Master's in Mathematics of Machine Learning and Data Science
Master the advanced mathematical foundations and algorithmic methods driving modern machine learning and data science.
Best for:Best for quantitative bachelor's graduates with a strong background in mathematics seeking rigorous theoretical training in machine learning.
Overview
Heidelberg University offers a comprehensive four-semester Master of Science programme focusing on the mathematical concepts and methods underpinning machine learning and data analysis. Students explore core disciplines such as differential geometry, dynamical systems, functional analysis, numerical mathematics, optimization, statistics, and topology. The curriculum is designed for students holding a strong bachelor's degree in mathematics or closely related scientific fields with quantitative emphasis. Graduates gain rigorous analytical expertise applicable to advanced research, data science, and complex algorithmic engineering.
What you'll do
- Complete advanced coursework across core mathematical disciplines and machine learning theory
- Participate in seminars, data analysis projects, and optional international exchange units
- Engage in collaborative problem-solving and algorithmic implementation exercises
- Conduct independent research leading to a Master's thesis
Requirements
Degree required: Bachelor of Science in Mathematics, Scientific Computing, Physics, or a closely related discipline with sufficiently broad mathematical training
Degree offered: Master of Science
Language: English; B2 proficiency required, demonstrated by an official certificate such as IELTS Academic 5.5 or equivalent
Instruction: English
- Solid foundation in core areas of mathematics
- Proficiency in quantitative analysis and algorithmic reasoning
- Demonstrated academic achievement with a final bachelor's grade of 2.3 or better
- Open to applicants from all countries who hold an eligible Bachelor of Science degree
Funding & terms
Programme and admissions
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How to apply
Deadline: 2027-03-15
Applicants must submit their application documents through the university's online portal within the official application window. Ensure all academic transcripts and language certificates are prepared and uploaded prior to the deadline.
- BSc degree certificate
- Academic transcripts
- Proof of English language proficiency
Contact
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