Master program "Big data: infrastructures and methods"

Professor V.A. Sukhomlin

The Master's educational program "Big Data: Infrastructures and Methods for Problem Solving" aims to train Master's students majoring in the development and application of methods for information (knowledge) extraction from multistructured big data to data intensive domains (astronomy, molecular biology, material science, neuroscience, medicine, economics, sociology). The students study the methods for anomaly detection in big data collections, modeling of natural phenomena using hypotheses-stimulated virtual experiments. Students are trained to solve topical problems in the "data science" field. The present Master's program is supported by IBM and is based on the state-of-the-art technologies and tools implemented in modern Big Data platforms including the tools for the development of scalable programs for big data analysis in distributed multi-node clusters, virtual and materialized data integration in subject mediators and data warehouses, entity extraction, recognition and fusion in massive collections of unstructured and semi-structured data applying cognitive methods, statistical analysis,and machine learning.


  • Mathematical modelling
  • Software for modern computer complexes
  • Data mining
  • Multi-structured big data management
  • Applied multivariate statistical analysis
  • Virtual integration of heterogeneous data and data models unification
  • Identification and merging of entities in big data
  • Materialized data integration and big data warehousingv
  • Big data analysis in social media
  • Data Science and Cognitive Systems (in English)
  • Hypotheses and models in data-intensive areas
  • Big data anomaly detectionv
  • Russia language
  • Modern philosophy and methodology for science
  • History and methodology for applied mathematics and computer sciencev
  • Specialised seminar
  • Research work