Computer Science

This full Master of Science in Computer Science is an advanced, English-language programme that builds both theoretical foundations and practical skills across the main areas of computing. Core topics include software engineering, information systems, databases, machine learning, communication and security, algorithms, and programming. The curriculum combines classroom teaching with application-oriented modules so you gain expertise relevant to research and industry alike.

Students must choose one of three specialised study tracks to focus their studies and take in-depth modules from a broad catalogue: visual computing, embedded systems, or complex and intelligent software systems. Visual computing covers image- and 3D-based disciplines such as computer vision, computer graphics, image processing, machine learning, visualization, and VR/AR, with applications in medical image processing, quality control, autonomous robotics, multimedia and games. The embedded systems track addresses domains like consumer electronics, industrial control and transportation (notably automotive electronics), emphasising hardware/software design, real-time and dependable systems, and the growing role of connected cyber-physical systems and embedded AI. The complex and intelligent software systems track focuses on modern software development and maintenance, machine learning integration, quality assurance, and also trains social and management skills needed for complex projects.

Interdisciplinary cooperation between computer science and electrical engineering is a hallmark of the programme, giving you access to research-driven teaching and hands-on topics such as sensor development, face detection, online range-data processing (e.g., Kinect-like sensors), and multimodal pattern recognition. Master's students are encouraged to join ongoing research projects at the university, and outstanding participants may have the opportunity to continue toward a PhD within these projects.

Key programme structure and choices

• You must select one study focus: visual computing, embedded systems, or complex and intelligent software systems.
• Within your chosen focus, you build in-depth competence by selecting modules from a wide-ranging catalogue.
• The programme includes development of non-technical skills (presentation, teamwork, management and leadership).
• For the embedded systems focus, courses cover hardware/software co-design, computer architectures, real-time systems, dependability, security, operating systems, modelling and application domains (e.g., automotive, industrial control).
• Research participation is actively supported; excellent Master’s students may be invited to pursue a PhD in related projects.

Curriculum overview

This Master's curriculum combines broad core subjects, hands‑on practical work, specialised electives and research projects to develop both theoretical understanding and professional skills in computer science. Core modules cover central topics across theory, systems and applications, while practical modules focus on software and hardware development, project-based teamwork and industry‑relevant workflows. Research‑oriented components (seminars, cutting‑edge research and project work) prepare you for scientific methods and independent investigation, culminating in a substantial Master’s thesis.

Programme structure and key modules

• Core modules (choose 4 of 6; 6 CP each): Embedded Systems; Computer Architecture; Modelling and Animation; Parallel Processing; Algorithms; Advanced Logic. These provide a broad foundation in theoretical, practical and technical aspects of computer science.
• Practical and research‑oriented modules: Cutting Edge Research (6 CP), Scientific Working including a seminar (9 CP), and project work (15 CP). These modules train research skills, scientific communication and collaborative project delivery.
• Specialised modules: six elective modules (6 CP each) from a comprehensive catalogue that deepen scientific expertise and typically form the basis for student projects and the Master’s thesis.
• Master’s thesis: 30 CP, integrating knowledge from core and specialised modules into an independent research or development project.

Specialisation highlights and learning outcomes

• Embedded Systems focus: options include networked embedded systems, microelectronics, semiconductor technology, AI, ubiquitous systems and real‑time systems. Coursework can cover communication engineering and telematics, FPGA and Systems‑on‑a‑Chip development, small sensor‑equipped ubiquitous devices, and applied AI/deep learning. Graduates gain skills to design, implement and evaluate embedded solutions across hardware and software stacks.
• Visual Computing focus: modules span computer vision (e.g., machine vision, convex optimization), computer graphics (e.g., rendering, GPU programming, scientific visualization, virtual reality) and machine learning (e.g., statistical learning theory, deep learning, recent advances). Learning outcomes include the ability to analyse image/video data, generate and simulate visual content, and apply ML methods to visual problems.
• Complex and Intelligent Software Systems focus: specialisation modules deepen competencies in building large, complex software systems and integrating machine learning to create intelligent behaviour, while linking these applied skills to relevant theoretical foundations.

Requirements (concise)

• Complete 4 of 6 core modules (6 CP each)
• Complete Cutting Edge Research (6 CP)
• Complete Scientific Working including seminar (9 CP)
• Complete project work (15 CP)
• Complete six specialised modules (6 CP each)
• Submit Master’s thesis (30 CP)

Notes for international students: the curriculum balances classroom theory, lab work and team projects to prepare you for research roles or technical positions in industry; specialised choices let you tailor the degree toward hardware‑centric, visual/computational or software/AI career paths.

Graduates are prepared for technical and research roles across a wide spectrum of industries. Typical positions include software engineer, embedded systems developer, computer vision or graphics specialist, machine learning engineer, and roles in autonomous systems, automotive electronics, industrial control, multimedia and gaming industries. The programme’s practical modules and project work equip students for engineering roles that require both software and hardware competence.

For students interested in research, the strong ties between computer science and electrical engineering at Siegen, plus involvement in ongoing research projects, create pathways to doctoral study. The combination of specialised technical knowledge and non-technical skills (project management, teamwork, scientific working) also supports careers in technical management, R&D teams, and product development.