MSc in Human-Centred Intelligent Systems (HCIS)

The programme will educate participants to successfully master the novel technical and economic challenges at the crossroads of computer science, software engineering, next-generation communication systems, and intelligent systems. It consists of three main blocks: Artificial Intelligence and Machine Learning Human-Centred and Interactive Technologies Use and Societal Impact Two mandatory courses introduce the students to the first two blocks: "Introduction to Learning Systems and Data Science" and "Designing Interactive Systems". In the third block, courses such as “AI Ethics” will be offered. An optional fourth block is available for students who wish to deepen their interest in general computer science. The programme is particularly special in offering a significant proportion of research lab courses embedded in both basic and applied research of the participating Fraunhofer Institutes of Applied Information Technology (FIT) and Intelligent Analysis and Information Systems (IAIS). A further lab can be conducted at the university, at Fraunhofer Institutes, or in cooperation with industry. Major topics covered by courses offered include: Data Science Advanced Methods of Text Mining Pattern Matching and Machine Learning Computer Graphics/Animation/Visualisation Speech/Image/Video Processing and Technology Virtual and Augmented Reality Designing Interactive Systems Management of Information and Knowledge Explainable AI and Applications Business Process Intelligence and eBusiness Cooperative Work Environments The course of study also includes methodological aspects of designing intelligent interactive systems from the perspectives of software engineering, usability, interaction design, and business requirements. The standard duration of the programme is four semesters (two years). Students typically complete 30 ECTS credits per semester through a combination of lectures across various fields, seminars, and lab courses. The fourth semester is dedicated to the Master’s thesis, which may also be carried out in collaboration with industry partners. All courses are organised into flexible modules and are fully aligned with the ECTS system. PDF Download

Course details verified 09 Sep 2026 — intakes, entry requirements and course facts · official source

1. Winter semester

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English

E.G. IELTS Academic: 5.5

Prerequisites

A candidate should hold a recognised first degree (Bachelor of Science or Engineering) in Computer Science, Computer Engineering, Informatics, or a closely related discipline from an internationally recognised university. Applicants with a different degree must still demonstrate a strong background in computer science, mathematics, and engineering; otherwise, a bridging course may be required, or the application will be deemed ineligible. The GRE General Test is required for non-EU/EEA applicants and must be submitted with the application; otherwise, the application will be rejected. For English-taught programmes at RWTH Aachen University, candidates must demonstrate proficiency in spoken and written English (see details below). Candidates should have performed above average in their undergraduate studies and possess a solid background in computer science and mathematics. The candidate must provide credits in the following areas: Applied Computer Science (at least 28 CP), including: min. 8 CP in programming min. 8 CP in data structures and algorithms min. 6 CP in databases and information systems min. 6 CP in elements of machine learning and data science min. 6 CP in software technology Computer Engineering (at least 18 CP), including: min. 6 CP in computer & electrical engineering min. 6 CP in operating systems and system software min. 4 CP in IT security min. 6 CP in data communication and security Theoretical Computer Science (at least 18 CP), including: min. 6 CP in formal systems, automata, and processes min. 6 CP in computability and complexity min. 6 CP in mathematical logic Mathematics (at least 26 CP), including: min. 6 CP in discrete structures min. 8 CP in mathematical analysis min. 6 CP in linear algebra min. 6 CP in applied stochastics Credits are based on the European Credit Transfer and Accumulation System (ECTS). If substantial background knowledge is missing, a bridging course may be assigned. If more than 22 CP are missing, admission will not be granted.

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