Description of the field of study:
The course provides students with the knowledge and skills necessary to develop and use computer systems in the broadest sense. Covers both theoretical foundations in mathematics, physics, and computer science, as well as practical aspects, including the design and implementation of PC and mobile systems, software development (use of development tools and programming in various languages), systems administration, and data analysis.
The graduate of the field of study has knowledge in the following areas:
computer science and information systems, in particular, the design and implementation of computer and mobile systems, software development (programming in various languages), algorithms and data structures, databases and computer graphics, mathematical foundations of computer modeling and design, as well as basic issues of electrical engineering, electronics, and computerization of measurements, protection of intellectual property and patent law, as well as the principles of creation and development of forms of individual entrepreneurship and teamwork.
The graduate of the field of study can:
Algorithmize an engineering problem, use appropriate IT methods and tools, program in various types of language, design and execute an IT system, diagnose an IT system, consider nontechnical aspects and security principles when formulating requirements and designing IT solutions.
Career prospects:
Graduates of the course can undertake work as IT specialists in the design and implementation of software in various technologies, including database and Internet technologies. In addition, he or she is skilled in the appropriate security of such computer systems and their administration. In particular, he can perform roles in teams that require advanced knowledge of computer science (creation and analysis of algorithms and programs, implementation, mapping of algorithms to computer hardware, including high-performance parallel hardware) and mathematics (creation and analysis of mathematical and numerical models, estimation of computational errors, risk assessment, and statistical and stochastic properties of problems and solutions).