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  2. Majors

Data Mining

Major: Computer Sciences
Code of Subject: 6.122.00.O.69
Credits: 5
Department: Automated Control Systems
Lecturer:
Semester: 3 семестр
Mode of Study: денна
Learning outcomes:
Required prior and related subjects:
Summary of the subject:
Recommended Books:
Assessment methods and criteria:

Data Mining

Major: Computer Sciences
Code of Subject: 6.122.00.O.70
Credits: 5
Department: Computer-Aided Design
Lecturer:
Semester: 3 семестр
Mode of Study: денна
Learning outcomes:
Required prior and related subjects:
Summary of the subject:
Recommended Books:
Assessment methods and criteria:

Data Mining

Major: Computer Sciences
Code of Subject: 6.122.00.O.71
Credits: 5
Department: Artificial Intelligence Systems
Lecturer: Boyko Nataliya
Semester: 3 семестр
Mode of Study: денна
Learning outcomes:
1. To substantiate and analyze the choice of a particular type of model and method of data mining in solving practical problems.
2. Use modern software tools for the design and research of data mining systems.
3. Create programs for intelligent data analysis in solving specific practical tasks.
4. To analyze the results of the construction and use of data mining systems in the solution of applied problems.
5. Use software for using intelligent analysis procedures when processing and analyzing primary information.
Required prior and related subjects:
prerequisite:
Methods of calculation
Organization of databases and knowledge
Object-Oriented Programming
co-requisite:
Database and knowledge management systems
Computer design technologies
Technologies for creating software products
Summary of the subject:
Regulatory discipline Intellectual data analysis is part of the cycle of professional training of specialists in the educational-qualification level "Bachelor". The offered training course is a discipline of professional-practical training of specialists in the specialty 122 "Computer Science and Information Technologies". This academic discipline is the theoretical basis of the totality of knowledge and skills forming the technical profile of a specialist in the field of information management systems and technologies.
Recommended Books:
1. Бойко Н. І. Інтелектуальний аналіз даних: Методична праця електронний навчально-методичний комплекс для студентів спеціальності 122 «Комп’ютерні науки та інформаційні технології» [Електронний ресурс]. – Режим доступу: http://vns.lp.edu.ua
2. Акіменко В. В. Проектування СППР на основі нечіткої логіки. Навчально - методичний посібник / В. В. Акіменко, Ю. В. Загородній. – К.: Вид - во КНУ, 2007. – 94c.
3. Барсегян А.А. Методы и модели анализа даннях : OLAP и Data Mining / А.А. Барсегян, М.С. Куприянов, В.В. Степаненко, И.И. Холод - СПб.: БХВ- Петербург, 2004. - 336 с.
4. Брагинський О. Л. Проектування систем штучного інтелекту / О. Брагинський. – К., МНТУ, 2002. – 205 с.
5. Глибовец Н. Н. Генетические алгоритмы и их использование для решения задачи составления расписаний // Кибернетика и системный анализ / Н. Н. Глибовец, С. А. Медведь. 2003. – № 1. – С. 95–108.

Assessment methods and criteria:
- current control (40%): written reports on laboratory work, practical tasks, oral examination;
- final control (60% of assessment for works), testing (50%), oral component (10%).