Master of AI and Data Science at Frankfurt School of Finance & Management: Program Structure, Outcomes, and Admissions
- MastersDegreeXperts
- Feb 10
- 3 min read
Key Takeaways
The Master of AI and Data Science is designed for graduates with strong quantitative backgrounds seeking careers in Europe.
The 21-month program combines applied machine learning, AI, and data science with a focus on real-world business problems.
Frankfurt School is described as ranked number one in Germany for employability by Times Higher Education.
The program uses a three-day-per-week class model to allow time for part-time work, internships, or entrepreneurial projects.
Graduates report strong career outcomes, including average starting salaries above €80,000 and placement across multiple industries.
The admissions process includes academic requirements, standardized tests, an interview, multiple deadlines, and access to scholarships.
Institutional Context and Employability
Frankfurt School of Finance & Management is presented as a leading European institution with a strong focus on employability. According to the transcript, Times Higher Education ranks the school number one in Germany for employability. This positioning is attributed to a combination of technical training, business-oriented education, and close connections to industry.
The school is described as triple-crown accredited and focused on practical, project-based learning. Faculty members are characterized not only as academics but also as entrepreneurs and founders, contributing applied perspectives to teaching.
Program Purpose and Ideal Candidate Profile for the Master of AI and Data Science
The Master of AI and Data Science is structured for students who already possess a solid foundation in quantitative disciplines. The program targets individuals aiming to become leaders in data science and AI-driven roles, particularly within the European job market.
The degree spans 21 months and integrates applied machine learning, artificial intelligence, and data science. Its stated objective is to train students to transform raw data into actionable business insights and to address real-world organizational challenges.
Learning Model and Academic Structure
The program emphasizes applied learning rather than purely theoretical instruction. Coursework is designed to connect technical concepts directly to business use cases, ensuring that analytical methods are immediately relevant to professional environments.
A defining feature of the program is the three-day class model. Students attend classes on three days per week while remaining enrolled full-time. This structure is intended to enable participation in part-time employment, internships, or startup activities alongside academic study.
Student Experience and International Cohort
The student body is described as highly international, with a majority of students in the Class of 2026 coming from outside Germany. This diversity is presented as contributing to a global learning environment and the development of international professional networks from the beginning of the program.
Students are encouraged to apply classroom concepts directly to professional settings during the program. The structure allows for immediate application of newly learned material in work environments, reinforcing practical skill development.
Company Cooperation Project: Industry Integration in the Master of AI and Data Science
In the third semester, students participate in a company cooperation project. This component involves working with partner companies on real business challenges. Students manage projects from initiation through completion, applying technical and analytical skills in collaboration with industry stakeholders.
Career Outcomes and Industry Placement
Graduate outcomes are highlighted as a central strength of the program. The transcript reports an average starting salary exceeding €80,000, including bonuses. Graduates are employed across a range of industries, including energy, banking, technology, consulting, and asset management.
Common roles mentioned include data science, analytics, and finance-related positions. The diversity of outcomes is presented as evidence of the versatility and demand for the skills developed during the program.
Career Services and Professional Support
Frankfurt School provides structured career support throughout the program. Services described include one-on-one career counseling, skills workshops, dedicated career fairs with major employers, and access to an alumni network. This support is intended to assist students in securing roles in Germany or internationally.
Admissions Requirements and Application Process
Applicants are expected to hold a bachelor’s degree and demonstrate strong quantitative skills, with STEM backgrounds identified as particularly relevant. Additional requirements include proof of English proficiency and a standardized test score such as the GMAT or GRE.
The admissions process consists of an online application, followed by an assessment and an interview. Admission decisions may also include scholarship offers. Enrollment is confirmed upon acceptance of the offer and payment of a deposit.
Application Deadlines, Tuition, and Scholarships
The final application deadline is stated as June 30. Earlier application deadlines provide financial incentives. Applicants who apply before November 30 are eligible for a €4,000 tuition discount, while those applying before March 31 may receive a €2,000 discount.
Total tuition is listed as €35,500. The school also offers a range of scholarships, including awards for international students with STEM backgrounds and scholarships aimed at promoting diversity within the program.
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