Computer Science International (CSI)

Overview

This research-focused Master's programme, taught in English, prepares graduates for careers in industry, academia, and public service by combining strong theoretical foundations with practical engineering methods. Students learn to assess, model and systematically solve complex problems in computer science, work independently on specialised topics, and contribute to the advancement of their field through research and engineering practice.

Core topics

• Information Systems: concentrates on designing software, algorithms and data structures for information systems, techniques for analysing large datasets, and related areas. Subjects include database management and retrieval, big data and data mining approaches that integrate complex models with large datasets, issues of process traceability and privacy protection, software engineering topics such as requirements engineering and human–computer interaction, basic machine learning/artificial intelligence, interactive visual analysis, and the development and use of simulation models.

• Complex Systems: focuses on architectures, models, methods, algorithms and tools needed to design, implement and operate large-scale, heterogeneous IT systems. Emphasis is placed on modelling, simulation and systems analysis to design, evaluate and verify such systems and to determine core properties (e.g., correctness). The topic also covers methods for ensuring performance, safety and reliability— including self-organisation, fault tolerance, safety, cryptography, distributed algorithms, middleware and World Wide Web technologies.

Programme structure and learning experience

Students select one core topic as their major and the other as their minor, allowing them to tailor the degree toward either data- and software-oriented work or the engineering of large, distributed systems. The curriculum includes a topical seminar that concludes the major theme and a project component that gives hands-on experience in applying methods learned during coursework. The balance of research orientation and practical modules equips graduates to tackle complex technical challenges and pursue further research or professional roles.

Key requirements and credit breakdown

• Major topic: 30 ECTS
• Minor topic: 12 ECTS
• Additional modules: 12 ECTS from remaining modules of both core topics or other departmental modules
• Project: 12 ECTS
• Topical seminar: concludes the major topic (part of the programme modules)
• Computer science courses (excluding thesis): 78 ECTS
• Non-technical option: 12 ECTS
• Master's thesis: 30 ECTS
• Total programme credits: 120 ECTS

The programme runs over four semesters and is structured to give both breadth and depth:

• Major/minor structure: students select one core topic as a major (30 ECTS) and the other as a minor (12 ECTS).
• Electives: an additional 12 ECTS may be chosen from remaining modules in the two core topics or other departmental offerings, enabling customisation of the degree.
• Practical and research components: a topical seminar concludes the major topic and a project module is included (12 ECTS) to apply methods in practice or research settings.
• Final thesis: the Master's thesis accounts for 30 ECTS. Overall computer science coursework totals 78 ECTS (excluding the thesis) plus a 12 ECTS non-technical option.

Key learning outcomes include advanced competence in algorithm and software design, large-scale data analysis and machine learning basics (Information Systems track); modelling, simulation, verification and reliability methods for distributed and heterogeneous systems (Complex Systems track); and the ability to critically evaluate, verify and ensure performance, safety and privacy in complex IT systems. Graduates will be able to plan and carry out substantial research or engineering projects independently and to communicate results to specialist audiences.

Graduates are prepared for diverse careers in industry (e.g. software development, data science, systems architecture), public service and research institutions. The combination of theoretical foundations and engineering methods equips alumni to design, analyse and verify complex IT systems, work on large-scale data problems, and ensure system reliability, safety and privacy.

The programme also provides a solid basis for doctoral studies and academic research thanks to its research-oriented profile and emphasis on independent project work and thesis research.