Artificial Intelligence
8.122.00.04 Artificial Intelligence
Qualification awarded: Master in Computer Sciences
Entry year: 2022
Mode of study: full
Program duration: 1,4 years
Institute: Institute of Computer Science and Information Technologies
Number of credits: 90 credits ECTS
Level of qualification according to the National Qualification Framework and the European Qualifications Framework: NQF Level 7 (Second cycle of QF-EHEA / EQF Level 7)
Field(s) of study: Information technology
Specific admission requirements: Entrance examinations in specialty and foreign language.
Specific arrangements for recognition of prior learning: Given that the previous level obtained in another country requires nostrification, which is held Lviv Polytechnic.
Qualification requirements and regulations, including graduation requirements: The full implementation of the curriculum and defense of Master's Thesis.
Characteristics of the educational program: Gaining profound theoretical and practical knowledge and skills in the field of artificial intelligence systems which will enable the students effectively fulfill innovative tasks on the corresponding level of professional activity focused on the research and solution of complex problems concerning information systems development and engineering in order to meet the needs of science, business and enterprises in various branches.
Програмні результати навчання: PH1. Have specialized conceptual knowledge that includes modern scientific achievements in the field of computer science and is the basis for original thinking and conducting research, critical understanding of problems in the field of computer science and at the border of the fields of knowledge.
PH2. Have specialized computer science problem-solving skills necessary for conducting research and/or conducting innovative activities to develop new knowledge and procedures.
PH3. It is unambiguous to convey one's own knowledge, conclusions and arguments in the field of computer science to specialists and non-specialists, in particular to persons who are studying.
PH4. Manage work processes in the field of information technologies, which are complex, unpredictable and require new strategic approaches.
PH5. Evaluate the results of teams and collectives in the field of information technologies, and ensure the effectiveness of their activities.
PH6. Develop a conceptual model of an information or computer system.
PH7. Develop and apply mathematical methods for the analysis of information models.
PH8. Develop mathematical models and methods of data analysis (including large data).
PH9. Develop algorithms and software for data analysis (including large data).
PH10. Design architectural solutions of information and computer systems for various purposes.
PH11. Create new algorithms for solving problems in the field of computer science, evaluate their effectiveness and limitations on their application.
PH12. Design and maintain databases and knowledge.
PH13. Assess and ensure the quality of information and computer systems for various purposes.
PH14. Test the software.
PH15. Identify the needs of potential customers regarding the automation of information processing.
PH16. Conduct research in the field of computer science.
PH17. Identify and eliminate problematic situations during software operation, formulate tasks for its modification or reengineering.
PH18. Collect, formalize, systematize and analyze the needs and requirements for the information or computer system being developed, operated or supported.
PH19. To analyze the current state and global trends in the development of computer sciences and information technologies.
PH20. Collect and pre-process data from various data sources (tabular, text, images, time series, etc.), including data with outliers and uncertainties to solve various problems.
PH21. Develop an end-to-end machine learning process: data reception and pre-processing; model building, validation, inference and feedback loop.
PH22. Select, design, evaluate, and tune machine and deep learning models.
PH23. Analyze data (including big data) using modern tools.
PH24. Implement and deploy event-driven data pipelines.
Line 1. Deep learning systems.
PH25. Develop mathematical models and algorithms for pattern recognition and object classification in intelligent decision support systems.
PH26. Create mathematical models and decision-making algorithms using algorithmic and software tools, machine learning, artificial neural networks, evolutionary modeling, methods of genetic optimization, inductive modeling and mathematical apparatus of fuzzy logic.
PH27. Perform natural language processing using appropriate techniques to search for text, emotions, and sentiments.
Academic mobility: Based on bilateral agreements between National University "Lviv Polytechnic" and the Technical University of Ukraine. Based on bilateral agreements between National University "Lviv Polytechnic" and schools partner countries
Work placement(s): Master’s Thesis Related Research Practice
Programme director: Doctor of Technical Sciences, Head of the Department of Artificial Intelligence Systems, Shakhovska Natalia Bogdanivna, natalya233@gmail.com
Occupational profiles of graduates: Work in information technology, communication and IT project management: IT-companies, finance companies, insurance companies, government agencies, consulting.
Access to further studies: Obtaining third (educational and scientific / educational and creative) level
Other program features: Internship of students in branches of the department in IT companies