This summer course explores the impact of Artificial Intelligence (AI) in society, combining theoretical knowledge with hands-on development of AI prototypes. In 2026, the course focuses on AI for urban mobility, public infrastructure, and fairness in digital public services. Together with Berliner Verkehrsbetriebe (BVG), students will work on real-world use cases related to public transport, accessibility, data-driven services, and the responsible use of AI in urban mobility.

Date: 28.09.26 – 02.10.26
Location: HTW Berlin, Germany & Online
Credits: 3 ECTS
Target Audience: Master students in Computer Science, Business Administration, Business Informatics, and related fields

Students will work in groups to create a prototype demonstrating AI use in a use case provided by our partner. 

The practice partner for the 2026 edition is Berliner Verkehrsbetriebe (BVG), Berlin’s public transport operator. BVG provides mobility services across U-Bahn, tram, bus and ferry networks and is a central actor in Berlin’s urban infrastructure. Its digital services include journey planning, service information, ticketing and multimodal mobility services such as Jelbi. The collaboration gives students the opportunity to work on AI use cases situated in a real public-service context, where technical innovation, usability, inclusion, data protection and fairness must be considered together. 

The use case is the AI-supported extraction of information from historical transport-related construction plans and infrastructure documents. Students may explore OCR, layout analysis and computer vision techniques to identify text, symbols, metadata and relevant structural information. The focus is not on building a production-ready system, but on designing, testing and critically evaluating a transparent AI workflow.

• Hands-on AI Prototypes – Develop AI applications for use cases.
• Expert Lectures & Workshops – Learn from researchers and industry professionals.
• Ethics & Fairness in AI – Explore AI bias, transparency, and responsible AI.

After completing the course, students will be able to:
– explain opportunities and risks of AI in public-service and mobility contexts
– design a small AI prototype for a real-world use case
– evaluate AI outputs using appropriate technical and socio-technical criteria
– identify fairness, accessibility, transparency and data-protection issues in AI-supported services
– communicate technical results to academic and practice partners
– collaborate in international and interdisciplinary teams

Assessment combines group work and individual academic reflection. Students prepare selected scientific readings before the intensive week and complete an individual on-site short essay without AI assistance. During the intensive week, teams develop a prototype and present their results.