Data Mining
Major: Computer Technologies and Systems for Publishing and Printing Industry
Code of subject: 7.186.01.E.015
Credits: 4.00
Department: Publishing Information Technologies
Lecturer: Dr.Sc, Prof., Roman Tkachenko
Semester: 2 семестр
Mode of study: денна
Завдання: The study of the discipline involves the formation of competencies in students:
general competencies:
1. Ability to search, process and analyze
information from various sources.
2. Ability to make informed decisions.
3. Ability to critically comprehend the problems of
of publishing and printing and on the border of branches of knowledge, as well as
promising areas of industry development.
professional competencies:
1. Ability to organize activities and effectively
manage institutions / units in the field of publishing and
printing.
2. Ability to perceive and acquire new knowledge that corresponds to the trends in the development of intelligent systems in printing and other industries, and integrate them with previously acquired knowledge.
3. Ability to develop effective information and organizational solutions aimed at implementing innovative developments in production.
4. Ability to evaluate and ensure the quality
of the work performed.
Learning outcomes: As a result of studying the discipline, the student must be able to demonstrate the following program learning outcomes:
Learning outcomes Learning and teaching methods Methods of assessing the level of achievement of learning outcomes.
1. Knowledge that will provide the ability to analyze and critically reflect on problems and challenges in the field of computer technology publishing systems and printing industries.
2. Knowledge and understanding of the scientific principles underlying the development and use of computer technology and information publishing systems.
3. Ability to manage the processes of preparation, substantiation, implementation, organization and control of the production of electronic multimedia publications, use knowledge of modern technologies for their production.
4. Design and develop interactive media and their individual elements, process multimedia content.
5. Knowledge and understanding of the basics of analysis and evaluation of problems and tasks, the solution of which contributes to improving the efficiency of information resources in the field of printing and multimedia.
6. To know and understand the principles of construction and operation of integrated data mining systems and features of their components in printing.
7. Use modern information sources of national and international level to assess the state of study of the object of research and the relevance of the scientific problem.
8. Ability to formulate and improve an important research problem, to collect the necessary information and formulate conclusions that can be defended in a scientific context.
9. Be responsible for the development of professional knowledge and practices, evaluation of the strategic development of the team, the formation of effective personnel policy.
10. Develop and implement projects of publishing and printing production and systems of their engineering and technical support, taking into account engineering, legal, economic, environmental and social aspects,
to carry out their information and methodological support.
11. To manage complex activities in the field of publishing and printing, organize and improve the activities of publishing and printing industries, develop plans and measures for their implementation, ensure quality, and calculate the technical and economic efficiency of production.
12. Apply modern experimental and mathematical methods, information technology and specialized software for research and development in the field of publishing and printing.
13. Search for the necessary data in scientific literature, databases and other sources, analyze and evaluate these data.
14. Ability to communicate, including oral and written communication in Ukrainian and foreign languages (English, German, Italian, French, Spanish).
15. Ability to understand the need for lifelong learning in order to deepen the acquired and acquire new professional knowledge.
16. Ability to take responsibility for the work performed, make decisions independently, achieve the goal in compliance with the requirements of professional ethics.
- Performing practical work and their protection.
- Writing a calculation and graphic work - Evaluation of practical work.
- Evaluation of calculation and graphic works.
- Testing.
Required prior and related subjects: Related and subsequent disciplines
• Automation of text and graphic information processing
• Execution of master's qualification work
Summary of the subject: The discipline is part of the cycle of professional training of specialists of the second master's level of education. The proposed course will provide students with in-depth theoretical and practical knowledge, skills and understanding related to modern trends in the development of information technology. The knowledge gained in the process of studying this discipline is based on both classical theorems and methods of linear algebra, applied statistics, and modern machine learning algorithms.
Опис: Basic concepts in the field of IDA, Data Mining, Business Intelligence, classification and comparative characteristics of the main methods, practical application.
Data. Types of data. Methods of data representation and processing. Big data. Data processing.
Computational intelligence. Components of computational intelligence. Soft computing.
Basic methods of computational intelligence. Fuzzy logic. Algorithms of global optimization.
Artificial neural networks. Basic paradigms. Disadvantages of classical neural network methods in the context of big data.
Model of geometric transformations. Neuro-like structures of the model of geometric transformations (NS MHP).
High-speed computational intelligence on the NS MHP.
Models of fuzzy logic on the NS IHP.
Assessment methods and criteria: 1. Performing practical work and their protection.
2. Writing of calculation and graphic work
3. Examination.
Критерії оцінювання результатів навчання: The maximum score in points is 100;
Current control (practical work) – 20;
Current control (calculation and graphic work) – 10.
Examination control (written component) – 40.
Examination control (oral component) – 30.
Recommended books: Аналіз даних та знань : навчальний посібник / Литвин В. В., Пасічник В. В., Нікольський Ю. В. ? Львів : Магнолія-2006 , 2021. ? 276 с.
Інтелектуальний аналіз даних : навчальний посібник / А. О. Олійник, С. О. Субботін, О. О. Олійник. – Запоріжжя : ЗНТУ, 2012. – 278 с.
Черняк О. І. Інтелектуальний аналіз даних : підручник / О. І. Черняк, П. В. Захарченко. – К. : Знання, 2014. – 599 с.
A. Agresti. Statistical methods for social sciences. Boston: Pearson, 2018.
Zumel N., Mount J. Practical Data Science with R. - Manning Publications Co., 2014. – 417 p.