Bachelor in Artificial Intelligence & Data Engineering

Graduates will have a well-founded understanding of the mathematical, statistical, computational, artificial intelligence, data engineering, and business foundations underpinning AI-enabled and data-driven computational systems across diverse application domains.

- Learning Objective 1.1: Students will demonstrate a well-founded understanding of the mathematical, statistical, and computer science foundations relevant to artificial intelligence, data engineering, and computational systems.
- Learning Objective 1.2: Students will demonstrate a well-founded understanding of artificial intelligence and data engineering methods, models, and system architectures.
- Learning Objective 1.3: Students will demonstrate a well-founded understanding of business functions,organisational processes, and decision contexts relevant to the development and use of AI enabled and data-driven systems.

Graduates will be able to apply data engineering, artificial intelligence, machine learning, and software engineering methods to develop, deploy, integrate, and maintain AI-enabled and data-driven systems that address complex real-world problems in business and related fields. They will be able to reason about the end-to-end lifecycle from development to deployment and ongoing operations.

- Learning Objective 2.1: Students will design and implement software components, data pipelines, and database solutions for structured and unstructured data, applying principles of reliability, maintainability, reproducibility, and scalability.

- Learning Objective 2.2: Students will develop, train, validate, and compare statistical, machine learning, and artificial intelligence models and justify methodological choices with reference to assumptions, performance, robustness, generalisation, and limitations.

- Learning Objective 2.3: Students will develop, deploy, and maintain AI-enabled and data-driven systems across the full lifecycle from data acquisition to ongoing operations.

- Learning Objective 2.4: Students will locate, interpret, and use scientific literature and technical documentation

Graduates will communicate technical, analytical, and business-related findings effectively and collaborate successfully in interdisciplinary and international teams.

- Learning Objective 3.1: Students will communicate technical concepts, analytical results, and business implications clearly and precisely in written and visual form, using appropriate terminology, evidence, and representations for specialist and non-specialist audiences.
- Learning Objective 3.2: Students will present and defend technical decisions, analytical findings, and business implications orally in academic and professional settings.
- Learning Objective 3.3: Students will collaborate effectively in teams by taking on appropriate roles and responsibilities, coordinating tasks, integrating contributions, and reflecting on stakeholder perspectives during problem formulation, system design, and implementation.

Graduates will act responsibly and professionally in academic and business environments. They will apply theoretical and methodological knowledge while considering ethical, legal, societal, economic, environmental, and cultural implications of AI, data engineering, and computational systems.

- Learning Objective 4.1: Students will evaluate artificial intelligence, data engineering, and business solutions considering ethical principles, legal frameworks, and regulatory requirements.
- Learning Objective 4.2: Students will critically assess societal, economic, and environmental implications of computational and artificial intelligence systems and justify responsible design and deployment decisions.
- Learning Objective 4.3: Students will recognise personal, cultural, and disciplinary differences in international working environments and adapt communication and collaboration practices accordingly.
- Learning Objective 4.4: Students will critically reflect on practical project experience by relating observed challenges, decisions, and outcomes to relevant theories, methods, and professional standards.

Once you have ensured that you meet the admission requirements for the Bachelor in Artificial Intelligence & Data Engineering and took a look at our application checklist, you can start your application via our online application form. 

You will need to upload the following supporting documents:

• A Recognised secondary school diploma* (Abitur, IB Diploma, US High School Diploma, A-Levels, European Baccalaureate, etc.) 
• An optional letter of motivation (maximum 500 words)
• A Curriculum Vitae (CV, résumé)
• A copy of your passport or ID card
• Additional documents, if applicable (e.g. references or letters of recommendation, certificates, awards, extracurricular activities)

*Please note that payment of the EUR 100 application fee is required before your application can be processed.

At Frankfurt School, there is no numerus clausus (NC). Successful applicants will be invited to an Online Assessment Centre (AC). 

We operate rolling admissions, allowing you to receive an admission decision before the application deadline.

If you do not meet the general admission requirements, you may still be eligible to apply under a recent change in German law. Please contact us for further information.

Note for neurodiverse applicants, applicants with disabilities, or chronic health conditions

To ensure that we can provide early advice and support (for example, when applying for additional time during the Assessment Center), please contact us or the Officer for Students with Disabilities and Chronic Illnesses as early as possible prior to your scheduled Assessment Centre. Further information can be found on our website under Life and Health Counseling.

You can select the AC date that suits you best as part of your application. 

The following dates are currently available: 

• 21 October 2026,
• 18 November 2026 
• 10 December 2026.

The online Assessment Center consists of four parts:

• Mathematics test
• Cognitive test
• English test
• Structured interview

For the assessment, you will need a non-programmable calculator, regardless of brand or model.

In addition to your test results, your motivation and commitment are key factors in the admission decision. All Assessment Centre sessions are conducted online. Please note that your application must be submitted at least two weeks before your preferred Assessment Centre date.

Frankfurt School offers a merit-based scholarship programme designed to ensure that talented students from diverse backgrounds can focus on their studies without financial concerns. The Diversity Scholarship Programme aims to promote diversity within the Bachelor of Science student body and provides tuition fee reductions of 15%, 25%, or 50%. Further information on scholarships and funding is available under “Financing & Scholarships.”

The application portal is open from 1 September 2026 to 30 June 2027. Late applications may be accepted in exceptional cases. We have rolling admissions, and you’ll usually receive a decision within two weeks of completing the online assessment test. We recommend applying early, as places are limited.

Programming and AI knowledge are helpful, but not required to successfully start the AIDE programme. Courses in programming and software engineering will help you develop these skills throughout your studies.

Yes. A strong analytical and mathematical foundation is important for successfully completing the Bachelor in Artificial Intelligence & Data Engineering. You should enjoy working with mathematics, logical thinking, and solving complex problems.

The programme offers numerous opportunities to apply your knowledge to real-world challenges. Throughout your studies, you will build your skills step by step – from technical and mathematical foundations to advanced AI applications.

Through internships and working student positions, you can gain additional practical experience and apply your knowledge in a business environment. Courses involving industry partners and a capstone project also give you the opportunity to work directly on relevant real-world business challenges.

Yes. Several modern student residences are located right next to campus, including i Live Campus Living and The Flag. Many other options are available nearby, ensuring short commutes. More information: Frankfurt School Housing