Special Course of Scientific Research in the Field of Specialty

Major: Computer Sciences
Code of subject: 7.122.00.O.26
Credits: 9.00
Department: Automated Control Systems
Semester: 3 семестр
Mode of study: денна

Special Course of Scientific Research in the Field of Specialty

Major: Computer Sciences
Code of subject: 7.122.00.O.27
Credits: 9.00
Department: Computer-Aided Design
Lecturer: P. V. Tymoshchuk
Semester: 3 семестр
Mode of study: денна
Learning outcomes: 1) The ability to study the theoretical foundations of research. 2) Ability to know existing methods of information retrieval. 3) Ability to know the principles of building expert systems. 4) Ability to know the basics of metrology, experiment planning and evaluation of the effectiveness of scientific results. 5) Ability to know the principles of preparation, design and defense of scientific papers. 6) The ability to formulate and improve an important research task, to solve it to collect the necessary information and formulate conclusions that can be defended in a scientific context. 7) Ability to work with expert sources of information for the integration of data and knowledge in the field of organization through methods of knowledge acquisition, knowledge representation, classification and compilation of knowledge. 8) The ability to have sufficient scientific skills to successfully conduct research under the supervision of a mentor.
Required prior and related subjects: Differential equations, systems theory, signal processing, electronic circuit theory, programming languages, numerical methods, systems modeling, artificial neural networks, computer networks, distributed computer systems.
Summary of the subject: Methods and means of scientific research and technical creativity, basic information about the organization of research work, its stages, methodology of scientific research in technical fields, and also recommendations on preparation and writing of scientific reports, course and diploma works are studied. The essence of training of skills of independent scientific researches, expansion of scientific world outlook and development of creative thinking is considered. The basics of the theory of experiment planning and analysis of its results are studied. The methodology of experimental researches is considered. Absolute and relative values and a graphic way of data representation are studied. Types and features of presentation of results of scientific researches are considered. The construction and properties of UDC are studied.
Assessment methods and criteria: • current control (50%): current reports of laboratory works, oral asking; • final control (50%, test): fulfilling test tasks.
Recommended books: 1. Anisimov A.V., Glybovets M.M., Kravchenko I.V., Oletsky O.V., Tereshchenko V.M., Kulyabko P.P., "Artificial Intelligence Systems" (in Ukrainian), Kyiv University Press, 2000. 2. Glybovets M.M,. Oletsky O.V., "Artificial Intelligence" (in Ukrainian), KM Academy Publishing House, 2002. 3. Zhurakhivsky A.V., Varetsky Y.O., Bakhor Z.M., "Fundamentals of Scientific Research and Technical Creativity: Tutorial for Students of Electric Power Specialties (in Ukrainian), Priaz. State Tech. University Publishing House, 2000. 4. Spirin O.M. "The Beginnings of Artificial intelligence. Tutorial for Students of Physical and Mathematical Sciences Specialties of Higher Pedagogical Educational Institutions" (in Ukrainian), Zhytomyr DU Publishing House, 2004. 5. Tymoshchuk P.V., "Artificial Neural Networks: Tutorial" (in Ukrainian), Lviv Polytechnic Publishing House, 2011. 6. P. Tymoshchuk and M. Lobur, "Principles of Artificial Neural Networks and Their Applications: Tutorial", Lviv Polytechnic Publishing House, 2020.

Special Course of Scientific Research in the Field of Specialty

Major: Computer Sciences
Code of subject: 7.122.00.O.28
Credits: 9.00
Department: Artificial Intelligence Systems
Lecturer: R.Ya.Kosarevych
Semester: 3 семестр
Mode of study: денна
Learning outcomes: As a result of the study of the discipline, the student should be able to demonstrate the following learning outcomes: to know: application areas and basic applied aspects of machine learning; basic concepts and principles of work of artificial neural networks; problem statement and basic natural language processing methods; be able to: correctly formulate the tasks that arise in the practical activity, to solve them by means of machine learning methods; to analyze a specific problem in order to select the best method of machine learning for its solution; to carry out the analysis and synthesis of informative features; to analyze the work of machine learning methods to identify their strengths and weaknesses
Required prior and related subjects: Discrete Math Mathematical analysis Linear algebra Probability theory Mathematical statistics
Summary of the subject: The purpose of studying the discipline is to obtain the necessary knowledge and to acquire practical skills in applying a wide range of methods and algorithms for analyzing information in the context of machine perception and learning to understand the issues of building, operating and operating computer systems and networks, as well as various information processing and control systems basis.
Assessment methods and criteria: Current control Laboratory work 40 points Examination control Written component of 60 points Oral component 0 points Total 100 points
Recommended books: Stephen Marsland. Machine Learning). Лінійна: An Alg). Лінійнаorithmic Perspective, 452 р., 2015. Ethem Alpaydin. Introduction To Machine Learning). Лінійна, 584 p., 2009. Tom M. Mitchell. Machine Learning). Лінійна [http://www.cs.cmu.edu/~tom/mlbook.html] Yaser S. Abu-Mostafa. Learning). Лінійна from data, 215 p., 2017