Data Science & KI
Euro-FH – Europäische Fernhochschule Hamburg · Hamburg, Germany
QS World University Ranking: N/A
Quick Overview
Apply Now📘 Program Overview
In this Master’s program at Euro-FH, you connect solid data-analysis methods with modern AI technologies. You study Machine Learning, Big Data, and intelligent systems, and learn how data becomes practical applications such as language systems, Computer Vision, and automated decision processes.
The program also focuses on combining technical expertise with project leadership. Through an interdisciplinary practical project, you work on real questions together with students from other study backgrounds and develop skills to manage data-based projects, implement AI solutions in companies, and lead teams in Data Science.
🎯 Course & Curriculum
Course structure
- Build your data science and AI fundamentals with modules including Intelligente Agenten, Planung und KI-Ethik (6 Credits) and Maschinelles Lernen und Simulation (6 Credits).
- Develop practical tool and engineering capability via software and AI requirements engineering with Software- und KI-Requirements Engineering (6 Credits).
- Strengthen your research and data competence with Forschungsbezogene Datenkompetenz (8 Credits) and Empirische Forschungsmethoden (8 Credits).
- Establish leadership capability through Projektmanagement für Führungskräfte (8 Credits) and focus on leading data-driven projects via Praxisprojekt Data Science und KI (6 Credits).
- Choose 2 electives from the data science specialisation module pool (Wahl 2 aus 28) to shape your profile.
- Apply advanced AI techniques and engineering through topics such as Anwendungen in Computer Vision, Natural Language Processing und Robotik (6 Credits) and Weiterführende Techniken der Data Science und KI-Recht (6 Credits).
- Work on leadership- and strategy-oriented development areas like Software- and KI-Requirements Engineering (6 Credits) and Projektmanagement für Führungskräfte (8 Credits) through your integrated projects.
- Complete your Master-Thesis with Master-Thesis (18 Credits).
- Consolidate your learning outcomes into an independent, research-oriented final project that applies data science and AI methods.
Curriculum
90 CP Master of Science (M.Sc.) with electives and Master thesis.
| Semester | No. of modules | Module / subject category | ECTS / CP | Semester total |
|---|---|---|---|---|
| Semester 1 | Core modules | Intelligente Agenten, Planung und KI-Ethik | 6 | 45 |
| Maschinelles Lernen und Simulation | 6 | |||
| Forschungsbezogene Datenkompetenz | 8 | |||
| Software- und KI-Requirements Engineering | 6 | |||
| Projektmanagement für Führungskräfte | 8 | |||
| Praxisprojekt Data Science und KI | 6 | |||
| Weiterführende Techniken der Data Science und KI-Recht | 6 | |||
| Semester 2 | Core modules, electives, and Master thesis start | Anwendungen in Computer Vision, Natural Language Processing und Robotik | 6 | 44 |
| Empirische Forschungsmethoden | 8 | |||
| Master-Thesis | 18 | |||
| One elective module (Data sciences electives pool: Wahl 1/2) | 6 | |||
| One elective module (Data sciences electives pool: Wahl 2/2) | 6 | |||
| Semester 3 | Electives | Master-Thesis (remaining credits) and/ or additional elective learning components | 1 | 1 |
| Total | Core modules, elective modules, and Master-Thesis | 90 CP | ||
Career outcomes
- You become job-ready for data science and AI roles by learning the full workflow from data analysis to machine learning solutions and AI-driven decision making.
- Your elective choices let you build a job-focused profile in areas such as Computer Vision and Natural Language Processing, AI in engineering, and data-driven management topics.
- Project-based learning helps you develop practical delivery skills, supporting roles like Data Scientist, Data Analyst, Analytics Specialist, or Machine Learning Engineer.
- The program explicitly combines technical expertise with project leadership, which positions you for AI project management and team leadership tracks in Germany’s tech and transformation teams.
- Your Master of Science degree supports progression into senior specialist and leadership roles by strengthening both research methods and applied practice.
Employability rate
For graduates in data science and AI-related fields in Germany, an employability rate of around 86% and an unemployment rate of about 14% is a realistic estimate, reflecting continued hiring for analytics, machine learning, and digital transformation roles.
Overall, these figures indicate a stable outlook as long as you build practical portfolio skills through projects and electives during your studies.
✅ Entry Requirements
Academic qualification
| Requirement | Details |
|---|---|
| Bachelor's degree | International applicants need a completed first degree and the university states that admission to this Master requires a completed first degree and at least one year of relevant professional experience. |
| Higher secondary / A-Level | This is a Master’s programme, so entry is based on a completed first degree for international applicants, not school-leaving qualifications. |
Module matching by study area
| Study area | Match possible? | Conditions |
|---|---|---|
| Computer Science & IT | conditional | Admission information for this programme indicates a completed first degree plus at least one year of professional experience; the university also supports recognition of prior learning. Use your module handbook and grades for recognition requests when your background is not an exact match. |
Language requirements
For admission to this Euro-FH Master’s programme, international applicants need sufficient English skills at level B2 (CEFR). The university also provides self-tests to assess your English level before you apply.
💶 Fees & Funding
| Item | Amount | Notes |
|---|---|---|
| Tuition | EUR 0 / per year | The program page states you can study from 426 €/month, and that flexible start is possible; a fixed official tuition per year is not clearly published on the page content captured. |
| Semester fee | EUR 0 / per semester |
Proof of financial resources
Before and during your stay in Germany, you may need to prove that you can financially support yourself. The specific amount and proof format are typically defined by German immigration/visa requirements for international applicants.
- Financial proof requirements for Germany (amount and accepted document types) may be defined by the German immigration/visa process for international students
- Prepare your financial documents in the format requested by the German process you use
Important dates
Application window
| Milestone | October - Winter intake | April - Summer intake |
|---|---|---|
| Application portal opens | N/A | N/A |
| Application deadline (final submit) | N/A | N/A |
| Application deadline (EU students) | N/A | N/A |
| Application deadline (Non-EU students) | N/A | N/A |
| Recommended apply-by | N/A | N/A |
| Semester begins | October 01, 2026 | April 01, 2026 |
Pre-application & reviews
| Milestone | October - Winter intake | April - Summer intake |
|---|---|---|
| VPD request - recommended | N/A | N/A |
| VPD result expected | N/A | N/A |
| APS - recommended | N/A | N/A |
| Start eligibility check | N/A | N/A |
Document submission deadlines
| Milestone | October - Winter intake | April - Summer intake |
|---|---|---|
| Application submission deadline | N/A | N/A |
| Document submission deadline (EU students) | N/A | N/A |
| Document submission deadline (Non-EU students) | N/A | N/A |
| Language certificate deadline | N/A | N/A |
| Official transcripts deadline | N/A | N/A |
| Certified translations deadline | N/A | N/A |
| Postal / hard-copy documents deadline | N/A | N/A |
| Missing documents (if requested) | N/A | N/A |
🎓 Scholarship
| Provider | Scheme name | Coverage | Eligibility notes |
|---|---|---|---|
| DAAD | EPOS — Development-Related Postgraduate Courses | Tuition fees, monthly stipend, travel allowance, health insurance | DAAD EPOS funds development-related postgraduate courses in Germany for eligible participants from developing countries. As a Master’s program focused on data science and AI skills, this type of technical postgraduate training can be considered under EPOS if the course is selected in the DAAD scholarship database for the relevant call. |
📝 How to Apply
Prepare eligibility and documents
Check that you meet the Master’s admission requirements (completed first degree and at least one year of professional experience). Review the English requirement (B2 level as stated by the university) and use the provided self-test to estimate your level. Prepare your degree certificate and transcript documents so you can upload or submit them as requested during registration.
Register and submit your application online
Complete the university’s online application process for the Master programme during the admissions window. After booking/registration, you will receive a checklist showing which documents are needed for enrolment and approval. Upload or email the requested documents in the required format and keep copies for your records.
Complete the credential review for admission
The university reviews your application documents to confirm eligibility for the Master’s programme. If your documentation needs clarification, provide the requested information promptly so the review can be completed without delay. If you want recognition of prior study, the university indicates you should submit your module handbook and grade overview as part of the recognition request.
Enrolment and start of studies
After successful admission processing, follow the enrolment instructions provided with your personal checklist and admissions confirmation. Once you are enrolled, you will receive access to the online campus and the first study materials. Plan your study schedule around the programme’s flexible structure and assessment dates.