This English-taught Master’s program prepares you to design and deliver innovative IoT products and smart systems that create digital value for businesses. You will learn both the technical foundations and the business thinking needed to develop applications and devices that drive new services and business models, while also focusing on usability and customer needs. The programme emphasises creativity and practical problem solving: students are encouraged to move beyond the obvious and invent the future of connected systems.
The curriculum gives hands-on experience across the full IoT stack and related disciplines. You will work with topics such as Internet of Things architectures, software for edge and distributed systems, artificial intelligence, mobile applications, large-scale data processing and analytics, human–computer interaction, information systems, project management, and digital business models. Project-based and interdisciplinary learning is central, so you’ll gain practical experience working on real-world projects and products alongside fellow students.
This master’s curriculum is organised across four semesters and balances theory with hands‑on practice through lectures, seminars and lab classes. Seminars and labs are deliberately small (typically 10–20 students) to foster close supervision and active skills development. German language courses are integrated into the programme during the early semesters (German Language Course 1 and 2) with an option in the third semester to continue German (German Language Course 3) or to take an additional elective.
Core technical foundations are introduced in the first two semesters: Project Management, Human‑Computer Interaction and its Application to IoT, IoT Architecture and Visualisation, Responsible Computing: Ethics, Society, and Security, and Compensation Programming. The second semester adds a central IoT Project alongside Artificial Intelligence and Large Scale Data Processing. You also begin to shape your focus via specialisation tracks (for example, Computer Science: Mobile Applications or Business and Marketing: Analytics for Data‑Driven Decisions) and modules that build communication and global business skills (Global Business and Project Communication in English).
In the third semester students complete an Interdisciplinary Project and an IoT Development module while continuing specialisation options such as Computer Science: Introduction Autonomous Driving or Business and Marketing: Digital Business Models, plus Advanced Topics and elective choices. The programme culminates in a fourth‑semester Master’s project, which may be carried out at the university or in collaboration with a company—providing a direct pathway to industry application and employment. Overall learning outcomes include designing and visualising IoT systems, developing embedded and distributed IoT solutions, applying AI and large‑scale data techniques, understanding ethical and security implications, managing multidisciplinary projects, and translating technical work into business and communication contexts.
Program requirements (study and completion highlights)
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Winter Semester (International)
https://www.whz.de/english/study/incomings/application/international-full-time-study/
Graduates are prepared for technical and product roles in the IoT ecosystem, such as IoT developer, embedded/edge systems engineer, software architect for distributed systems, data engineer or applied AI developer. The curriculum’s mix of software architecture, AI, large-scale data processing, human-computer interaction and project management equips students to design, implement and industrialise IoT solutions across sectors (manufacturing, mobility, smart buildings, healthcare, etc.).
The programme’s project-based learning, opportunity for a company-based master's project and optional internships improve readiness for industry roles, startups and R&D positions. The inclusion of digital business models and analytics also supports transitions into product management, technical consulting or business-facing roles within digital transformation teams.
Hochschule für Technik Stuttgart - University of Applied Sciences — Stuttgart
University of Regensburg — Regensburg
University of Bonn — Bonn
Brandenburg University of Technology Cottbus-Senftenberg — Cottbus