Faculty

of pedagogics

Specialty

7-06-0111-01 «Scientific and pedagogical activity»   

Academic degree

Master

Duration of study

Part time – 1,5 year

Main subjects studied

Methodology of scientific and pedagogical research;

design of educational programs;

pedagogy and psychology of higher education;

innovative approaches and technologies in the educational process;

personal and professional development of a teacher-researcher;

quality management of scientific and pedagogical activity;

productive technologies of scientific and pedagogical communication.

Main competencies that the graduate will have

Be able to apply the methods of scientific cognition (analysis, comparison, systematization, abstraction, modeling, data validation, decision-making, etc.) in independent research activities, generate and implement innovative ideas.

Possess the methodology of scientific cognition, be able to analyze and evaluate the content and level of philosophical and methodological problems in solving problems of research and innovation.

Have the skills to use modern information technologies to solve research and innovation tasks.

Be able to analyze the relevance and innovativeness of scientific research and development in the field of vocational education, use knowledge about trends in the development of vocational education to solve urgent problems of scientific and pedagogical activity.

Be able to apply the basic scientific concepts and research approaches to substantiate the proposed theoretical 6 provisions and methodological solutions in the field of methodology of scientific and pedagogical research.

Be able to use information and communication technologies to organize scientific and pedagogical activities, support the innovative educational process, design modern electronic educational resources and create high-quality educational content for them.

Area of future professional occupation

Higher education; specialized secondary education; vocational education; scientific research and development.

Entrance tests

Faculty

of mathematics and informatics

Specialty

7-06-0713-04 Industrial automatization

Academic degree

Master

Profilization

Analysis and management in digital economy systems

Duration of study

Full-time – 2years

Language of study

Russian/English

Main subjects studied

Management methods in complex systems;

Knowledge management technologies and intelligent information systems;

Smart technologies for business process automation;

Methods of extracting knowledge from experimental data;

CASE-tools for software product development;

Project management in the field of automation;

Neural network technologies;

Fundamentals of Data Science;

Methods and algorithms for distributed processing of unstructured data;

Modern threats and information security technologies;

Technologies and tools for controlling information flows.

Main competencies that the graduate will have

Analyze and apply methods of transformation of production and business, taking into account the trends of society's transition to the digital economy;

Ensure the use of technologies for predicting the development of situations, preliminary analysis and assessment of the state of digital economy systems;

To carry out mathematical modeling of the processes of processing and analyzing data of various kinds using modern tools and methods, machine learning technologies and artificial neural networks;

To ensure the safety of the functioning of computer information systems and industrial computer networks using modern information security technologies;

To ensure the safe management of the work of enterprises and organizations of the digital economy and the protection of the results of their production and research activities.

Area of future professional occupation

Our graduates work at enterprises and organizations of a modern profile, service and product IT companies focused on achievements in the field of high technologies and various forms of the digital economy, as well as engaged in the development, maintenance and operation of software, including those related to the protection of digital information and communication technologies.

Graduates can work:

Entrance tests

•          Interview to determine the level of proficiency in the language of instruction 

•          Additional interview in academic disciplines

Faculty

of mathematics and informatics                   

Specialty

7-06-0611-05 Computer engineering

Academic degree

Master

Profilization

Programmable complexes, systems and services

Duration of study

Full-time – 2 years

Language of study

Russian/English

Main subjects studied

Virtualization technologies of computing systems, Parallel and reconfigurable computing systems, System Engineering, Experiment planning, Development and profiling of Internet services, Decision support systems, Database design and Maintenance, Big Data analysis, Data Mining Methods, Supercomputers and quantum Systems and Technologies, Technologies and Security of the Internet of Things.

Main competencies that the graduate will have

Graduate:

has the skills of conducting scientific research and experiments, the skills of applying system engineering methods in the design of complex computing systems;

develops software systems and Internet services for various subject areas using modern programming platforms and technologies;

solves the problems of parallelization of calculations on multiprocessor systems;

owns big data analysis tools and data mining methods;

uses automation tools to develop models of databases and data warehouses, modeling business processes;

has the basics of project management in the field of OT and flexible project management methodologies;

able to carry out professional written and oral communication, including in a foreign language.

Area of future professional occupation

Development, operation and maintenance of software for computing systems, networks, databases and knowledge. Computer systems management and computer technology services.

Graduates can work in service and product IT companies, IT departments of enterprises, financial, consulting, transport organizations, enterprises producing computing and electronic equipment, scientific institutions and educational institutions in the following positions: software engineer, system administrator, network administrator, development team leader, software architect, database architect data manager, project manager, product manager, - data analyst, head of IT department (in non-core organizations), teacher of special disciplines, researcher.

Entrance tests

•              Interview to determine the level of proficiency in the language of instruction 

•              Additional interview in academic disciplines

Faculty

of economics and management

Specialty

7-06-0533-05 Applied Mathematics and Computer Science

Academic degree

Master

Profilization

Computer Data Analysis

Duration of study

 Full-time – 2 years

Language of study

Russian/English

Main subjects studied

Mathematical modeling and optimization of complex systems;

Multidimensional statistical analysis;

Mathematical and computer forecasting;

Basics of Python Programming;

Introduction to Machine Learning in Python;

Numerical methods of computer modeling and analysis;

Data mining technologies;

Fundamentals of computer data analysis using the R language;

Methods and means of data visualization;

Discrete optimization;

Mathematical methods of control in conditions of incomplete information;

Analysis and forecasting of time series in economics and finance in the Mathematica package.

Main competencies that the graduate will have

Specialists who have completed training in profiling are ready to:

• apply effective mathematical methods and computer technologies, as well as specialized software to solve scientific and practical problems;

• develop and apply effective methods, algorithms and software tools for computer data analysis;

• create and research models of complex systems and processes of various nature;

• develop intelligent decision support systems;

• solve problems of computer modeling and optimization of systems and processes of various nature, management of data mining processes, simulation modeling, statistical modeling and forecasting.

Area of future professional occupation

Entrance tests