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About the Programme

Data Science master’s  programme includes the full-time educational track for English-speaking students which consists of a set of basic disciplines and variety of elective and optional courses in English.

The aim of the programme is to train highly-qualified experts in applied mathematics, information science and data analysis. 
The programme involves an in-depth study of mathematical methods of artificial intelligence models and modern methods of data analysis, mathematical and informational modeling of complex systems as well as computer realization of these methods. Knowledge and skills of graduates from this course are in demand by Russian Federation ministries and institutions, regional administrations and large companies.
The concept and the curriculum of the specialization in Internet Data Analysis have been developed in conjunction with Yandex. This track involves the teaching of special disciplines by the Company staff members, the participation of students, postgraduates and lecturers in projects implementing tasks suggested by Yandex and related to its business operations, vocational training for students in Yandex and joint research carried out together with Yandex staff. 

The programme includes 3 specializations and a full-time English-taught track (120 credits):

  • English-taught track
General Curriculum Contents
Bridging Courses:
Discrete Mathematics for Application and Algorithm Development
Probability Theory and Mathematical Statistics
Components of the Field of Study
Basic Courses:
Modern Methods of Data Analysis
Modern Methods of Decision Making
Network Science
Machine Learning and Data Mining
Elective Courses:
Automated Methods for Program Verification
Medical Informatics
Data Analysis in Medicine
Data and Service Engineering for Automating Business Processes
  • Internet Data Analysis
Basic Courses:
Modern Methods of Data Analysis
Modern Methods of Decision Making
Machine Learning
Algorithms and Data Structures
Methods and Systems for Processing Big Data
Elective Courses:
Probabilistic and Statistical Approaches in Decision Making
Theory Parallel and Distributed Computations
Optimization in Machine Learning
Image and Video Analysis
Automatic Processing of Texts
Deep Learning
  •  Intelligent Systems and Structural Analysis
Bridging Courses:
Discrete Mathematics for Application and Algorithm Development
Probability Theory and Mathematical Statistics
Basic Courses:
Modern Methods of Data Analysis
Modern Methods of Decision Making
Ordered Sets in Data Analysis
Network Science
Introduction to Machine Learning and Data Mining 
Machine Learning and Data Mining
Elective Courses:
Computational Linguistics and Text Analysis
Information Theory and Combinatorial Theory of Search
Fundamentals of Design and Implementation of Artificial Intelligence
Systems Games and Decisions in Data Analysis and Modelling
Data Analysis in Medicine 
Big Data Analysis
Deep Learning
Automated Methods for Program Verification
Medical Informatics
Robust Methods in Statistics
Decision Making and Data Analysis under Uncertainty and Ambiguity
Automating Business Processes using Machine Learning
  • Technologies of Modelling of Complex Systems
Bridging Courses:
Discrete Mathematics for Application and Algorithm Development
Probability Theory and Mathematical Statistics
Basic Courses:
Modern Methods of Data Analysis
Modern Methods of Decision Making
Ordered Sets in Data Analysis
Mathematical Foundations of Modern Telecommunications
Statistical Methods for Predictive Modeling
Geometric Methods for Predictive Modeling
Elective Courses:
Computational Linguistics and Text Analysis 
Information Theory and Combinatorial Theory of Search 
Fundamentals of Design and Implementation of Artificial Intelligence 
Systems Games and Decisions in Data Analysis and Modelling 
Data Analysis in Medicine 
Big Data Analysis
Deep Learning
Automated Methods for Program Verification 
Medical Informatics 
Robust Methods in Statistics 
Decision Making and Data Analysis under Uncertainty and Ambiguity 
Automating Business Processes using Machine Learning
Data and Service Engineering for Automating Business Processes