The work is dedicated to the generation of tabular synthetic data. The aim of the work is to develop software that allows generating synthetic data that meets the customer's requirements related to the generation of data for student training tasks.
To achieve this goal, software was developed that allow the generation of synthetic data based on rules, copulas, and machine learning algorithms.
The result of the work is tested software that fully meets the customer's requirements. The software can be used to create tasks for student assignments related to regression analysis and other tasks.