Specialization: “Computer Statistics and Data Analysis”.

**Data analyst is a profession **that has gained popularity with the information technology development. Big data processing requires special statistical methods. A data analyst should combine proficiency in computer-aided processing with a good knowledge of the theoretical mathematical statistics. His or her purpose is not only to identify the hidden patterns in the existing datasets, but also to put forward and test the hypotheses about the phenomena under study, to predict their further development, to assist customers in decision-making.

The steady increasing need in collecting and analyzing the huge amounts of data generates the high demand for statistical data analysts. No wonder that the data analysts is called the most promising profession of the 21st century.

The following courses are delivered within the specialization:

**Computer statistics**– acquaintance with modern computer software for data analysis and statistics.**Machine learning**– introduction to modern methods of classification, prediction, machine language processing and pattern recognition using neural networks, decision trees, ensemble algorithms and other artificial intelligence techniques.**Time series**– data analysis with regard to time and space, modern techniques of statistical prediction.**Big data analysis**– methods for identification of statistical relationships and dependencies, creation and validation of models for the investigated phenomena based on large amounts of multi-variate information: factor analysis, dimension reduction, cluster analysis, multidimensional scaling, factor analysis, graphical statistical methods and models.**Statistical computations**– the effective, modern methods and algorithms of statistical computations.**Nonparametric statistics**– the science and art of constructing and fitting mathematical models for statistical data based on minimal a priori assumptions.**Survey sampling**– how to make sampling and analyze the data from the sample surveys as well as how to process the data with non-sampling errors.

In addition to gaining the fundamental theoretical background, our students acquire the real-world skills in applied statistics, mathematics and programming. The intensive studies of statistical modeling and prediction provide the data analysts training at the highest international level.