn. What you actually earn depends on the role, employer, city and your visa.
Rupee figure converted at the 2 Nov 2026 mid-market rate; your
bank's rate will be worse and currencies move, so use it for planning, not as the amount you will receive.
No tuition fee. Checked against the university's own fees page. We confirm the current fee and the scholarships you qualify for — free.
The main intake is Winter semester. Most universities admit on a rolling basis — we confirm the exact deadline for your profile, free.
Admission is possible for students with a (nearly completed) Bachelor's degree in Mathematics, Computer Science and related areas. Applicants undergo an aptitude test. More specifically, we expect students to show proof of sufficient previous knowledge in the following areas: Multivariate Calculus/Analysis (at least 5 ECTS CP) Linear Algebra (at least 5 ECTS CP) Fundamentals of (Higher) Programming Languages (at least 4 ECTS CP) Practical Programming Experience (at least 4 ECTS CP), e.g. by practical exercises or a lab course Algorithms or Numerical Methods (at least 5 ECTS CP) Discrete Structures/Mathematics, Databases or Data Engineering (at least 5 ECTS CP) and Data Science or Machine Learning (at least 4 ECTS CP) For details please also see our FAQ at https://www.uni-augsburg.de/en/fakultaet/fai/informatik/studienangebot/msc-dsc/#faq_contacts. English: E.G. TOEFL iBT (since 2026): 4 Reading: 4 Listening: 4 Speaking: 4 Writing: 4 Cambridge English Qualifications: B2 First TOEIC: 785 Reading: 385 Listening: 400 Speaking: 160 Writing: 150 UNIcert® English: UNIcert® II IELTS Academic: 5.5 TOEFL iBT (before 2026): 72 Reading: 18 Listening: 17 Speaking: 20 Writing: 17.
The programme runs about 24 months full-time.
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