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Study Machine Learning and Data Analytics in Heidelberg (2026/27)
Studying Machine Learning and Data Analytics as an international student prepares you to transform large datasets into predictive models and intelligent solutions across industries. The program combines statistics, linear algebra, programming (Python/R), machine learning algorithms, deep learning, data engineering, cloud platforms, and visualization with hands-on projects using real-world datasets. Germany and other leading study destinations offer strong applied research environments and partnerships with tech firms, automotive companies, and AI startups. Graduates gain highly in-demand expertise for international careers in data science, machine learning engineering, AI development, business analytics, research, and digital innovation worldwide.
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Most Popular Machine Learning and Data Analytics Universities in Heidelberg
Top 1 Machine Learning and Data Analytics Universities (by popularity)
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Most Popular Machine Learning and Data Analytics Study Programs in Heidelberg
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Fees & Costs
German Students 
Other EU Students 
Non-EU Students German StudentsDegree
Tuition Fee
Master
No tuition fees
Disclaimer: You should use this text as a general guide, but it cannot serve as a guarantee. Keep in mind that there is no universal tuition fee that applies to all study programs and all student groups. Hence, we urge you to always individually double-check the specific fees of the specific study programs on their official websites.
Deadlines
Below are the most frequent application deadlines for Machine Learning and Data Analytics programs in Heidelberg.
German Students Other EU Students 
Non-EU Students Non-EU StudentsWinter Semester
Summer Semester
| Admission-restricted courses | Admission-free courses | |
|---|---|---|
| Master | 15 May | No courses |
Master
Admission-restricted courses
15 May
Admission-free courses
No courses
Specific courses may have different application deadlines. Please always double-check the information individually. 
Numerus Clausus (Admission Restriction)
For degree courses with a numerus clausus, part of the study places are allocated according to the grade point average (GPA) of the previous degree. Selection is generally based on how many applicants apply for a place. The higher the grade, the more difficult it is to get onto the course. The German grading system ranges from 1.0 (very good) to 6.0 (unsatisfactory).
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Top 1 Most Selective Machine Learning and Data Analytics Program in Heidelberg (based on Numerus Clausus)
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