The goal of this program is to train Computer Scientist with a professional knowledge-based on solid theoretical background knowledge. They have the skills to take part in program development, in developing information systems and system management in various areas. The Computer Scientist often acts as a mediator between the customers of information systems and the producers. In this way, the job of a Computer Scientist synthesizes the constructive activity of engineers with the general problem-solving attitude of mathematicians while participating in teams of large-scale projects.
Our programs provide students with a broad education in Computer Science in combination with specialized work in programming languages, cybersecurity, data science, web engineering, autonomous systems, multimedia design, etc.
Students learn the theory as well as the methodologies and techniques in the development and implementation of computer systems. The more practical programming courses are aided by several courses in pure and applied mathematics and theoretical computer science courses throughout the curriculum.
This program is recommended to applicants who:
- want to partake in innovative and well-grounded education for the next generation of service designers and software architects capable of designing and engineering novel software system.
- want to conduct analyses to detect, discover and better understand the abounding data around us generated by social media, manufacturing systems, medical devices, logistic services, and countless others on a daily basis.
- want to be a responsible cybersecurity specialist with the right knowledge and skills to be able to contribute to make the digital world a safer place.
This program enables students to:
- work in teams to guide the software development process (modern and agile software engineering methodologies integrated with design thinking and User-Centric/Service Design methods) of complex information systems.
- gain in-depth technical skills in scalable data collection techniques and data analysis methods. They learn how to use and develop a suite of tools and technologies that address data capture, processing, storage, transfer, analysis, visualization, and related concepts (e.g., data access, data pricing, and data privacy).
- be valuable in open innovation settings where different aspects (market, users, social aspects, media technologies) come together, through their multidisciplinary attitude.