28.01.2027 – 05.02.2027
6,5 days
English
EUREF-Campus 9 (access through Torgauer Straße),
10829 Berlin
Certificate of Professional Education of TU Berlin & EIT Urban Mobility
(6 ECTS)
on-site
LECTURERS
1.300,00 €
AI IN MOBILITY
AI is reshaping how mobility systems are planned, operated, and governed. This course equips participants with the knowledge and strategic tools to evaluate, implement, and govern AI applications in the mobility sector. Combining technical foundations with practical exercises and industry perspectives, the module bridges the gap between AI concepts and management decisions.
Learning goals
After completing this module, participants will be able to:- Understand the fundamentals of artificial intelligence, machine learning, generative AI, and Large Language Models (LLMs)
- Identify high-impact AI applications across the mobility sector and evaluate their potential to create business, operational, and societal value
- Apply LLMs and prompt engineering techniques to enhance analysis, problem-solving, and managerial decision-making
- Assess AI-enabled business models and implementation strategies for mobility organizations
- Make informed and responsible decisions about AI adoption, considering sustainability, governance, and ethical implications"
Content
- Foundations: AI as mobility infrastructure, machine learning, generative AI, Large Language Models (LLMs), and data readiness
- Business & Strategy: AI applications in mobility (e.g. forecasting, optimization, autonomy), AI-enabled business models, implementation strategies, and build vs. buy vs. partner decisions
- Responsible AI: Sustainable mobility, governance, ethics, and the EU AI Act
- Practical Learning: Hands-on exercises, applied projects, industry case studies, and guest lectures
Target group
This course is designed for professionals interested in the strategic application of AI in mobility.It is particularly suited for current and future managers, consultants, entrepreneurs, and public-sector professionals who work with or commission AI-driven solutions. No technical background is required.
Prerequisites
No programming or data science experience is required.Participants should have an interest in mobility, digital innovation, and emerging technologies.
Dates
- 28 January 2027 (15:00–18:30) – Introduction
- 29 January 2027 (09:00-17:00) – Guest Lectures from Industry
- 1–5 February 2027 (10:00–18:00) – Intensive Module (lectures, hands-on exercises, case studies, and guest lectures)
Cooperation
This course is organised by TUB/CO and supported by EIT Urban Mobility, an initiative of the European Institute of Innovation and Technology (EIT), a body of the European Union.If you apply for this course, your personal data will be processed in accordance with the applicable privacy policies: https://www.eiturbanmobility.eu/privacy-policy/ TUB/CO Privacy Policy: https://apply.tubadvancedmasters.de/en_US/contents/content/9-data-protection
LECTURERS
Prof. Dr. Hamid Mostofi specializes in artificial intelligence, machine learning, and data-driven methods, with a particular focus on their application in mobility and urban systems. His teaching combines technical foundations with practical applications to equip future managers and practitioners with the knowledge required to evaluate and strategically implement AI solutions in real-world contexts.
Industry Guest Lecturers
The module features guest speakers from leading mobility companies, startups, public-sector organizations, and AI governance experts who share practical insights into the development, deployment, commercialization, and responsible use of AI in mobility."
