Data Mining

Course: Computer science

Structural unit: Faculty of information Technology

Title
Data Mining
Code
ОК 27
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2022/2023
Semester/trimester when the component is delivered
7 Semester
Number of ECTS credits allocated
5
Learning outcomes
Apply methods and algorithms of computational intelligence and intelligent data analysis in the tasks of classification, forecasting, cluster analysis, search for associative rules using software tools to support multidimensional data analysis based on DataMining, TextMining, WebMining technologies.
Form of study
Full-time form
Prerequisites and co-requisites
Know the basics of probability theory, probabilistic processes and the basics of mathematical statistics. To be able to perform research of probabilistic processes. Have skills in working with mathematical packages, the basics of programming in the Python language.
Course content
Within the framework of the discipline, the main attention is paid to researching the processes of knowledge discovery, mastering the methods and algorithms of Data Mining. Concepts, technologies, practical approaches to building associative rules and decision trees, building datawarehouse and OLAP technologies, neurocomputer technologies and neural networks, models and methods of classification, clustering, sequencing, forecasting and some other methods of intelligent data analysis are considered. Attention is paid to the acquisition of practical skills in the use and adaptation of some of the most well-known Data Mining systems, analytical platforms and libraries, to the acquisition of the ability to program individual elements of Data Mining systems of various purposes and different problem orientations at all stages of the life cycle of the information system.
Recommended or required reading and other learning resources/tools
Planned learning activities and teaching methods
Lectures, laboratory works, individual work
Assessment methods and criteria
The form of the final evaluation is the credit. To determine the level of achievement of learning outcomes, students present the results of their work during the defense of laboratory reports, answer the teacher's questions, to test the acquired skills, the teacher can give additional tasks that must be implemented by the student during the defense of the work. The condition for receiving a positive final grade in the discipline is to achieve at least 60% of the maximum possible number of points, i.e. the student is awarded a pass. The maximum number of points that a student can receive for work during the semester is 80 points on a 100-point scale plus up to 20 points for the final test. That is, under the condition of credit, a student can receive up to 100 points for work in the semester. If he scored 48 points or more, but less than 60 points, then he must take the final test. If more than 60 points - at will, but still he cannot score more than 100 points.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Departments

The following departments are involved in teaching the above discipline