Applied Artificial Intelligence in Healthcare study programs

Study Applied Artificial Intelligence in Healthcare in Germany (2026/27)

Applied Artificial Intelligence in Healthcare in Germany

Applied Artificial Intelligence in Healthcare in Germany

Overview Deadlines

Studying Applied Artificial Intelligence in Healthcare in Germany is a great choice because the country is a leader in engineering, medical technology, and research-driven innovation. You’ll learn how to apply AI to real healthcare challenges such as diagnostics, medical imaging, patient monitoring, and hospital decision-making, supported by strong academic programs and advanced digital health ecosystems. With Germany’s high standards for healthcare quality, data security, and clinical practice, it’s an ideal environment to build practical skills for careers in health AI, medical technology, and digital health innovation.

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Fees & Costs

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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 Applied Artificial Intelligence in Healthcare study programs in Germany.
German Students
Other EU Students
Non-EU Students
Non-EU Students
Winter Semester
Summer Semester
Admission-restricted courses Admission-free courses
Specific courses may have different application deadlines. Please always double-check the information individually.
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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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