The course will outline the basics of mathematical methods of data analysis. Methods such as linear and non-linear regression, analysis and forecasting of time series, clustering and data dimensionality reduction, decision trees and data sampling will be considered. Data analysis methods will be presented in terms of machine learning. Mathematical foundations: linear algebra, mathematical analysis, probability theory, mathematical statistics and random processes will be presented in the context of data analysis.

The course will be of interest to anyone who is interested in how mathematics is applied in data analysis, and who wants to understand the basics of data analysis from a mathematician's point of view.

Financial support. The course is supported by the Ministry of Science and Higher Education of the Russian Federation (the grant to the Steklov International Mathematical Center, Agreement no. 075-15-2022-265).

Lecturer
Shamin Roman Vyacheslavovich

Organizations
Steklov Mathematical Institute of Russian Academy of Sciences, Moscow
Steklov International Mathematical Center