Data Science
8.124.00.03 Data Science
Qualification awarded: Master of Systems Analysis
Entry year: 2021
Mode of study: full
Program duration: 1 year 4 months
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 in-depth theoretical and practical knowledge, skills and understanding related to the areas of systems analysis, engineering data and knowledge, the science of data, data analysis, enabling them to efficiently perform the tasks of innovative character appropriate level of professional activity, which is focused on research and solutions linking complex tasks of research, extraction and analysis of data from various information resources to meet the needs of science, business and enterprises in various fields.
Gained competence: - Specialized conceptual knowledge, which includes modern scientific achievements in the field of systems analysis and information technology and is the basis for original thinking and research
- Build and research models of complex systems and processes using methods of systems analysis, mathematical, computer and information modeling
- Apply methods to reveal uncertainties in the problems of systems analysis, to reveal situational uncertainties and uncertainties in the problems of interaction, counteraction and conflict of strategies, to find a compromise in revealing conceptual uncertainty
- Develop and apply methods, algorithms and tools for forecasting - the development of complex systems and processes of different nature
- Use risk assessment measures and apply them in the analysis of multifactorial risks in complex systems
- Apply methods of machine learning and data mining, mathematical apparatus of fuzzy logic, game theory and distributed artificial intelligence to solve complex problems of systems analysis
- To develop intelligent systems in the conditions of poorly structured data of different nature
- Identify and evaluate the parameters of mathematical models of control objects
- Develop and apply models, methods and algorithms for decision-making in conflict, fuzzy information, uncertainty and risk
- It is clear and unambiguous to communicate their knowledge, conclusions and arguments to professionals and non-specialists, in particular to students
- Freely present and discuss orally and in writing the results of research and innovation, other issues of professional activity in the state and English languages
- Ability to create mathematical models, technologies and algorithms for research, extraction, analysis and processing of Big Data and distributed information resources
- Ability to create mathematical models, technologies and algorithms for research, extraction, analysis and processing of Big Data and distributed information resources
- Ability to develop information products in terms of resource constraints and the need to decompose data research problems using models of artificial intelligence theory and machine learning, game theory methods, creating structures and modeling processes of information resources processing
- Ability to develop mathematical models and algorithms for pattern recognition, in-depth analysis, classification and clustering of data, identification of associations and patterns in information resources using appropriate mathematical software, using formal data representation procedures
- Ability to design new intelligent decision-making systems using specialized software packages using methods of search, extraction, purification and integration of data
- Ability to have sufficient knowledge of mathematical models and methods of data analysis, modeling languages and software to perform practical tasks
- Ability to have skills in the field of analytics of text and Web-resources of different nature in conditions of uncertainty
– It unambiguously clear and communicates own knowledge, conclusions and arguments to specialists and non-specialists, in particular to those who are studying.
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, Professor, Professor of the Department of Information Systems and Networks, Andrii Berko, Andrii.Y.Berko@lpnu.ua
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: The emphasis on sound knowledge of systems analysis, data science, engineering data and knowledge, methods and means of research, extraction and analysis of data and knowledge, and the ability of their application in various domains.