M.Sc.Data Science - Digital Health
| Study location | Germany, Nürnberg/Fürth |
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| Type | Master, full-time |
| Nominal duration | 24 months (120 ECTS) |
| Study language | English |
| Awards | M.Sc. (Master of Science in Digital Health and Data Science) |
| Course code | WLH-M37 |
| Accreditation | in accreditation 2023 |
| Tuition fee | €5,400 per semester Non-EU / EEA |
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| Registration fee | €900 one-time non EU/non-EEA |
| Entry qualification | Undergraduate degree (Bachelor's degree or higher) - Regular Track: 3-year Bachelor’s degree (180 ECTS), min. 3.0 German GPA. - Fast Track: 3,5-year Bachelor’s degree (210 ECTS) and a 3.0 German GPA. - The degree should be in Computer Science, Information Systems, (Health) Economics or a similar area of studies and be issued by an accredited university. - Proof of English proficiency: IELTS 6.5. We accept: Academic IELTS, IELTS Indicator I TOEFL iBT I PTE I CAE/CPE/FCE I Duolingo |
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| Language requirements | English |
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| More information |
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Overview
Companies and institutions in the healthcare sector are looking for competent data scientists, who have a solid understanding for handling and creating valuable insights from big data. Be a part of this revolution and shape the future with us!
Programme structure
1st semester
- Fundamentals of Healthcare Management I (Health Systems, Health Issues, Health Law and
Ethics)
- Fundamentals of Digital Health I (E-Health, M-Health, Telemedicine, Electronic Health Record)
- Digital Health Analytics I (Health Data, Information and Communication)
- Digital Health Analytics III (Statistics)
- Digital Health Analytics V (Requirements Management)
- Digital Health Analytics VII (Fundamentals of Programming)
2nd semester
- Fundamentals of Healthcare Management II (Market Access, Regulatory Affairs &
Reimbursement)
- Fundamentals of Digital Health II (Health Information and Application Systems)
- Digital Health Analytics II (Data Management)
- Digital Health Analytics IV (Data Preprocessing and Analytics)
- Digital Health Analytics VI (Data Visualization and Dashboards)
- Digital Health Analytics VIII (Machine Learning)
3rd semester
International/Practical Experience: Internship/Global Study Semester
4th semester
- Master Thesis: Master Thesis set-up (Master Thesis Kolloqium and Thesis Reflexion)
- Innovation Project (Digital Health Innovation Project: Trends in Digital Health)
Career opportunities
Designed for delivering practical skills, methodological competences paired with theoretical knowledge in Digital Health, this study course prepares you for taking over international leadership positions and driving the digital transformation of global healthcare industries.
Take the chance and be ready for careers in Digital Health:
- data science and business intelligence
- data understanding, visualization
- project and program management
- regulation and consultancies
- innovation and leadership
- product and service development
- public health departments
- education and research