01.03.04 Applied mathematics

This area of studies in focused on modern concepts and methods of big data analysis to identify patterns and dependencies, to predict parameter trends and values, to compile analytical reviews and reference materials, to prepare management decisions and to provide business intelligence. Special attention is given to programming and efficient use of application software for computing and research, including prognostic and analytical platforms by domestic and foreign developers, and to the study of data repository architecture, construction and operation principles. 
Level of education:
Bachelor's degree
Form of training:
Full-time (daytime)
Place of training:
Moscow
Entrance examination:
— Mathematics (major)
— Russian language
— Information science and ICT
Profiles and specializations:
Data analysis
Students receive theoretical instruction and practical training in the field of data processing, storage, search and analysis in various applied areas. Their training includes acquisition of skills in using specialized software and mathematical techniques to identify patterns and dependencies, to predict parameter trends and values, to make analytical reviews and reference materials, to prepare management decisions and to provide business intelligence. Students pursuing the program have access to modern training laboratories, foreign and domestic specialized software, and large volumes of experimental data in economics, physics, engineering, natural processes, etc.
Professions that a graduate can choose
  • data engineer
  • data scientist
  • big data analyst
  • mathematical engineer
Specialized disciplines
  • Group theory and number theory
  • Theory of algorithms and recursive functions
  • Additional chapters of computational mathematics
  • Programming languages for statistical data processing
  • Applied problems of mathematical statistics
  • Machine learning techniques and tools
  • Data analysis methods
  • Data management systems
  • Optimal control theory models and methods
  • Prediction and analysis systems
  • Simulation software
  • Models and methods of predictive analytics
  • Statistical data organization, processing and storage technology
  • Simulation of dynamic systems
  • Non-linear dynamics application tasks
Graduating department:
Applied Mathematics Department