- knowledge and understanding of scientific tools for the study of linguistic phenomena, modern methods of developing linguistic support of information systems;
- the ability to formulate theoretical and practical solutions in modern computational linguistics, principles of cognitive modeling;
- in-depth knowledge of modern scientific methods of linguistic research within the limits of communicative and cognitive directions of linguistics.
- the ability to use knowledge and skills in conducting data collection, modeling of relevant resources and systems for processing natural texts;
- practical application of knowledge of the current state of affairs and the latest technologies in linguistics.

Computer recognition and classification technologies in complex systems. Methods of analysis and optimization of complex systems.

Terms and definitions. Models of queuing systems. The Petri net. Probabilistic modeling. Simulation modeling. Planning and conducting experiments with models. Decision making based on modeling results. Simulation modeling of complex information systems.

1. Mathematical linguistics. Book 1. Quantitative Linguistics: A Study. manual / V.V. Pasichnyk, Yu.M. Shcherbina, VA Vysotska, TV Shestakevich.– Lviv: New World 2000, 359 p. .– (Computer Series).
2. Nikolsky Yu.V. Artificial Intelligence Systems: Educ. manual / Yu.V.Nikolsky, V.V.Pasnychnyk, Yu.M.Sherbyn.- Lviv: Magnolia-2006, 2010. - 279 pp. - (Computer series).
3. Yu. V. Nikolsky, V.V. Pasichnyk, Y. M. Shcherbin. "Artificial Intelligence Systems": a tutorial. 2nd edition, revised and revised - Lviv: Magnolia-2006, 2013. - 279 p.
4. Nikolsky Yu.V. Discrete Mathematics: Teaching manual / Yu.V.Nikolsky, V.V.Pasnychnyk, Yu.M.Sherbyn.- Lviv: Magnolia-2006, 2010. - 279 pp. - (Computer series).

written reports on laboratory work, oral examination (50%)
final control (control measure, exam), written-oral form (50%)