Modern methods of visualization data and data mining | Centre for Joint Academic Programmes

Level: Master

Semestre: 3rd

ECTS: 3

Working Hours:

- Lectures: 32

- Labs: 32

- Self-study: 44

- Total: 108

Language of Instruction: English (Russian)

Author of the Course: Evgeny Pchelintsev, PhD, Associate Professor.

Lecturers:

Evgeny Pchelintsev, PhD, Associate Professor.

Objectives:

- This course is intended for training Masters in Math to apply mathematical methods and modeling technique in their professional work.

- Prepare a Master of Mathematics for applying statistical methods and numerical experiment for applications in professional activities.

- Connect theory and practice, to teach students to "see" the statistical problems in various subject areas and correctly apply the methods of applied statistics, practical examples show the possibilities and limitations of statistical methods.

Learning Outcomes:

To know:

- the basic methods of applied statistics, the appointment, capabilities and features of modern statistical software (R, Statistica, etc.), advantages of the data processing using statistical software in comparison with other methods (tabular processors, database, programming, etc.).

To be able to:

- understand the posed problems;

- reasonably choose the data processing method according to the task and the type of data available;

- To carry out data selection, the various types of modifications and data conversion;

- To freely navigate in the menu of the package and be able to use the various functions;

- Present the results of treatment in the form of tables and graphs;

- Use the syntax and create a data processing program;

- Competently draw conclusions and interpret the results obtained in the course of treatment with a statistical software.

Assessment Methods:

The current control of mastering the discipline includes two written test and four reports on the labs.
The final control – exam.