specialties

specialties (227)

Technical Building Equipment and Supply Engineering

Faculty

of engineering and construction

Specialty

7-07-0732-02 Technical Building Equipment and Supply Engineering

Qualification

Civil engineer

Academic degree

Master

Profilization

«Heat and gas supply, ventilation and air basinprotection

Duration of study

Full-time – 5years

Language of study

Russian

Main subjects studied

  • Descriptive geometry and engineering graphics
  • Technical thermodynamics
  • Heating
  • Ventilation
  • Air conditioning and refrigeration
  • Heat generating units
  • Water supply and sanitation
  • Heat supply
  • Organization, planning and management of production
  • Information modeling of engineering systems of buildings and structures
  • Operation and maintenance of engineering systems of buildings and structures

Main competencies that the graduate will have

  • Use basic methods of collecting, processing and storing information, programming languages to solve practical problems in the field of heat and gas supply and ventilation
  • Calculate and analyze the operating modes of air conditioning systems, prospects and directions of their development
  • Carry out calculation and selection of heat generating units to ensure the efficiency of heat and gas supply systems
  •  Apply methods of calculation and selection of equipment for water supply and sanitation systems to solve applied and engineering problems
  • Apply the basics of technology, economics, organization and management for the design, construction and operation of heat and gas supply and ventilation systems

Area of future professional occupation

  • engineering and technical design and provision of technical advice;
  • technical testing, research, analysis and certification;
  • scientific research and development in the field of natural and technical sciences
  • distribution of gaseous fuel through pipelines;
  • production, transmission, distribution and sale of steam and hot water;
  • air conditioning 

Entrance tests

INTERVIEW to determine the level of proficiency in the language of instruction (Russian)

Additional information

Contacts of the Faculty of Engineering and Construction:

  • e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
  • phone number: +375 29 71 75 375 (Viber; WhatsApp)
  • website: fbt.grsu.by
  • instagram: @isf_grsu

Building and Construction

Faculty

of engineering and construction

Specialty

7-07-0732-01 Building and Construction

Qualification

Civil engineer

Academic degree

Master

Profilization

«Industrial and civil construction»

Duration of study

Full-time – 5years

Language of study

Russian

Main subjects studied

  • Building Materials Science
  • Resistance of materials
  • Construction mechanics
  • Organization and management of processes in construction
  • Architecture
  • Building Construction Technologies
  • Soil mechanics, bases and foundations
  • Metal structures
  • Reinforced concrete and stone structures
  • Production economics
  • Assessment of the condition and reinforcement of building structures

Main competencies that the graduate will have

  • Apply modern methods and approaches in the field of construction technologies, structures and materials to solve engineering and construction tasks
  • Use software tools to solve engineering problems
  • Apply calculations of building structures and their elements for strength, stability and rigidity to solve engineering and construction tasks

Apply modern methods, equipment and technologies for the construction of buildings and structures

Area of future professional occupation

  • building construction;
  • construction of other engineering structures;
  • other special construction works;
  • scientific research and development in the field of technical sciences

Entrance tests

  • INTERVIEW to determine the level of proficiency in the language of instruction (Russian)

Additional information

Contacts of the Faculty of Engineering and Construction:

  • e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
  • phone number: +375 29 71 75 375 (Viber; WhatsApp)
  • website: fbt.grsu.by
  • instagram: @isf_grsu


 

Mechanical engineering technology, metalcutting machines and tools

Faculty

of innovative engineering

Specialty

6-05-0714-02 Mechanical engineering technology, metalcutting machines and tools

Qualification

Mechanical engineer

Academic degree

Bachelor

Profilization

Technological support of machine-building production

Duration of study

Full-time – 4 years

Language of study

English, Russian

Main subjects studied

Mechanics of materials, materials science, machine parts, engineering graphics, technology of structural materials, cutting theory, metal cutting machines and tools electrical engineering and electronics.

Main competencies that the graduate will have

– To use knowledge about the properties of structural materials and their interrelationships with the strength characteristics of parts to determine stress and deformation in typical machine parts.

– Based on the knowledge of the requirements for standard machine parts, design these parts and assemblies and perform their calculations.

– To propose schematic diagrams of mechanisms for solving engineering problems, to master methods for calculating static and dynamic systems, rationing the accuracy of machine parts to ensure the required quality of machines and mechanisms.

– To use knowledge about the basic processes in metal cutting, the processes of surface formation on metal-cutting machines, the features of various types of machines for the design of cutting tools.

Area of future professional occupation

– departments and workshops of machine-building enterprises;

– design and research organizations;

– certification and licensing services for products;

– commercial and administrative structures for the maintenance of equipment and the sale of products on the domestic and international market.

Entrance tests

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

Operation of ground transport and technological machines and complexes

Faculty

of innovative engineering

Specialty

6-05-0715-07 Operation of ground transport and technological machines and complexes

Qualification

Engineer

Academic degree

Bachelor

Profilization

– Technical operation of cars and car service

– Electric and autonomous transport

Duration of study

Full-time – 4 years

Language of study

English, Russian

Main subjects studied

Engineering graphics, technology of structural materials, materials science, theory of mechanisms and machines, mechanics of materials, theoretical mechanics, maintenance of motor vehicles, diagnostics of electric and autonomous transport, device of vehicles, electrical equipment of cars, electronic car control systems, electric machines.

Main competencies that the graduate will have

– Apply various methods of graphic constructions on the plane and in the space of car parts and technical equipment for maintenance and repair of motor vehicles.

– To select structural materials of a certain composition and functional properties during maintenance and repair of cars.

– Carry out calculations for strength, rigidity and stability of structures.

– To carry out measurements of electrical quantities, calculation of electrical circuits and determination of parameters of elements of electronic devices and automation devices.

Area of future professional occupation

– technical services of motor transport and auto repair enterprises;

– transport workshops of factories and firms;

– car service organizations.

Entrance tests

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

Computer Physics

Faculty

Physics and technology faculty

Specialty

6-05-0533-04 Computer Physics

Qualification

Physicist. Programmer

Academic degree

Bachelor

Profilization

Computer modeling of physical and technological processes

Duration of study

Full-time – 4years

Language of study

Russian, English

Main subjects studied

Higher mathematics.

General physics.

Theoretical physics.

Programming languages and technologies.

Computer technologies in physics.

Computer technologies in engineering.

Modern physics experiment

Main competencies that the graduate will have

Master the basics of research activities, search, analyze and synthesize information.

Master modern technologies and programming languages.

Apply the laws of mechanics, molecular physics, thermodynamics, electromagnetism, optics, atomic and nuclear physics for the development and software implementation of mathematical models of physical and technological processes.

Possess methods of automation of experimental research and processing of their results

Area of future professional occupation

Scientific research and development.

Computer modeling in physics and engineering.

Education

Entrance tests

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

Information and Measuring Equipment

Faculty

Physics and technology faculty

Specialty

6-05-0716-03 Information and Measuring Equipment

Qualification

Engineer

Academic degree

Bachelor

Profilization

Information and Measuring Equipment

Duration of study

Full-time – 4years

Language of study

Russian, English

Main subjects studied

Mathematics, physics, chemistry.

Information technology.

Mechanics.

Electrical engineering and electronics.

Measurements, measuring equipment and systems.

Automation.

Design and production technologies

Main competencies that the graduate will have

Master the basics of research activities, search, analyze and synthesize information.

To use the basic concepts and laws of physics, the principles of experimental and theoretical study of physical phenomena and processes to solve the problems of professional activity.

Solve measurement tasks, including the selection of measurement methods and processing of measurement results

Area of future professional occupation

Scientific research and development in the field of natural and technical sciences.

Manufacture of instruments and instruments for measurement, testing and navigation.

Repair of general and special purpose machinery and equipment.

Manufacture and repair of electronic household appliances

Entrance tests

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

Physics

Faculty

Physics and technology faculty

Specialty

6-05-0533-01 Physics

Qualification

PhysicistTeacher

Academic degree

Bachelor

Profilization

Methods of teaching physics and computer science

Duration of study

Full-time – 4years

Language of study

Russian, English

Main subjects studied

Higher mathematics.

General physics.

Theoretical physics.

Computer modeling of physical processes.

Electronics and circuitry.

Spectroscopy and laser physics.

Methods of teaching physics and computer science

Main competencies that the graduate will have

Master the basics of research activities, search, analyze and synthesize information.

Solve standard tasks of professional activity based on the use of information and communication technologies.

Apply the laws of mechanics, molecular physics, thermodynamics, electromagnetism, optics, atomic and nuclear physics to solve typical computational and experimental physical problems.

Possess methods and devices for measuring physical quantities.

Use various methods of teaching physics and computer science in order to maximize the effectiveness of the educational process

Area of future professional occupation

General secondary education.

Higher education.

Analysis of physical and chemical properties of the substance

Entrance tests

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

Robotic Systems

Faculty

Physics and technology faculty

Specialty

6-05-0713-05 Robotic Systems

Qualification

Engineer Specialist

Academic degree

Bachelor

Profilization

Industrial robots and robotic complexes

Duration of study

Full-time – 4years

Language of study

Russian, English

Main subjects studied

Mathematics, physics, chemistry.

Computer science and computer engineering.

Theoretical and applied mechanics.

Electrical engineering and electronics.

Executive systems of industrial robots.

Control systems of industrial robots.

Industrial robot software

Main competencies that the graduate will have

Master the basics of research activities, search, analyze and synthesize information.

Master the basics of higher mathematics, physics, chemistry, computer science, necessary for solving professional problems.

Know the types and means of automation of various types of production and production processes.

Possess methods of diagnostics, adjustment and technical operation of robotic complexes, including numerical control machines

Area of future professional occupation

Scientific research and development in the field of natural and technical sciences.

Production of individual machines and equipment for general and special purposes.

Production of computing electronic and optical equipment, electrical equipment.

Operation and repair of robotic systems

Entrance tests

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

 

Applied Mathematics and Informatics

 

Faculty 

FEU

Specialty 

1-31 80 09 Applied Mathematics and Informatics
Profilisation Computer Data Analysis
Language of study  English / Russian
Mode of study  Full-time
Term of study  1 year 8 months
Entrance exams for foreign citizens 

Curriculum

(with an indication of the main disciplines studied)

 
Names of master’s degree students’ activities, cycles of  disciplines, disciplines Number of credits

 

 

  • • Mathematical modelling and optimization of complex systems

Study of the theoretical foundations of mathematical modeling and optimization, principles and practical methods for constructing and analyzing models of complex processes, phenomena and systems.

Solving optimization problems in various fields of science, technology and economics.

Formation of practical skills in applying mathematical modeling and optimization methods to solve problems of modeling and optimizing complex systems using modern software

3
 
  • • Multivariate statistical analysis

Study of mathematical models and methods of statistical analysis of multidimensional structure data.

Formation of practical skills for solving applied problems of multidimensional data analysis using modern software in the field of statistical analysis

3
 
  • • Mathematical and computer prediction

Obtaining theoretical knowledge and practical skills on methodological foundations and methods of making forecasts based on mathematical models.

Building predictive models.

Mastering the methods of constructing econometric models based on spatial data and time series, building econometric models based on economic and statistical data.

Mastering computer software packages for economic and statistical data analysis and forecasting

6
 
  • • Special data structures

Creating a database for using modern libraries in various programming languages.

The ability to adapt existing algorithms and data structures for specific application tasks.

Development of the ability to evaluate the complexity of operations with data structures, perform worst-case estimation and amortized estimation of operations, use probabilistic estimation of the complexity of operations.

Learning about special data structures.

Study of methods of organizing efficient search, optimization of this method, using various data structures.

 
  • • Technologies and computer data processing systems

Study of modern computer systems for statistical data processing.
The most commonly used statistical methods of data processing and the principles of forming conclusions based on their application, the features of implementing algorithms for statistical methods of data processing in various modules of computer data processing systems.
Using computer systems in solving applied problems related to data processing

3
 
  • • Fundamentals of programming on Python

Mastering the syntax of the Python programming language and acquiring practical programming skills in Python

3
 
  • • Mathematics and Python for data analysis

Acquisition of practical skills in using mathematics to solve data analysis problems using the Python programming language

3
 
  • • Introduction to computer-assisted teaching on Python

Study of various models of neural networks, methods and algorithms of their training for solving practical problems with the use of ready-made libraries of the Python programming language

 
  • • Applied problems of data analysis on Python

Study of methods for solving applied problems of data analysis using  Pandas module of the Python programming language

3
 
  • • Multivariate statistical analysis on panel data

Construction of econometric models based on panel data, methods of conducting econometric analysis, consisting in the diagnosis of models.

Methods for developing forecasts based on econometric models.

3
 
  • • Numerical methods of computer modeling and analysis

Mastering and obtaining practical skills in algoritmization and programming methods of computational mathematics and numerical optimization methods.

Using modern computer modeling software in solving problems from various fields of human activity

3
 
  • • Data analysis in logistics

Development, solution and analysis of logistics problems based on economic and mathematical methods and models and computer technologies: construction of economic and mathematical models during logistics research.

Identification of the most significant quantitative relationships of the modeled logistics objects.

Mastering the techniques of mathematical formulation of individual connections and phenomena of logistics systems.

Acquisition of theoretical knowledge of basic economic and mathematical models and methods of transport logistics and inventory management

3
 
  • • Features of computer data analysis by the types of economic activity

Construction and application of optimization models and methods of applied statistics for the analysis of statistical data in various spheres of socio-economic development of the region on the basis of modern computer technologies.

Using modern information technologies to solve the problems of state regulation, forecasting and planning of state revenues and expenditures.

Evaluation of results, including financial and economic analysis of economic processes and production activities.

Using scientific achievements and development of proposals for improving professional activities in the field of finance, money circulation and credit.

Development of practical recommendations for the use of scientific research in the field of finance, money circulation and credit, planning and conducting experimental research

 3
 
  • • Mining technology

Introduction to the basic concepts and types of patterns identified by data mining, study of IAD methods, training in the use of software tools based on data mining technology for solving practical problems

 
  • • Methods and means of data visualization

Study of the main approaches and methods of graphical representation and data analysis.

Formation of practical skills and skills of working with tools for data visualization, including business intelligence systems.

6
 
  • • Discrete optimization

Mastering the statements and features of discrete programming problems.

Study modern methods for solving discrete programming problems.

Developing skills in using software products for implementing discrete programming algorithm.
3
 
  • • Mathematical methods of management in incomplete information conditions

Mastering methods, techniques, procedures, models and software tools for analyzing decisions in conditions of multivariance, multicriteria, uncertainty and risk, acquiring modeling skills for decision-making tasks in conditions of incomplete information

 
  • • Fundamentals of computer data analysis using R language

Systematic study of the R programming language.

Study of methods for solving the main applied problems of statistical data analysis by R language (data types in R, methods for creating loops, checking conditions, rules for writing functions, handling exceptional situations, writing and reading data from files and databases, working with graphs, exporting reports to pdf-file, etc., finding descriptive statistics).

3
 
  • • Analysis and forecasting in economics and finance using time series in Mathematica

Study of time series analysis methods based on higher-order statistics with implementation in the Mathematica package

The main competencies that

the graduate will acquire

  • • 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 explore models of complex systems and processes of nature;
    • develop intelligent decision support systems;
    • solve problems of computer modeling and optimization of systems and processes of nature, management of data mining processes, simulation modeling, statistical modeling and forecasting.

Options to continue education

(postgraduate specialties)

• 08.00.13 – Mathematical and Instrumental Methods of Economics
Graduate certificate MASTER’S DEGREE DIPLOMA

 

 

Industrial Automation

 

Faculty 

FMI

Specialty 

1-53 80 01 Industrial Automation
Profilization Analysis and management in digital economy systems
Language of study  English
Mode of study  Full-time
Term of study  1 year
Entrance exams for foreign citizens 

Curriculum

(with an indication of the main disciplines studied)

 
Names of master’s degree students’ activities, cycles of  disciplines, disciplines Number of credits

 

 

  • • Control Methods in Complex Systems
Within the framework of the discipline, methods for solving the main problems of control theory are studied. The issues related to the main methods of mathematical description and research of continuous and discrete automatic control systems are considered. The study of the discipline will allow you to develop the skills of studying specific systems, determining their main quality indicators, solving optimization problems, including using computer mathematics packages
3
 
  • • Methods of Computer-assisted Teaching
Machine learning methods are the basic technology of artificial intelligence. Within the framework of this discipline, theoretical and practical aspects of machine learning technologies, modern methods of restoring dependencies based on empirical data are studied. The issues of building and training models and evaluating their quality are considered. Skills for practical solutions to big data mining problems are also being developed in many financial, medical, commercial, and scientific applications.
3
 
  • • Neural Network Technology
Within the framework of the discipline, methods of mathematical modeling of artificial intelligence systems based on neural networks are studied. Students will get acquainted with the methods of design, training, analysis and practical application of neural networks in solving complex formalized engineering problems. The acquired practical skills will allow you to use modern software tools for building and training neural networks.
3
 
  • • Technologies of Digital Business Transformation

Digital transformation is the introduction of modern digital technologies into the business processes of an enterprise. It involves not only the use of modern hardware or software, but also fundamental changes in management approaches, corporate culture, and external communications. The discipline examines the methods of digital transformation caused by the introduction of Industry 4.0 technologies, in particular technologies based on the Internet of Things platform. The acquired practical skills will allow you to apply technologies, models, tools and digital business transformation; provide basic knowledge on the use of services to ensure cybersecurity in the context of digital business transformation

3
 
  • • Project Management in Automatization Sector

Project management is a recognized methodology for effective management, which is especially relevant in the context of the Industry 4.0 economy. While studying the discipline, students will get acquainted with the principles, tools and technologies that allow them to competently initiate, plan, execute, monitor and control the implementation of the plan, budget, requirements for the content and quality of the project, successfully complete the project, and effectively manage the project team. The acquired practical skills will allow you to design IT products; choose, justify and try on a project management methodology; use modern project management software systems.

3
 
  • • Knowledge Management Technologies and Intelligent Information Systems
Within the framework of this discipline, you will gain a systematic knowledge of the main models, methods, tools and languages used in the development of artificial intelligence systems. Get acquainted with the main methods of finding solutions used in artificial intelligence systems. You will develop analytical and practical skills that will allow you to navigate in the choice and use of methods, tools and languages in solving modern problems
3
 
  • • Contemporary Threats and Data Security Technologies

The purpose of the discipline is to gain knowledge on the issues of ensuring the protection of information in cyber-physical systems built on the Internet of Things platform. We consider systems that are currently being rapidly implemented in critical areas – medicine, transport, manufacturing, but, at the same time, carry a number of threats and vulnerabilities associated with the use of modern IT. The knowledge and skills gained in the course of studying the discipline will be useful in the development and use of smart systems and the analysis of the problems of their complex information protection.

3
 
  • • Fundamentals of Data Science

Within the framework of the discipline, methods of building and applying complex data processing systems are considered. Modern methods of data processing (receiving, storing, processing) and analysis using Python libraries for data representation and analysis, machine learning, and visualization are studied and systematized. The acquired knowledge and practical skills will allow you to use batch and distributed data technologies; mathematical methods and tools for statistical processing and data mining.

3
 
  • • Methods and Algorithms of Unstructured Data Distributed Processingta

The discipline is aimed at developing students ' professional competencies in the development and use of big data processing and analysis systems (Big Data). Methods of using Big Data distributed processing systems based on Map Reduce, Hadoop, Apache Spark technologies, methods of analyzing graph structures of social networks are considered. The acquired practical skills will allow you to develop decision-making automation systems; design and use distributed data processing systems and best practices in the development of competitive software products

3

The main competencies that

the graduate will acquire

  • • Will be able to make decisions based on the results of the application of scientific methods, assess the completeness of information in the course of professional activity, if necessary, fill in and synthesize missing information, work in conditions of uncertainty.
    • Will be able to carry out a critical analysis of problem situations based on a systematic approach, develop an action strategy.
    • Will be able to identify and implement the priorities of their own activities and ways to improve them based on self-esteem.
    • Will be able to apply the methods of scientific knowledge (analysis, comparison, systematization, abstraction, modeling, data validation, decision making, etc.) in independent research activities, generate and implement innovative ideas).
    • Will be able to apply methods of analysis and synthesis of optimal and adaptive control systems.
    • Will be able to apply modern technologies and tools in information systems.
    • Will be able to apply systems analysis methodology when designing complex systems.
Graduate certificate MASTER’S DEGREE DIPLOMA

 

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