Computer Science (Artificial intelligence)
6.122.00.13 Computer Science (Artificial intelligence)
Qualification awarded: Bachelor in Computer Science with a degree in Artificial Intelligence Systems
Entry year: 2024
Mode of study: full
Program duration: 4 years
Institute: Institute of Computer Science and Information Technologies
Number of credits: 240 ECTS credits
Level of qualification according to the National Qualification Framework and the European Qualifications Framework: NQF Level 6 (First cycle of QF-EHEA / EQF Level 6)
Field(s) of study: Information technology
Specific admission requirements: None
Specific arrangements for recognition of prior learning: Provided that the previous level was obtained in another country, nostrification is required, which is carried out by Lviv Polytechnic.
Qualification requirements and regulations, including graduation requirements: Full implementation of the curriculum and defense of bachelor's thesis
Characteristics of the educational program: Provide students with the knowledge, skills and abilities needed to make decisions in complex systems of different nature using artificial intelligence and modern information technology, fundamental and applied methods of data processing and analysis to solve problems in various fields of science, technology, finance, socio-economic and political spheres, global and local environmental issues and various spheres of social and economic life.
Be prepared to successfully master more complex programs for researchers in artificial intelligence systems.
Програмні результати навчання: 1. Apply knowledge of the primary forms and laws of abstract logical thinking, the basics of the methodology of scientific knowledge, forms and methods of extraction, analysis, processing and synthesis of information in the subject area of computer science.
2. To use the modern mathematical apparatus of continuous and discrete analysis, linear algebra, and analytical geometry in professional activities to solve theoretical and applied problems in the design and implementation of information objects.
3. Use knowledge of the laws of random phenomena, their properties and operations on them, models of random processes and modern software environments to solve problems of statistical data processing and construction of predictive models.
4 Use computational intelligence, machine learning, neural network and fuzzy data processing, genetic and evolutionary programming to solve problems of recognition, prediction, classification, identification of control objects, etc.
5. Design, develop and analyze algorithms for solving computational and logical problems, and evaluate the efficiency and complexity of algorithms based on the use of formal models of algorithms and computational functions.
6. Use methods of numerical differentiation and integration of functions, solving ordinary differential and integral equations, features of numerical methods and the possibility of their adaptation to engineering problems, and have the skills of software implementation of numerical methods.
7. Understand the principles of modeling organizational and technical systems and operations; use operations research methods, solving single- and multicriteria optimization problems of linear, integer, nonlinear, stochastic programming.
8. Use the system analysis methodology of objects, processes and systems for research, forecasting, management and design of dynamic processes in macroeconomic, technical, technological and financial entities.
9. Develop software models of subject environments, and choose a programming paradigm from the standpoint of convenience and quality of application to implement methods and algorithms for solving problems in computer science.
10. Use tools for developing client-server applications, designing conceptual, logical and physical models of databases, developing and optimizing queries, creating distributed databases, repositories and storefronts, knowledge bases, including cloud services, and using web programming languages.
11 Have the skills to manage the life cycle of software, products, and information technology services following the customer's requirements and restrictions and develop project documentation (feasibility study, terms of reference, business plan, agreement, contract, contract).
12. Apply methods and algorithms of computational intelligence and data mining in the problems of classification, forecasting, cluster analysis, search for associative rules using software tools to support multidimensional data analysis based on the technologies of DataMining, TextMining, and WebMining.
13. Know the languages of system programming and methods of program development that interact with the components of computer systems, know network technologies, computer network architectures, have practical skills in computer network administration technology and their software
14. Apply knowledge of methodology and CASE tools for designing complex systems, methods of structural analysis of systems, and object-oriented design methodology in the development and study of functional models of organizational, economic and industrial systems.
15. Understand the concept of information security, the principles of secure software design, and ensure the security of computer networks in conditions of incomplete and uncertain source data.
16. Perform parallel and distributed calculations, apply numerical methods and algorithms for parallel structures, and parallel programming languages to develop and operate parallel and distributed software.
17. Use the technologies and tools of search engines and data mining methods of various structures (including texts and images) to process, interpret, and summarize data.
18. Analyze the strengths and weaknesses of design and technological decisions using artificial intelligence methods, weigh and analyze the opportunities and risks of decisions, and evaluate the effectiveness of decisions.
Academic mobility: Based on bilateral agreements between Lviv Polytechnic National University and technical universities of Ukraine, and higher educational institutions of foreign partner countries.
Work placement(s): Design and technological practice. Practice on the topic of bachelor's thesis.
Programme director: Doctor of Technical Sciences, Head of the Department of Artificial Intelligence Systems, Shakhovska Natalia Bogdanivna, natalya233@gmail.com
Occupational profiles of graduates: Jobs in the field of data analytics, information technology, artificial intelligence: IT companies, specialists in the development of mathematical, information and software information systems in information technology.
Access to further studies: Obtaining the second (master's) level