Monday, 03 May 2021 20:43

Industrial Automation

 

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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