In Project Seminar, students analyse a real-world case from a specific industry. Students divide into groups according to their preferences and work on one of four cases through the lens of process management, data and application security, data science, or digital innovation. The course topics change from semester to semester.

Projects typically aim to turn data into value and leverage technological advancements. They might focus on business aspects, such as identifying use-cases for novel AI models. Projects often include hands-on work on the data side, such as data mining and collection, as well as on the model side, such as leveraging and adjusting AI models, including foundation models. Projects are expected to deliver conceptual designs or conduct practical case studies on various aspects of data science and artificial intelligence.

• The course involves interactive seminars with workshops and regular presentations.
• The faculty and a jury of representatives from regional companies evaluate the students’ solutions in terms of innovativeness and usefulness and provide them with feedback and advice.

After successful completion of the course, students will

Professional competence

• be able to analyse real-world cases
• integrate knowledge to identify areas of improvement or innovation
• use appropriate methods to develop recommendations for a case company

Methodological competence

• manage a (small) project
• identify and structure existing information
• work with domain experts (external partners)

Social competence

• self-organise within a group
• work in a group and with external partners
• handling criticism and demonstrate the ability to criticise in a constructive manner

Personal competence

• reflect on limitations of their own work
• work on tasks independently within a group
• manage time

Seminar paper (50%), presentations (50%); attendance is mandatory (80%)