About the Department
«Computer science and intellectual property» Department
of «Computer Science and Software Engineering» Faculty of National Technical University «Kharkov Polytechnic Institute»
provides trainings in the following specialties:
- «Computer sciences» (“Bachelor’s degree“, 4 years long, 240 credits);
- «Data and Knowledge Engineering» (“Master’s degreе“, 1.4 years long, 90 credits);
- «Intellectual property in Hardware and Software Engineering» (“Master’s degree“, 1.4 years long, 90 credits)
- «Artificial intelligence and machine learning» (“Master’s degree“, 1.4 years long, 90 credits)
Students of the department develop the knowledge and skills necessary for data and knowledge programmers and engineers, developers of cloud services software, for intellectual processing of large volume consolidated data, based on of modern software and information technologies
Java, C++, PHP, XML, IBM DB2, Eclipse, MS SQL Server, MySQL, Oracle, Mantis, Wiki, MS Project, IBM Rational Software, Platinum BP/ER Win, Sybase Power Designer, MS Visio, J2EE = Java Enterprise Edition, LAMP = Linux/Windows + Apache + PHP + MySQL.
After the bachelor’s program completion in Computer Science, students of the department continue education through one of the following master’s programs:
Data and Knowledge Engineering:
Data and knowledge engineering software; Modern mathematical and computer modeling methods; Service-oriented architecture; Web technologies and cloud services; Machine learning; Distributed databases; Semantic Web; Visualization of data; Cybersecurity; Artificial Intelligence and Cognitive Technologies; Knowledge-oriented systems design.
Intellectual Property in Hardware and Software Engineering:
Industrial property rights in HW and SW engineering; Copyright and related rights to software and digital content; Disposal of rights; Intellectual property and confidential information protection; Patent and marketing research of digital markets; Rights commercialization on information technology objects; Start-up management and investment.
Artificial intelligence and machine learning:
Mathematical foundations of artificial intelligence; Fundamentals of the theory of formal systems; Methods and means of machine learning; The theory of decision making and cognitive calculus; Technologies and means of artificial intelligence; Artificial neural networks; Pattern recognition