113 Applied Mathematics

Specialty 113 “Applied Mathematics” refers to the field of mathematics, which considers the application of mathematical methods, algorithms in other fields of science and technology. Examples of such applications are: numerical methods, mathematical physics, linear programming, optimization and research of operations, modeling of continuous media, information theory, game theory, probability theory and statistics, financial mathematics and actuarial calculations, cryptography, and therefore combinatorics and to some extent finite geometry, graph theory in addition to network planning. Mathematical methods are usually applied to a specific class of applied problems by compiling a mathematical model of the system.

Educational Program

Data Mining

Graduating Department

Computer Mathematics and data analysis

Brief description

Data mining is an educational program (specialization) of specialty 113 “Applied Mathematics”. The educational program is aimed at training researchers with mathematical methods and information technology of machine learning and artificial intelligence to search, analyze, process and visualize data, including measurement and observation data, texts, signals and images to extract knowledge, predict and accept decisions.

Employment opportunities

Employment in enterprises and companies of the IT industry, in information and analytical departments of enterprises of the manufacturing and banking and financial sectors, research institutions, services, etc.

Selective educational components (Profile blocks). Brief description

1. Intelligent Analysis of Big Data

The block of disciplines is aimed at studying mathematical methods, algorithms and software for analyzing large amounts of data of different nature, such as results of observations and measurements, textual information, signals and images, time series and flows based on artificial intelligence and machine learning. The unit includes additional study of modern programming languages, including Python, theory and methods of designing databases and data warehouses, modern methods and tools of design and development of software for analysis and processing of big data. Additional sections of machine learning methods and artificial neural networks, deep learning methods for analysis and forecasting in conditions of uncertainty are studied.

2. Intelligent Business Analysis

The block of disciplines is aimed at studying mathematical methods, algorithms and software tools for analysis and optimization of business processes, decision-making based on data. Provides for the study of methods of requirements analysis, modeling and management of business processes, methods of process and forecasting analytics, project management methods. Methods and software tools for processing, statistical analysis and visualization of data for business decisions, methods of expert analysis and risk analysis are studied. The study of modern algorithmic languages ​​for data analysis, such as R and Python, methods of software development and analysis, software life cycle methods.