Industrial Internet of Things

This course will study the fundamental laws of nature: the law of conservation of momentum, the law of conservation of energy and the law of conservation of moment of momentum, and the fundamental concepts of statistical mechanics. Students will be able to solve a wide range of physical and engineering problems based on the assimilation of a small number of fundamental laws of nature. The main focus will be on the atomic structure of matter and the interaction between material objects. During the course, students learn to explain and predict the behavior of different systems, such as elementary particles, molecules, solid metals and galaxies. The course integrates the tasks of modeling physical processes based on Visual Python

The course aims to develop an understanding of the fundamentals of linear algebra and matrix theory. The subject of the discipline is the basic properties of matrices, including determinants, inverse matrices, matrix factorizations, eigenvalues, linear transformations, etc.

The academic discipline includes knowledge of analyzing functions represented in a variety of ways, and understanding the relationships between these various representations; understanding the meaning of the derivative in terms of a rate of change and local linear approximation, and using derivatives to solve a variety of problems. The course is aimed at forming students’ mathematical foundation for solving applied problems in their specialty.

The academic discipline acquaints students with important branches of calculus and its applications in computer science. During the educational process, students should become familiar with and be able to apply mathematical methods and tools (ordinary differential equations, series, double and triple integrals) to solve various applied problems. The discipline forms the ability to apply mathematical methods and tools (differential equations, series, double and triple integrals) to solve complex applied problems in their specialty.

The course aims to develop an understanding of the foundations of mathematics, combinatorics and graph theory. The subject of the discipline is basic mathematical principles such as proof, understanding of discrete objects; solving counting problems using various enumeration methods.

This discipline covers the basic concepts of computer science, including understanding how computers work, their history, hardware and software basics, algorithms, data structures, and an introduction to programming languages.

This course will study the concepts of electric and magnetic fields, which will make it possible to better understand the atomic structure of matter, the electrical and magnetic properties of solids, and the generation and propagation of electromagnetic waves. The course is aimed at studying the fundamental principles of electricity and magnetism, which underlies many modern technologies, from cell phones to medical imaging. The course integrates the tasks of modeling physical processes based on Visual Python.

“Control Systems 1” is an introductory course on the theory of automatic control. Due to the interdisciplinary nature of control systems, the ideas and concepts from this course are an integral part of systems in a wide range of applications, including electrical, mechanical, chemical, information and biomedical engineering, robotics and mechatronics, etc. The course introduces and integrates the basic concepts of linear automatic control systems. The exposition and demonstration of the basic concepts of feedback control systems, such as classical PID control, digital control, control in the state space and multivariable control, are discussed and illustrated.

Educational practice is an integral part of the student training program. The main content of the practice is the implementation of practical educational, educational and research, creative tasks that correspond to the nature of the future professional activity of students. The purpose of educational practice: the study and consolidation of theoretical and practical knowledge in the disciplines obtained in the learning process, the development of creative activity and initiative of students, their artistic and creative needs and aesthetic worldview.

This course teaches students the mathematical and conceptual analysis of electrical circuits. Students apply mathematical concepts such as differential equations, complex analysis, linear algebra, and probability theory to solve problems related to the design and analysis of electrical circuits. They develop a deep understanding of Kirchhoff’s laws, Thevenin’s and Norton’s theorems, and learn to analyze electrical circuits in the time and frequency domains using Laplace and Fourier transform methods. The course also includes the analysis of semiconductor devices such as diodes and transistors using differential and integral calculus equations. This course is a key component in the education of electrical engineers and requires a high level of mathematical preparation.

The course considers the basic methods of calculation of established and transient processes in electric circuits, their application to the most widespread in engineering practice electronic circuits, including amplifiers, rectifiers, stabilizers, triggers and other devices. Much attention is paid to properties and characteristics of semiconductor elements: diodes, bipolar and field transistors, thyristors, operational amplifiers, simple logic elements. Some chapters are devoted to the circuitry of digital devices.

The course examines basic, classical algorithms and data structures used in programming. The principles of construction and description of algorithms, the concepts of complexity and performance of algorithms, their main classes are considered.

Control Systems 2 discipline is an extension of the course ” Control Systems 1″. This course presents a fundamental approach to the design of control systems based on models. The concepts of modeling and identification of control objects will be studied in detail. Advanced control systems such as linear-quadratic controller, linear-quadratic Gaussian control, model prediction control, etc. will be studied in detail, analyzed and synthesized.

The course teaches the study of patterns of random phenomena and their properties, and use them for data analysis. As a result of studying this discipline, students will know the basic concepts of probability theory and mathematical statistics and their properties and be able to use probabilistic models for solving problems, work with random variables, calculate sample characteristics, evaluate the reliability of statistical data.

The course offers a broad understanding of a variety of signals (continuous and discrete), system properties (linear and non-linear), and tools for signal and system analysis, including Fourier and Laplace transforms. It also covers spectrum analysis, digital signal and system fundamentals, and filter design. This course provides a foundation for more advanced topics such as signal processing, communications systems, and systems control.

This course provides in details the principles and applications of digital electronics, including the fundamentals of Boolean algebra, the design and analysis of combinational and sequential logic circuits, and the operation and application of key digital elements such as decoders, multiplexers, counters, and registers. In addition, students are introduced to various memory circuits and the basics of programmable logic devices. The course also covers modern methods and technologies for designing digital systems, preparing students for work in the field of electronics and microprocessor technology.

The course provides students with a comprehensive understanding of the fundamental principles and mechanisms that drive modern operating systems. Students explore topics such as process management, memory management, file systems, and input/output management. They learn about the internal structures and algorithms used by operating systems to optimize resource allocation and scheduling, enabling efficient execution of applications. Throughout the course, students engage in practical exercises and projects that allow them to gain hands-on experience with real or simulated operating systems. By the end of the course, students develop a strong foundation in operating systems, equipping them with the skills to analyze and solve problems related to process management, memory management, file systems, and I/O operations, and enabling them to effectively develop software that interacts with the underlying operating system.

The discipline is aimed at developing knowledge and programming skills in assembly and C languages, and introduces students to the interface and structure of various families of microcontrollers. Mastering the course will allow students to start developing simple embedded systems based on various families of microcontrollers.

The course provides a broad understanding of the principles, architecture, and technologies behind computer networks. Students learn the basics of network communication, wired and wireless connection technologies, data transfer protocols, routing and switching, network security and network resource management. Emphasis is placed on understanding and using the OSI model and the TCP/IP model. This course prepares students for the design, management, and security of computer networks, as well as the foundation for more advanced networking topics and specializations.

Academic Writing is aimed to develop the ability in differentiating writing styles in English; skills in critical reading and writing strategies to foster critical thinking and prepare a critical analysis of а written piece; understanding of academic vocabulary, grammar and style; skills in writing well structured paragraphs; writing statements with arguments and proofs; and writing an academic essay.

The course is devoted to the design and development of advanced of embedded systems. The course is aimed at forming students’ understanding of embedded systems based on advanced and industrial microcontrollers, the specifics of their design and operation. As a result of the training, a basic system of knowledge and skills is formed that allows you to understand the principles of the functioning of complex embedded systems, choose tools and technologies for their development, evaluate the effectiveness of their use in various application areas, including IoT.

The course is designed to study the basic methods and tools required for the introduction of scientific research. The course also introduces students to the most popular search and scientometric databases of scientific articles, such as Web of Science, Scopus, ScienceDirect and others. During the course, students will become familiar with the tools for citing and searching for the required scientific information.

This course builds competencies in various industrial control devices and the networks that connect them. Topics include an overview of the various types of detection sensors and their interfacing. You will learn about various industrial wireless technologies, their standards and devices and experiment with modern industrial communication network protocols which include, Modbus, HART, Profibus with a considerable amount of time spent on Ethernet/IP networks. Fiber optic communications will also be covered in this course.

The course is designed to study programming, debugging and implementation of tasks. The principles of network technologies operation, access to local and remote network resources, programs using the C ++ language are analyzed.

The course focuses on enhancing students’ proficiency in C programming, including writing and executing code, utilizing data structures and algorithms, and problem-solving through coding. Additionally, students will learn how to design, implement and test programs, as well as how to debug and optimize code for improved performance.

The course is aimed at studying methods and algorithms for improving, analyzing and converting signals in digital form. Students learn the basic principles and theories of digital signal processing, including the Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), z-transform, and Laplace transform. The course also includes the study of digital filters, linear and non-linear systems, statistical signal processing, as well as the basics of digital modulation and coding. Students also gain practical skills in working with digital signal processing software (on MATLAB). This course is the foundation for more advanced signal processing courses such as image processing, speech processing, and communications

To give students theoretical knowledge in the field of metrology, standardization and certification. To form and develop practical skills and abilities in carrying out various measurements, including calculations of errors and the choice of adequate measuring instruments.

The course goal is to acquire the theoretical and practical knowledge in the field of artificial intelligence in general and in particular in the creating of algorithms capable of learning. The course examines the basic machine learning algorithms, various approaches and technologies for data analysis, their qualities, features and impact in various fields of science and technology. As an outcome of mastering the course, students will be able to apply machine learning methods to visualize their data, build graphs, and present the results qualitatively

The course provides students with an understanding of the possibilities of digital modeling technologies for industrial objects and processes to create duplicates. Having mastered this course, students will be able to develop and use the basic elements of digital twins, create digitalе modelsand processes.

The course provides an insight into various conceptual approaches to data storage and the underlying technologies that implement these approaches. The practical component is aimed at developing an understanding of the work of various classes of DBMS and their application scenarios.

This course focuses on the fundamentals of mechanical design and 3D solid modeling which lays the analytical foundation needed for the design, assembling, structural analysis and motion simulation of common machine elements. Practical sessions of the course teach students basic skills of computer-aided design (CAD) using Autodesk Fusion 360 software and exposes them to different manufacturing processes with major emphasis on additive and subtractive manufacturing technologies.