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Applied Mathematics and Data Science Master Programs in Germany: Application Deadlines (2026/27)
Studying Applied Mathematics and Data Science as an international student equips you with strong quantitative skills to model complex systems and extract insights from large datasets across science, engineering, and business. The program combines advanced mathematics, statistics, machine learning, optimization, and programming with hands-on data projects in fields such as finance, logistics, healthcare, and technology. Germany and other leading study destinations offer excellent interdisciplinary programs, modern computing facilities, and strong links to industry and research institutions.
Show more...Applied Mathematics and Data Science Master: Application Deadlines for Summer Semester 2027
Below are the most frequent application deadlines for Applied Mathematics and Data Science Master programs for the Summer Semester 2027.
German Students 
Other EU Students 
Non-EU Students | Admission-restricted courses | Admission-free courses | Still open for application | |
|---|---|---|---|
| Master | 15 January | 15 January | 100% of Master programs |
Master
Admission-restricted courses
15 January
Admission-free courses
15 January
100% still open for application
Specific courses may have different application deadlines. Please always double-check the information individually. Applied Mathematics and Data Science Master: Application Deadlines for Winter Semester 2026/2027
Below are the most frequent application deadlines for Applied Mathematics and Data Science Master programs for the Winter Semester 2026/2027.
German Students Other EU Students Non-EU Students | Admission-restricted courses | Admission-free courses | Still open for application | |
|---|---|---|---|
| Master | 15 July | 15 July | 100% of Master programs |
Master
Admission-restricted courses
15 July
Admission-free courses
15 July
100% still open for application
Specific courses may have different application deadlines. Please always double-check the information individually. 
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