Master's track Systems and AI
Source: https://www.tue.nl/en/education/graduate-school/masters-track-systems-and-ai Parent: https://www.tue.nl/en/education/degree-programs/master-programs
A track of the MSc Computer Science and Engineering
Master's track Systems and AI
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ECTS points
120
Education type
Master program
Duration
Two years
Language
English
Systems and Ai: Dual degree with taltech
The Systems and AI track focuses on the design and analysis of advanced computer systems that integrate machine learning with distributed, real-time, and cyber-physical systems. Students explore how data-driven methods interact with networked and time-critical software, emphasizing correctness, reliability, and security.\ \ The program bridges theory and practice, training students to model, analyze, and evaluate intelligent software systems under real-world constraints such as timing, safety, and security. Graduates gain skills to design dependable systems that combine formal and automated reasoning with practical implementation, with exposure to industrial standards for safety-critical systems.\ \ Topics include machine learning, distributed/cloud/edge systems, real-time software engineering, cyber-physical systems, software security, robotics, and standards-aligned development frameworks such as DO-178C, ECSS, and ISO 26262.
HIGHLIGHTS OF OUR PROGRAM
- International double degree experience\ The Systems and AI track combines TU/e's deep, research-oriented and mathematically solid approach with TalTech's practical, industry-focused training. Students gain both theoretical foundations and practical experience in high-tech system design and evaluation.
- Balance theory and practice\ Offers a strong balance between theory and practice, with in depth training in distributed and real time systems, cyber physical systems, machine learning, automated reasoning, software security, cloud architectures and robotics.
- Preparing for real world impact\ Trains students to design trustworthy, explainable and safe AI systems for complex societal and industrial challenges in high tech domains such as automotive, space and data driven industries.
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