Admission requirements

You need the General University Entrance Qualification (Abitur), the subject-related university entrance qualification (Fachhochschulreife), or an equivalent recognized education. Alternatively, a completed apprenticeship with three years of professional experience or a completed advanced training course can also serve as a requirement.

In addition, you must currently be employed or completing a company training programme, a trainee programme, or a voluntary editorial programme. If you are not currently employed but aspire to be, you can contact the student advisory service to discuss your individual admission options.

Details

The Bachelor's programme in Applied Artificial Intelligence (B.Sc.) at FOM University provides comprehensive training in the rapidly advancing field of Artificial Intelligence. The target audience for this programme is professionals interested in the transformation of the working world through artificial intelligence and looking to specialize in this field.

The programme stands out with a flexible Digital Live Study format, enabling location-independent learning and promoting the compatibility of work and study. Classes include both practical project modules and theoretical lectures led by experienced lecturers. The live lectures are also available to students recorded in a media library.

The course is designed to be completed in seven semesters and can be pursued alongside employment. In addition to subject-specific content, students acquire valuable soft skills essential for leadership positions in the digitized working world. The focus is on machine learning, working with neural networks and big data.

Students have the opportunity to specialize in key areas such as Innovation & Change Management or Digital Leadership. Through projects during the course, students learn, for example, how to train and test an AI model in practice.

1st Semester: Mathematical Foundations of Computer Science, Programming Concepts, AI Basics, AI Tools, Time and Self-Management.

2nd Semester: Quantitative Methods of Computer Science, Databases, Machine Learning, Practical Data Management, Scientific Work.

3rd Semester: Algorithms and Data Structures, Concepts of Dynamic Programming Languages, Deep Learning & Cognitive Systems, Advanced Machine Learning, Project Management.

4th Semester: Software Engineering, IT Infrastructure, Governance, Operationalization & Explainability of AI, Project: AI enabled Process Management, Digital Transformation.

5th Semester: Big Data & Data Science, Operating Systems, AI enabled Business Models, Project: Research Methods, ESG - Sustainability.

6th Semester: Technology Trends & Innovation Management, Information Security & Data Protection, Applications of AI, Project: AI Applications in Practice, Exposé.

7th Semester: Thesis/Colloquium.

Graduates are qualified for positions involving the implementation of AI solutions, data analysis, and innovation management. Upon completion of the programme, a wide range of professional opportunities awaits you, thanks to a nationally and internationally recognised Bachelor's degree.