Information has become a central economic resource in the global, networked world. This English-taught MSc programme at Rhine‑Waal’s Kamp‑Lintfort campus trains you to manage information throughout its lifecycle — from acquisition and validation to efficient delivery, presentation and security. You will learn to design and implement IT solutions that ensure data are available in the right format, at the right time and place, to the right users, while meeting high standards for reliability and confidentiality.
The curriculum gives you in-depth exposure to data acquisition, processing and handling, and to distributed and networked computing infrastructures. It also prepares you to work with large-scale data sets and to apply modern methods from artificial intelligence and systems engineering. To tailor the degree to your interests and career goals, the programme offers several specialization tracks, including Computer Science, Environmental Engineering, Logistics, Cyber‑Physical Systems Engineering and Artificial Intelligence.
Graduates are prepared for internationally oriented roles in industry and research where information and data management, AI, cloud and web-scale services, simulation and decision support, automation, logistics control, and embedded systems are central. The course emphasises innovative, interdisciplinary problem solving to boost your employability in sectors such as IT services, automotive, medical technology, logistics providers, research institutes and companies running large-scale computing facilities.
Requirements (check the university’s admissions page for exact details)
This is an intensive, three‑semester follow‑up Master's programme designed to build directly on the technical foundation you gained during your undergraduate studies. The first two semesters focus on delivering both theoretical knowledge and hands‑on practice through lectures, advanced seminars and exercises, while the third semester is reserved for an independently researched Master's thesis and its accompanying colloquium. Practical training is woven into every module so that learning is regularly applied, not just theoretical.
During the initial two semesters you will deepen core competencies across a range of technical areas and benefit from structured opportunities to specialise. Core subject areas include System Simulation, Data Mining, Data Analysis and Information Engineering, Statistics and Geoinformatics. You will also develop transferable skills such as scientific and technical communication, intercultural management and competence, and innovation management. Each semester culminates in an applied research project that lets you tackle larger, practice‑oriented problems and build a portfolio of concrete outcomes.
The final semester centres on preparing and writing your Master’s thesis and presenting it in a colloquium. Topics are expected to meet high academic standards while remaining closely connected to real‑world applications, reinforcing the programme’s emphasis on research quality and professional relevance.
Key modules
Learning outcomes / competencies
Programme requirements (concise)
This master’s programme requires a formal application and a completed undergraduate degree with a sound technical background. Successful applicants normally hold a BSc, BA, German “Diplom” or an equivalent qualification with coursework in practical computer science and computer engineering, plus foundational subjects in mathematics, natural sciences and engineering. In exceptional cases, missing specific courses may be offset by other related academic training or professional experience — see the bullet about the supplementary essay below.
Academic performance and standardised test scores are part of the selection criteria, and applicants must also demonstrate sufficient English language ability. If your home grading system differs from the one used here, include documentation or an explanation so your final mark can be assessed. For full details on the application process and supporting documents, consult the programme web page linked at the end.
Requirements (bullet points)
For more information and application details, visit: https://www.hochschule-rhein-waal.de/en/academics/prospective-students/current-application-period/masters-programmes
Winter Semester (International)
15 July 2026
Summer Semester (International)
15 January 2027
Winter Semester (EU/EEA)
15 July 2026
Summer Semester (EU/EEA)
15 January 2027
Graduates are prepared for technical and research roles in areas such as information and data management, artificial intelligence, cloud and web-based storage and computing operations, simulation of complex systems, and development of decision support systems. The programme also trains students for hardware and software development roles in automation, logistics control and embedded systems used in industries such as automotive and medical technology.
With its interdisciplinary and international orientation, the degree strengthens employability for positions in international companies, research institutes and technology-driven organisations that require both practical engineering skills and the ability to manage and analyse large-scale information systems.
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