Courses taught in English for 2026-2027 Autumn Semester

Annotation of Course

In contrast to the classical statistics, data is considered as fixed and it’s distribution parameters are considered as random in Bayesian statistics. Inference about the parameters and other unknown values is updated applying information obtained from the data. Using Bayesian theorem statistical models are constructed. Prior distributions, data likelihood, posterior distributions and their approximation are studied for this. Bayesian methods are applied for the moedls of the classical statistics. Advantages and disadvantages of classical and Bayesian methods are compared; acquitance with the estimation of the hierarchical models is made. Suitability of the statistical models is tested applying information criteria. R software is used for practical application of Bayesian methods.

Aim of Course

To make acquaintance with the principles of the Bayesian inference in statistics and apply this knowledge in practice.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

Indicators of official statistics can be analysed in spatial cross section and time, therefore applied statistical methods are divided into methods of statistical analysis of independent statistical data and methods of time series analysis. Students are introduced with the linear and nonlinear modeling of indicators. The aspects of the economical indicators time series preadjustment nonobserved components estimation are introduced during the course. Theoretical knowledge is realised in practical exercises with statistical software R and others.

Aim of Course

Course aim – to provide students with knowledge of official statistics, methods for the analysis and modelling of statistical indicators, and to develop their ability to apply statistical methods to multivariate data and time series, assess indicator quality, perform forecasts, and critically interpret the obtained results.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -180

Annotation of Course

This course covers a range of statistical methods applied in the practice of official statistics. Students will explore both traditional and modern data sources (censuses, surveys, administrative registers, big data), fundamental concepts of sampling theory, and probabilistic as well as non-probabilistic sampling. Topics include complex sampling techniques-such as stratified and unequal probability sampling-and the use of ratio, regression, and calibrated estimators. The course also addresses practical challenges such as nonresponse, data editing, imputation, and validation. A strong focus is placed on small area estimation, indirect and model-based estimators. Additionally, the course examines the integration of independent samples and the combination of probability and non-probability data, as well as issues of confidentiality and dissemination of statistical results.

Aim of Course

To introduce students to advanced statistical methods used in official statistics for data collection and population parameter estimation, covering various data sources, sampling strategies, nonresponse and outlier treatment, small area estimation, and modern data sources such as administrative data and big data.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

Methods of solving systems of linear equations. Elements of vector algebra ana analytic geometry. Second-degree curves and quadric surfaces. Limit of a sequence. Limit of a function. Continuous and discontinuous functions. Derivative and its applications. Curve sketching. Functions of several variables. Extrema of functions of several variables.
Students must attend at least 51% of the lectures, at least 80% of the exercises.

Aim of Course

To acquaint students with methods of solving systems of linear equations. To expose range of applications of the differential calculus.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -10
Practical works -10
Laboratory works – 0
Consultations -4
Individual work -136

Annotation of Course

The course is devoted to the basics of the probability theory and mathematical statistics. The definitions for random event and probability are formulated, their main properties are presented. Random variables and their properties are studied, acquaintance with some discrete and continuous random distributions is made further. The second part of the course consists of the main principles of mathematical statistics. Methods for population parameter estimation and statistical hypothesis testing are overviewed. Each topic is illustrated by applications and solutions of practical tasks. Computer software application in statistics is introduced for students.
Students must attend at least 51% of the lectures, at least 60% of the exercises and at least 60% of the laboratory work during the scheduled time.

Aim of Course

Ai mis to provide students with an understanding of the probability theory, to develop their ability to solve problems of mathematical statistics and apply their knowledge for statistical data analysis.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -10
Practical works -6
Laboratory works – 6
Consultations -4
Individual work -134

Annotation of Course

The module covers the basic notions with elements of linear algebra and analytical geometry, the real numbers system, sequence, function, limit and derivative, as well as applications of the derivative in economics, engineering and other fields. Notions of the indefinite, the definite integrals, and their applications.
Students must attend at least 51% of the lectures, at least 80% of the exercises.

Aim of Course

To provide students with general knowledge of the basics of linear algebra, analytical geometry, differential and integral calculus. To teach students to apply the theoretical knowledge of this subject in the solution of practical problems and studying other subjects provided in the study program.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -60
Practical works -45
Laboratory works – 0
Consultations -6
Individual work -129
Part-time, distance learning studies:
Lectures -20
Practical works -16
Laboratory works – 0
Consultations -6
Individual work -198

Annotation of Course

In contrast to the classical statistics, data is considered as fixed and it’s distribution parameters are considered as random in Bayesian statistics. Inference about the parameters and other unknown values is updated applying information obtained from the data. Using Bayesian theorem statistical models are constructed. Prior distributions, data likelihood, posterior distributions and their approximation are studied for this. Bayesian methods are applied for the moedls of the classical statistics. Advantages and disadvantages of classical and Bayesian methods are compared; acquitance with the estimation of the hierarchical models is made. Suitability of the statistical models is tested applying information criteria. R software is used for practical application of Bayesian methods.

Aim of Course

To make acquaintance with the principles of the Bayesian inference in statistics and apply this knowledge in practice.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

Statistical data analysis has several main stages: data collection and their transformation, visualization, statistical modeling. These stages depend on the capabilities of the software and, of course, on the skill of using that equipment.
Software used in data analysis can be divided into several groups. A separate group consists of specialized programming languages.
R is a functional programming language specifically designed for statistical data analysis and data visualization. Using additional libraries, the number of which is constantly increasing, the basic capabilities of the language can be easily extended to use the latest statistical modeling, visualization and other data analysis techniques. According to the TIOBE index, R is among the top 20 programming languages and its position in the ranking has been increasing in recent years. This course is designed to consolidate basic programming skills with R, with a strong focus on the functional programming style. In addition, R is used in other data science specialization courses, so this course will prepare students for further studies.

Aim of Course

The purpose of this course – to introduce students to functional programming using the R programming language, to improve their programming skills with R, and to prepare them for the use of the R language in statistical data analysis.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

This course is aimed to equip the students with tools appropriate for the analysis of large collections of unstructured textual data. It gives an overview of both data structures applicable to the forementioned task and the main algorithms for analyzing the content and structure of written communication.

Aim of Course

To provide students with some knowledge and experience applicable to real-life problems which involve the analysis of textual data.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -180

Annotation of Course

In the first part of the course the main elements of combinatorics and operations of random events are presented. They are followed by a definition of the probability space, the classical definition of probability and theorems of probability summation and multiplication. The theorems of Bernoulli, Poisson, local and integral theorems of Muavre-Laplace are given. In addition, consideration of random variables distribution and their numerical characteristics, the central limit theorem make up a separate part. In the second part, empirical analogs of theoretical distribution characteristics and the main concepts of mathematical statistics are described, such as: population, sample, statistics, main properties of statistics. The problem of confidence interval construction is formulated and the basic concepts of the hypothesis testing are introduced. Teh R software is used for practicals.
Students must attend at least 51% of the lectures, at least 80% of the exercises and at least 80% of the laboratory work during the scheduled time.

Aim of Course

To master the basics of probability theory and get acquainted with the elements of mathematical statistics by making the statistical analysis with the help of R software.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 15
Consultations -4
Individual work -81
Part-time, distance learning studies:
Lectures -14
Practical works -6
Laboratory works – 6
Consultations -4
Individual work -130

Annotation of Course

An introduction to probability theory and mathematical statistics that emphasizes the probabilistic foundations required to understand probability models and statistical methods. Topics covered will include the probability axioms, basic combinatorics, discrete and continuous random variables, probability distributions, common families of probability distributions, statistical estimation, confidence intervals and statistical hypothesis testing.
Students must attend at least 51% of the lectures, at least 60% of the exercises and at least 60% of the laboratory work during the scheduled time.

Aim of Course

To provide students with a good understanding of the theory of probability, to help students develop the ability to solve problems using probability, to introduce students to some of the basic methods of statistics.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -6
Laboratory works – 2
Consultations -4
Individual work -140

Annotation of Course

The aim of this course is to introduce principles of algebra and mathematical analysis. The first part of this course covers theory and applications of linearity, including matrices and determinants, linear equations and systems of linear equations, Economic system balance model (Leontjev model) for optimal planning and solving linear programming problems. The second part of this course covers the basic concepts of mathematical analysis: a functions and their properties, limits, continuity, a comprehensive view of the theory and techniques of differential and integral calculus including differentiation rules, methods and applications, techniques of integration, improper and multiple integrals and its practical applications also ordinary differential equations.
Students must attend at least 51% of the lectures, at least 100% of the exercises.

Aim of Course

The aim of this course is to provide a sufficient understanding of basic linear algebra concepts, functions, limits and derivative terms, the integral and features as well as develop skills to address various economic and other problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -45
Practical works -45
Laboratory works – 0
Consultations -6
Individual work -144
Full-time weekend learning studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -6
Individual work -174
Part-time studies:
Lectures -18
Practical works -18
Laboratory works – 0
Consultations -6
Individual work -198

Annotation of Course

The aim of this course is to introduce principles of algebra and mathematical analysis. The first part of this course covers theory and applications of linearity, including matrices and determinants, linear equations and systems of linear equations, Economic system balance model (Leontjev model) for optimal planning and solving linear programming problems. The second part of this course covers the basic concepts of mathematical analysis: a functions and their properties, limits, continuity, a comprehensive view of the theory and techniques of differential and integral calculus including differentiation rules, methods and applications, techniques of integration.
Students must attend at least 51% of the lectures, at least 60% of the exercises.

Aim of Course

The aim of this course is to provide a sufficient understanding of basic linear algebra concepts, functions, limits and derivative terms, the integral and features as well as develop skills to address various economic and other problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -45
Practical works -45
Laboratory works – 0
Consultations -6
Individual work -144
Part-time studies:
Lectures -16
Practical works -16
Laboratory works – 0
Consultations -6
Individual work -202

Annotation of Course

The module expounds on the basic notions and theorems of probability theory, distribution laws of random variables and their numerical characteristics. Various problems of mathematical statistics and the ways of their solution are presented as well as empirical characteristics, and point and interval estimates of unknown parameters. Statistical hypotheses and their verification are considered as well as correlation and regression elements.
Students must attend at least 51% of the lectures, at least 80% of the exercises and at least 80% of the laboratory work during the scheduled time.

Aim of Course

To master the basics of probability theory and get to know the elements of mathematical statistics.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -10
Practical works -4
Laboratory works – 4
Consultations -20
Individual work -122
Part-time, distance learning studies:
Lectures -10
Practical works -4
Laboratory works – 4
Consultations -20
Individual work -122

Annotation of Course

Linear algebra and differential calculus are the foundation of modern mathematics and engineering. The concepts of linear algebra make it easy to explain and simplify calculations in engineering, physics, and other fields of science. Differential calculus plays an important role in modeling physical, technical or biological processes. The course will combine abstract thinking with calculations of varying complexity that students will use in further studies.
Students must attend at least 51% of the lectures, at least 80% of the exercises.

Aim of Course

To acquaint students with the basic concepts and methods of algebra, to introduce the possibilities of differential calculus application, to help students acquire mathematical thinking skills, including problem formulation, identification of possible methods for solution, calculation of results, and their proper interpretation.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -8
Laboratory works – 0
Consultations -20
Individual work -124
Part-time, distance learning studies:
Lectures -20
Practical works -24
Laboratory works – 0
Consultations -0
Individual work -116

Annotation of Course

In this course, students will learn a variety of data visualization and analysis techniques. The analysis will be carried out using Microsoft Excel and Origin software, while visualization will be done with programs such as Biorender, ConceptDraw, or by using AI tools. During the course students will explore how to turn different types of data into clear, compelling charts and graphics suitable for scientific publications, presentations, and theses. Throughout the course, you will not only create professional-looking figures, but also learn how to craft engaging stories from your data. In the final part, ethical aspects of data analysis will be discussed, including how to avoid data manipulation and communicate results responsibly.

Aim of Course

Aim of the course – introduce students to principles of data analysis and vizualization and cultivate students comunication and data presentation skills.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -50

Annotation of Course

This course introduces engineering enzymology, focusing on how enzymes are analyzed and adapted for practical use. It covers enzyme classification and nomenclature, structure-function relationships, and the fundamentals of Michaelis-Menten kinetics, including how to design kinetic experiments and interpret data. Students will learn enzyme inhibition and activation, two-substrate reaction kinetics, and the role of thermodynamics in enzyme-catalyzed processes. The course also addresses enzyme stability and inactivation, immobilization methods, and how mass transfer influences performance in enzymatic reactors. Finally, real industrial and medical applications are discussed to connect theory with biocatalyst and process design.
Students must attend at least 70 % of the scheduled practical sessions.

Aim of Course

The aim of this course is to introduce the fundamentals of engineering enzymology and develop students’ ability to analyze enzyme-catalyzed reactions (kinetics, inhibition, thermodynamics), and apply this knowledge to enzyme stability, immobilization, and basic reactor design for industrial and medical applications.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -4
Individual work -31

Annotation of Course

Due to the increasing amount of data worldwide – particularly biological Big Data – there is a growing demand for programming skill. Python is a programming language great for beginners that also has become especially popular for use in scientific fields. This course familiarizes students with basic principles of programming with Python programming language, with focus on biological data.
Students must attend at least 80% of the time scheduled practical lectures and at least 50 % of theoretical lectures.

Aim of Course

Introduce the principles of programming, the Python programming language, teach how to work with Python objects and packages and to use Python for biological data analysis.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -50

Annotation of Course

During the course, the methods and equipment of water purification are reviewed. Sterile filtration for preparation of sterile solutions is analysed in detail. A lot of attention is dedicated for endoproducts isolation. A detailed presentation of process automation and management is made (sensors, pumps, valves). Liofilization process and equipment are briefly discussed. During the course, students learn to create an equipment scheme for exclusion and purification of a defined biotechnological product and learn to perform comparative analysis of biotechnological equipment.
Students must attend at least 70 % of the scheduled laboratory work. Students are required to complete all scheduled laboratory work.

Aim of Course

To introduce the main biotechnology processes and operation principles of the most important apparatuses.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -4
Individual work -31

Annotation of Course

Microbiological technology principles. Fermentation technology: raw material, bioagents, bioreactors, process management and control. Basic product extraction methods and equipments. Producing technologies of main industrial products (ethanol, amino acids, organic acids, enzymes, polysaccharides, microbial proteins).
The basic knowledge of biotechnological process’s mathematical modelling and optimization.
Students must attend at least 70 % of the scheduled practical sessions. Students are required to complete all scheduled laboratory work.

Aim of Course

Introduction of microbial technology’s principles, methods and main product’s production technology, mathematical modeling and optimization of biotechnological process’s.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 30
Consultations -4
Individual work -96

Annotation of Course

The diversity of microorganisms and their distribution in nature. Eukaryotic and prokaryotic cells, comparison of structure.
Archaebacteria and Eubacteria. Systematics of microorganisms. Propagation and growth conditions of microorganisms, methods for their cultivation, physiology of icroorganisms. Metabolism of microorganisms, biosynthesis. Ecology, symbiosis and evolution of microorganisms. Application of microorganisms in industrial microbiology.
Students must attend at least 70 % of the scheduled practical sessions and at least 50 % of theoretical lectures. Students are required to complete all scheduled laboratory work.

Aim of Course

To indoctrinate with fundamentals of of microbiology: scope of microbiology, characracteristics of prokaryotic and eukaryotic microorganisms, growth, culturing and metabolism of bacteria, microbial genetics, main reseach methods, classification of microorganisms; ecology and application of microbes in industry.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 30
Consultations -4
Individual work -81

Annotation of Course

Tissue engineering-interdisciplinary science connecting different fundamental and applied scientific disciplines (cell biology, biocheistry, material science, nanotechnology, medicine, etc.). Organization of cells into the higher order structures. Components of extracellular matrix. Stem cells (embryonic, adult, cancer, induced pluripotent). Cell and tissue banking. Extracellular matrix substitutes (biological, semibiological, synthetic). Designing 3D microenvironment in vitro. Microscale patterning of cells and their environment. Tissue scaffolds. Prototyping, organ printing. Bioreactors.

Aim of Course

To familiarize students with principles of tissue engineering and present up to date information about modern technologies

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -0
Individual work -100

Annotation of Course

This course will focus on the possibilities of recombinant DNA technology in biomedical field with emphasis on the technological and technical aspects of biotech drugs.
Students must attend at least 80% of the time scheduled practical lectures.
Students must attend 100% of the time scheduled laboratory work.

Aim of Course

To introduce with the most recent scientific and industrial achievements in the pharmaceutical biotechnology field.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 30
Consultations -4
Individual work -81

Annotation of Course

Biomolecules and cells. Major compounds of living organisms: proteins, nucleic acids, lipids, carbohydrates, mineral compounds, and water. Their structure, properties, and functions. Major metabolic and energy pathways.
Students must attend at least 70 % of the scheduled practical sessions. Students are required to complete all scheduled laboratory work.

Aim of Course

To introduce to the major compounds of the living organisms, their characteristics and metabolism.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 30
Consultations -6
Individual work -144

Annotation of Course

Classes of organic compounds and IUPAC system of nomenclature. Alkanes and organohalogen compounds. Alkenes and alkynes. Aromatic compounds. Alcohols and phenols. Ethers. Aldehydes. Ketones. Carboxylic acids and derivatives of carboxylic acids. Amines. Organoelement compounds. Mechanisms of organic reactions.
Students must attend at least 70 % of the scheduled practical sessions and at least 50 % of theoretical lectures. Students are required to complete all scheduled laboratory work.

Aim of Course

Aware of the basis of organic chemistry, basic organic compound classes, their characteristics, evolution and practical use of organic compounds.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 30
Consultations -6
Individual work -144

Annotation of Course

The Bioethics course addresses ethical issues in research, biotechnology, bioengineering and biomedicine, bioethical approaches to the environment and engineering solutions. Students are introduced to the laws and directives governing the use of cells, tissues, organs and laboratory animals in scientific experiments and the participation of humans in clinical trials. Students gain knowledge of the ethical norms and legal regulations of genetic engineering, organ and tissue cloning, transplantation, body reconstruction, birth control and euthanasia.
Students must attend at least 70 % of the scheduled practical sessions.

Aim of Course

To provide knowledge on ethical issues in research, life and death, biotechnology and environmental and ethical legislation.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -2
Individual work -33

Annotation of Course

Bioreactor design and analysis, batch reactor, plug flow and packed bed bioreactors. Imperfect mixing. Biological waste water treatment. Separation of insoluble particles. Filtration. Chromatography.
Students must attend at least 70 % of the scheduled practical sessions.

Aim of Course

Numerical methods applied to biotechnology engineering problems. Use of computational tools such as MATHCAD and EXCEL to solve biotechnology engineering problems. Statistical methods.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -31

Annotation of Course

The course examines the theoretical and practical aspects of conducting biomedical research. During the course, students will be introduced to the regulation of biomedical research, ethical issues and data security. They will learn to work according to good clinical practice and the highest quality standards. Students will acquire knowledge about translational medicine and standard diagnostic methods used to confirm diseases. During practical exercises, students will learn how to plan research with human biological material and health information; write bioethics protocols and quality assurance documents.

Aim of Course

To provide knowledge about planning, execution and regulation of biomedical research and gain competence working with human biological material and health information.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

This course introduces students to the principles, technologies and good manufacturing practices for the production of dosage forms and drug delivery systems. The course introduces the application of pharmaceutical and biopharmaceutical principles, product design, formulation, manufacturing, compounding and clinical application of different dosage forms in patient care. It also covers the regulations and standards governing the manufacture and formulation of medicines.
Students must attend at least 70 % of the scheduled practical sessions. Students are required to complete all scheduled laboratory work.

Aim of Course

To provide students with the pharmaceutical dosage forms manufacturing industry: technological processes, equipment, manufacturing specifications.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 30
Consultations -4
Individual work -81

Annotation of Course

It is a set of theoretical knowledge and practical skills that help understand forecasting methods of thermodynamic systems, the formation of solutions and their properties, water chemistry, oxidation-reduction processes, which are taking place in electrochemical devices, electrolysis, and corrosion of metals, which are very important in rapidly changing in operational situations in the field of mechanical engineering. Understanding of the studied chemical processes or phenomena and the ability to manage them will contribute to effective work in this field of engineering.
Students must attend at least 70 % of the scheduled laboratory work sessions and at least 50 % of theoretical lectures. Students are required to complete all scheduled laboratory work.

Aim of Course

To enable students to seek basic chemical knowledge in shaping their concept of their application in practical and professional activities.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -4
Individual work -111
Part-time studies:
Lectures -20
Practical works -0
Laboratory works – 12
Consultations -4
Individual work -124
Part-time, distance learning studies:
Lectures -20
Practical works -10
Laboratory works – 10
Consultations -0
Individual work -120

Annotation of Course

Students must attend at least 70 % of the scheduled practical sessions. Students are required to complete all scheduled laboratory work.

Aim of Course

To give the underlying knowledge about the fundamentals of immunology: the components and functions of the immune system; molecular mechanisms of the immune response; the roles and importance of the immune system in different human diseases.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 30
Consultations -4
Individual work -81

Annotation of Course

The course presents general information about studying at the university, drafting of writing papers, searching for information sources. Introduction to bioengineering science, interdisciplinarity of this discipline. There are analyzed different branches of biotechnology, production processes and production.
Students must attend at least 80% of the time scheduled practical lectures and at least 50 % of theoretical lectures.

Aim of Course

To provide general knowledge of studies at the university, bioengineering. To introduce biotechnology and their specificities.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 0
Consultations -2
Individual work -48

Annotation of Course

Introduction to the course studies. Atomic structure and chemical bounds. Dissolution of materials and formation of solutions. Expression of solution concentration and methods for its calculation. Chemical kinetics and chemical equilibrium. Catalysis. Properties of nonelectrolytes and electrolytes solution. Electrolytical dissociation. Degree and constant of dissociation. Water dissocesiation, pH and pOH. Hydrolysis of salts and its application. Oxydation-reduction processes. Water hardnes and its softening. Electrochemical processes within galvanic cells, electrolysis and corrosion of metals, the methods of protection of the metals against corrosion.
Students must attend 100% of the time scheduled laboratory work, at least 80% of the time scheduled practical lectures and at least 50 % of theoretical lectures..

Aim of Course

Impart fundamental knowledge and develop abilities necessary for a job in biotechnology sphere.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 30
Consultations -6
Individual work -79

Annotation of Course

The Diagnostic Nanobiotechnology course deals with the application of nanotechnologies in diagnostic biotechnology. Nanomaterials, principles of biological recognition and biopolymer interactions are analyzed. The application of nanotechnology to the visualization of biomarkers and the analysis of metabolites and xenobiotics are discussed.

Aim of Course

Introduce the principles of nanotechnologies and their applications in biotechnological diagnostics. Provide the latest knowledge on nanomaterials, biomarkers visualization principles and nanobiosensors. Analyse the modern diagnostic methods of nanobiotechnology and possibilities of their practical applications.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

Cell biology module provides an overview of the main hypotheses of origin of life and also the main concepts of evolution and functioning of viruses, single cell and multicellular organisms. There are presented the major model organisms and their contribution to cell biology, bioengineering and biotechnology. Different methods of cell biology are discussed as well as new technologies (RNAi, CRISPR), and practical use of retro/lentiviruses, transgenic and knockout animal technologies. The module presents analysis of the main structural elements of the cell/organelles (plasma membrane, endoplasmic reticulum, Golgi apparatus, the nucleus, mitochondria, lysosomes, cytoskeleton), their physico-chemical composition, functionality and their crosstalk and changes in diseases. It is also explains the main cell physiological mechanisms involved in ion transport, transport of biomolecules, nerve impulse, cell cycle, energy processes, cell death, photosynthesis and mechanisms of carcinogenesis.

Aim of Course

The goal is to provide students with basic and most recent scientific knowledge about the evolution of prokaryotic and eukaryotic cell, their structural elements, function and overview the major cellular processes including cell cycle, cell death, signal transduction and introduce to the main methods and model organisms used in molecular and cellular biology.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -0
Individual work -115

Annotation of Course

The gene engineering course gives theoretical and practical basis of recombinant DNA construction and analysis, including: gene cloning, selection of vector system, prokariotic and eukaryotic gene and genome analysis; transcriptomic analysis of DNA expression; detection of recombinant products; application of DNA technology in medicine, biotechnology, industry and agriculture.
Students must attend at least 70 % of the scheduled laboratory work sessions. Students are required to complete all scheduled laboratory work.

Aim of Course

The main purpose of the course is introduction to the basic technologies of recombinant DNA construction and analysis; elucidation of the significance of gene engineering and development of methods in modern biotechnology science.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 30
Consultations -0
Individual work -100

Annotation of Course

Nanomaterials are definied as materials having unique physical, chemical, mechanical and biological properties at nanoscale. This course covers different classes of nanomaterials, their physical and chemical properties, characterization and possibilities of applications.

Aim of Course

Provide the intersdisciplinary knowledge on the newest scientific achievements and developing methods in the field of nanomaterial designing and their application.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -0
Individual work -115

Annotation of Course

It is a set of theoretical knowledge and practical skills that help understand forecasting methods of thermodynamic systems, the formation of solutions and their properties, water chemistry, oxidation-reduction processes, which are taking place in electrochemical devices, electrolysis, and corrosion of metals, which are very important in rapidly changing in operational situations in the field of aeronautical engineering. Understanding of the studied chemical processes or phenomena and the ability to manage them will contribute to effective work in this field of engineering.
Students must attend at least 70 % of the scheduled laboratory work sessions and at least 50 % of theoretical lectures. Students are required to complete all scheduled laboratory work.

Aim of Course

To provide the students with chemistry knowledge in the studies of general and special courses and practical activities.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -2
Individual work -33

Annotation of Course

It is a set of theoretical knowledge and practical skills that help to understand thermodynamic and kinetic methods of predicting systems, the formation of solutions and their properties, oxidation-reduction processes occurring in electrochemical devices, electrolysis and corrosion of metals, which are very important in the field of environmental engineering. It is important to recognize in which field of civil engineering what chemical processes or phenomena take place and how to use them correctly and usefully for effective work in this field.
Students must attend at least 80 % of the time scheduled laboratory work and at least 50 % of theoretical lectures.

Aim of Course

To enable students to seek basic chemical knowledge in shaping their concept of their application in practical and professional activities.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -2
Individual work -33
Part-time, distance learning studies:
Lectures -8
Practical works -0
Laboratory works – 4
Consultations -4
Individual work -64

Annotation of Course

It is a set of theoretical knowledge and practical skills that help to understand thermodynamic and kinetic methods of predicting systems, the formation of solutions and their properties, oxidation-reduction processes occurring in electrochemical devices, electrolysis and corrosion of metals, which are very important in the field of transport engineering. It is important to recognize in which field of transport engineering what chemical processes or phenomena take place and how to use them correctly and usefully for effective work in this field.
Students must attend at least 70 % of the scheduled laboratory works and at least 50 % of theoretical lectures. Students are required to complete all scheduled laboratory work.

Aim of Course

To enable students to seek basic chemical knowledges in shaping their concept of their application in practical and professional activities.
Students must attend at least 70 % of the scheduled practical sessions. Students are required to complete all scheduled laboratory work.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -2
Individual work -33
Part-time studies:
Lectures -10
Practical works -0
Laboratory works – 6
Consultations -2
Individual work -62

Annotation of Course

The Molecular and Cell Biology course provides knowledge about cell as a basic functional unit of living organisms, cell processes and their control, complexity of biological systems. The module explains postulates of cell theory, prokaryotes and eukaryotes differences, fundamentals of genome functioning emphasizing gene expression regulation in eukaryotes. The course provides theoretical and practical knowledge about cells endomembranous system and cytoskeleton, the functioning and origin of the organelles and their interrelationships, basics of proteins sorting and transport, molecular chaperone and ubiquitin/proteosome system functioning; examines the issues of cellular-matrix interactions and matrix structure, intercellular and intracellular signalling; regulation of eukaryotic cell cycle. The course provides practical skills of eukaryotic cells cultivation and experimental manipulations.
Students must attend at least 70 % of the scheduled practical sessions. Students are required to complete all scheduled laboratory work.

Aim of Course

The goal is to provide knowledge about cell structure and functioning, structure of the genome, its functioning and regulation, basics of compounds traffic in the cell, signalling pathways and their regulation, cell cycle and its control, cells interactions; introducing into some modern techniques used in cell biology.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 45
Consultations -6
Individual work -129

Annotation of Course

Introduction to Project Management. Project Management Basics. Initiating Processes. Planning Processes. Project Scope Planning. Project Time Planning. Project Cost Planning. Project Quality Planning. Project Human Resources Planning. Project Communication Planning. Project Risk Planning. Project Procurement Planning. Project Executing Processes. Project Monitoring and Controlling Processes. Closing Processes.
Students must attend at least 80% of the time scheduled practical lectures.

Aim of Course

To prepare project managers, practice on project management tools and methods.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -2
Individual work -33
Part-time, distance learning studies:
Lectures -12
Practical works -6
Laboratory works – 0
Consultations -3
Individual work -59

Annotation of Course

The Operating Systems course is designed to provide a general understanding of the structure and basic functions of an operating system. The course includes the concept of process, process scheduling algorithms and their comparison, memory management methods are compared and examined, file system and file system implementation are discussed, file system management and optimization are discussed. Case studies will be used to illustrate and reinforce fundamental concepts.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.

Aim of Course

To get knowledge about functions of OS and to get skils in using command files.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -14
Practical works -10
Laboratory works – 0
Consultations -4
Individual work -132

Annotation of Course

Students remember the principles of software project management, best practices of software systems design and implementation, research methods, requirements for data analysis and apply all these knowledge for development of individual project. During the semester different phases of project development are analyzed (project idea generation, project exclusivity, requirement and architecture specification, project success evaluation, analysis of project results, etc.). It is also a strong focus on proper project documentation and presentation for different type of audience.
Students must attend at least 60% of the time scheduled practical lectures.

Aim of Course

To provide hands-on experience in self-planning and implementation of software and/or research projects in Information technology field.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -0
Practical works -45
Laboratory works – 0
Consultations -4
Individual work -111
Part-time, distance learning studies:
Lectures -0
Practical works -22
Laboratory works – 0
Consultations -4
Individual work -134

Annotation of Course

This course serves an introduction to procedural programming using the C++ programming language. Participants will gain a solid understanding of fundamental programming concepts. The curriculum covers key topics such as variables, control flow, functions, arrays, pointers, file handling, and dynamic memory allocation. Students will also explore the principles of error handling, preprocessor directives, and some coding practices. By the end of the course, students will be ready to study principals of objected-oriented programming.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.

Aim of Course

To acquaint students with potentials of procedural programming, fundamental data structures of programming language and general algorithms for their processing. To learn students writing, validating and documenting procedural code.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -14
Laboratory works – 0
Consultations -4
Individual work -134
Part-time, distance learning studies:
Lectures -8
Practical works -14
Laboratory works – 0
Consultations -4
Individual work -134

Annotation of Course

In this study subject students are introduced to robotized process automation (RPA), analyzes how to select processes, suitable for automation, how to evaluate its possible benefits, implementation and maintenance resources, possible risks of RPA application. Students get know possible solutions and technologies used for RPA application and in class uses UiPath, UiVision, Python or othertechnologies for robotized process automation.
Students must attend at least 60% of the time scheduled practical and laboratory work.

Aim of Course

Provide students knowledge on robotized process automation and ability to design, develop and test its qualitya and payoff.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 15
Consultations -2
Individual work -33
Part-time, distance learning studies:
Lectures -6
Practical works -6
Laboratory works – 6
Consultations -2
Individual work -60

Annotation of Course

Introduction to enterprise information and technology management based on process management methodology. An overview of information and technology business specification, organizational structure, process management methodology. The course provides an overview of ITIL v.4. ITIL processes and functions are initated for practical modeling and analysis.
Students must attend at least 60% of the time scheduled practical lectures.

Aim of Course

To provide knowledge and abilities, needed for management of enterprise used infromation and technologies, its risk evalaution and governance to regulation requirements.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -10
Practical works -6
Laboratory works – 0
Consultations -2
Individual work -142

Annotation of Course

This course provides basic knowledge of procedural programming. It examines programming languages, program execution and programming environments, procedural programming paradigms, including basic data types, expressions, conditions and loop operators, working with files and arrays. The work is done in Python syntax.
Students must attend at least 60% of the exercises and at least half of the theoretical lectures during the scheduled time.

Aim of Course

To introduce students to the possibilities of procedural programming, the internal data structures of a programming language, and simple algorithms. During the course, students will learn how to write procedural programs, test them, and document them.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -140

Annotation of Course

To provide knowledge about the 3D object models and web animation applications. Presents the main principles of the Internet 3D graphics. Discussed in detail the international standard X3D. Provided general and specific methods for creating 3D scenes. Interactive 3D virtual space visualization techniques.
Students must attend at least 80% of the time scheduled practical lectures.

Aim of Course

Practice will be able to create interactive 3D graphics models for Internet applications in WebGL library and other graphics engines.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -2
Individual work -33
Part-time studies:
Lectures -4
Practical works -8
Laboratory works – 0
Consultations -2
Individual work -66

Annotation of Course

Current progress of technology enables almost everybody to have a mobile phone. Very often, the phone is used not only for its primary function, but for various other tasks, essentially it becomes multifunctional mobile device. Graphical possibilities of these devices and programming is discussed in the module.
Students must attend at least 80% of the time scheduled practical lectures.

Aim of Course

Having finished the course, the students will be able to:
1) Work with programming environments for the mobile devices;
2) Create small graphical programs, to show various abilities of mobile devices;
3) Manage dataflow to/from mobile device, have practical experience in working in client-server environment;
4) Work independently.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -45
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -4
Practical works -12
Laboratory works – 0
Consultations -4
Individual work -140

Annotation of Course

This course aims to provide students with the opportunity to acquire and apply an understanding of the key principles and production methodologies involved in creating small-scale creative projects, specifically in the context of animation.
Students must attend at least 60% of the time scheduled theoretical lectures. Students must attend at least 80% of the time scheduled practical lectures. Students must attend at least 80% of the scheduled laboratory work time.

Aim of Course

This course provides students with the opportunity to acquire and implement an understanding of the key processes through the practical experience of animation and the post-production processes.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -45
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -81
Part-time studies:
Lectures -12
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -136

Annotation of Course

Theoretical and practical aspects of computer game design are analyzed during theory lectures: game ideas and narrative planning; game levels, their characters and other game assets design; definition of game rules, core and meta mechanics; game resource balancing; design of diegetic and non-diegetic game user interfaces, user interface design in different gaming platforms (including AR and VR games). During the lectures, students are also introduced to different player types, best practices for keeping them immersed into the game. During the laboratory and practice works, students individually deconstruct a computer game having a narrative, while working in a team they design the concept of the new narrative based video game: a game design document is filled out, graphic resources are created, game levels are designed, and the presentation of the game idea is prepared.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.

Aim of Course

After this course students should be able to:
– select and apply effective methods for computer game planning, design and documentation;
– apply principles of aesthetics and computer design for the development of computer game character, environemt and gameassets;
– select the appropriate game mechanics, define the economy of game resources, control the complexity of the game levels.
– create the level design of narrative based video games
– understand the influence of the player’s psychology in the process of creating computer games, use this knowledge inpractice
– effectively and attractively present the idea of a new computer game

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -140

Annotation of Course

This course deals with principles of geographical information system (GIS) development elements, geographical information infrastructure, raster and vectorial analysis methods. It also presents Marker-Based AR and marker-less AR technologies highlighting location-based augmented reality pecularities. Geo AR app development principles are also introduced in the course.
Students must attend at least 80% of the time scheduled practical lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

” to understand and apply basic raster and vectorial analysis methods,
” to know standards of geographical information infrastructure,
” to understand Location-based Augmented Reality Technology and its applications.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -4
Laboratory works – 4
Consultations -4
Individual work -140

Annotation of Course

Unity game engine. Graphics creation tools for computer games. Data structures and algorithms for game programming. Developing strategies. Import of 3D models, pictures and audio recordings. Game physics. 3D and 2D animation. Game scene lighting. Visual effects. Graphical user interface. Configuring a Unity game for different platforms.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

Basic knowledge of game design theory and ability to use Unity game engine. After this course students will be able to:
” create game strategies;
” use different mechanics in the game;
” apply 3D models, pictures, sounds for game development;
” create animated game elements;
” create computer games.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -12
Practical works -8
Laboratory works – 8
Consultations -6
Individual work -126

Annotation of Course

During theoretical lectures, the students are introduced to a client – server architecture, the principles of generating HTML pages, and operating principles of server software, as well as its installation on different operating systems. The open-source PHP scripting language is studying for creating web applications. For this purpose Apache server software is used and a free MySQL database management system, which is currently widely used in the development of Internet applications.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

Basic knowledge of principles and technologies of web applications based on client – server architecture.
After completion of this course students will be able to:
1. Install and launch server software
2. create Internet applications
3. develop application using database management systems

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -4
Laboratory works – 4
Consultations -4
Individual work -140

Annotation of Course

During the course, participants will be introduced to the fundamental principles of software system development, the methodology of software project management, and will learn how to create a specific software project plan using tools such as MS Project or similar software. The course will cover essential concepts of requirements engineering, provide an overview of requirements gathering, analysis, and specification methods, as well as the Unified Modeling Language (UML). Participants will also be familiarized with software design methods, software maintenance and support techniques, configuration management, and the basic principles of user interface design. The course will present the fundamentals of software testing methods and tools, which will help in creating a testing plan for the developed software and documenting the test results. Participants will learn how to create documentation for the software being developed, including project plans, requirements specification documents, design documents, testing plans, user guides, and administration guides.
Students must attend at least 80% of the time scheduled practical lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

To understand the software development process and to be able to apply the acquired knowledge to the development and dokumentation of the specific software project increasing the teamwork skills.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -4
Laboratory works – 4
Consultations -4
Individual work -140

Annotation of Course

This course deals with essential internet technology components: markup languages, style sheets, DOM script programming and content management systems.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

Students will have knowledge and comprehesision concerning main web design and development principles, essential elements of programming technologies

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -4
Laboratory works – 8
Consultations -4
Individual work -136

Annotation of Course

During theoretical lectures students are introduced with graphic tools for artistic expression, coloring fundamentals, compositional principals and possibilities of their usage. During practical training it’s taught to create compositions in the plain, using various sizes and forms of spots, dots, lines, and factures. It’s taught to abstract, to create colligated compositions of coloring spots, artistic font compositions. Students are promoted creativity, educated aesthetic sansation. Students are taught to use independently tools for artistic expression by creating specially selected tasks (individual tasks by the themes)
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.

Aim of Course

Identify and apply the main compositional principals, be capable to create compositions using graphic tools, principals of coloring harmony, be able to evaluate and choose suitable expression tools, considering to tasks’ particularity.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 0
Consultations -2
Individual work -48
Part-time studies:
Lectures -4
Practical works -4
Laboratory works – 0
Consultations -2
Individual work -70

Annotation of Course

Understanding operating system (OS), architecture and purpose. Threads, processes execution planning, memory management and file systems. Administration of OS and automation of tasks. Main OS: MS Windows, Unix, Mac OS X.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.

Aim of Course

To get knowledge about functions of OS and to get skills in using system commands and system administration.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -140

Annotation of Course

“Media production” provides students with a general knowledge on audiovisual arts industry. Module introduces all stages of film production – development, production, editing and postproduction. Students gain theoretical and practical
knowledge on using audio and video equipment, develop practical video editing, scriptwriting skills.
Students must attend at least 80% of the time scheduled practical lectures and at least half of the lectures at the scheduled times.

Aim of Course

This course will provide students with such knowledge:
1) Terminology and definitions used in audiovisualy industry;
2) Screenwriting for short films: structure & dramaturgy; Industry standart script formatting;
3) Audio and video equipment – theoretical knowledge ant practical skills;
4) Video editing – basics of using Adobe Premiere software;
5) Film crew: Roles and responsibilities;
6) Various media forms (advertising, music video clips, etc.) and their application.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -140

Annotation of Course

.

Aim of Course

.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -35

Annotation of Course

This course provides a thorough introduction to computer graphics, the primary role of which is to present digital content on a computer screen in a human understandable form. This course introduces students to the tools and technologies of raster and vector (2D and 3D) graphics. It covers topics specific to an introductory course: image creation sequence, color models, 3D object creation, animation and texturing, mathematical foundations of computer graphics, coordinate systems, projection classification, shading models, real-time graphics pipeline, interactive graphics programming technologies.
Students are required to attend at least 80% of the practical and laboratory classes at the scheduled time during the semester. Mandatory minimum attendance of module lectures – 50%.

Aim of Course

To introduce with the principles of image formation, color theory, modern raster and vector (2D and 3D) graphics technologies.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -2
Individual work -33
Part-time, distance learning studies:
Lectures -8
Practical works -8
Laboratory works – 0
Consultations -2
Individual work -62

Annotation of Course

Sketch drawing, means of dimensivining, material marking in drawings. Demountable and non-demountable joints, types of srews, viewing and marking of screws, screw fastening elements. Assemblies drawings and their drawing order. Understanding and detailing of assembly drawings. Specification. Viewing of springs, gears, gear and chain trains. Kinematics diagrams. Marking of surface machining types in the drawings. Tolerances and fits.
Students are required to attend at least 80% of the practical and laboratory classes at the scheduled time during the semester. Mandatory minimum attendance of module lectures – 50%.

Aim of Course

Sketch drawing, means of dimensivining, material marking in drawings. Demountable and non-demountable joints, types of srews, viewing and marking of screws, screw fastening elements. Assemblies drawings and their drawing order. Understanding and detailing of assembly drawings. Specification. Viewing of springs, gears, gear and chain trains. Kinematics diagrams. Marking of surface machining types in the drawings. Tolerances and fits.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 15
Consultations -2
Individual work -33
Part-time studies:
Lectures -6
Practical works -6
Laboratory works – 6
Consultations -2
Individual work -60
Part-time, distance learning studies:
Lectures -10
Practical works -10
Laboratory works – 10
Consultations -0
Individual work -50

Annotation of Course

The concept of computer graphics (CG). CG image creation sequence. Colour models and understanding of colours. CG software. Raster and vector graphics systems. Computer animation. Three-dimensional CG development systems. Creating and texturing 3D objects. Basics of image processing technology. Mathematical foundations of CG. Coordinate systems. Two-dimensional and three-dimensional transformations. Classification of projections. Shading models. Interactive 3D graphics.

Aim of Course

Introduce with the principles of image formation, color theory, modern technologies of raster, two-dimensional and three-dimensional vector graphics

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -0
Practical works -15
Laboratory works – 15
Consultations -0
Individual work -50

Annotation of Course

This cours presents a captivating exploration of Applied Engineering Graphics within the context of the environmental engineering major. This cours showcases the relevance and application of engineering graphics focusing on key topics such as projection drawing, image placement in drawings, simple and complex cuts, construction drawing. Furthermore, this cours delves into the importance of accurately representing building plans and facades, shedding light on the techniques involved in their drawing. It emphasizes how these graphics play a vital role in the visualization and communication of sustainable solutions in environmental engineering projects. This cours also provides an insightful overview of computer-aided design (CAD) systems and their unique features when applied to the field of construction. It highlights how CAD tools enhance efficiency, precision, and innovation in the design and implementation of environmental engineering projects. Moreover, this cours highlights the significance of CAD data management and adherence to CAD standards. It discusses the importance of organized data practices to ensure the seamless integration of engineering graphics within the broader environmental engineering context.
Students are required to attend at least 80% of the practical and laboratory classes at the scheduled time during the semester.

Aim of Course

To acquaint with the main requirements for the engineering graphics documentation, using automated computer design systems. The student will be able to read and understand the drawings of building constructions. To provide the knowledge to be able to apply engineering graphic methods in the design of structures, to be able to understand the design document correctly, to be able to depict drawings of parts of buildings and constructions using modern automated design systems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -0
Practical works -15
Laboratory works – 30
Consultations -2
Individual work -33
Part-time studies:
Lectures -0
Practical works -6
Laboratory works – 4
Consultations -8
Individual work -62

Annotation of Course

Module presents basics of the projection drawing. It introduces how to create mechanical drawings, teaches to read and perform assembly drawings, presents detailed information about the development of the details working drawings; shows the application of computer systems for mechanical drawing.
Students are required to attend at least 80% of the practical and laboratory classes at the scheduled time during the semester. Mandatory minimum attendance of module lectures – 50%.

Aim of Course

To present general principles of the projection drawing and their application to mechanical drawings; to develop skills to read and perform assembly drawings using computer graphic systems and drawing standards.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -45
Laboratory works – 0
Consultations -4
Individual work -96
Part-time studies:
Lectures -6
Practical works -16
Laboratory works – 0
Consultations -4
Individual work -134

Annotation of Course

While studying the subject, the concept of engineering graphics was presented during the semester. The subject provides knowledge on how to use graphic tools in the preparation of engineering documentation, will be able to find and use suitable standards, and will understand how to apply appropriate information technologies. The combination of theory and practice will help to understand the possibilities of applying CAD systems in the preparation of technical drawings, paying attention to the requirements of the standards. The subject will not only introduce the basic methods of representing spatial objects on a plane and in space. Still, it will also encourage creative thinking when making appropriate decisions for drawing up a technical document.
Students are required to attend at least 80% of the practical and laboratory classes at the scheduled time during the semester. Mandatory minimum attendance of module lectures – 50%.

Aim of Course

To present the general engineering and computer graphics fundamentals necessary in civil engineering design. To acquaintance with basic methods of general descriptive geometry, principles of orthographic projections, design methods, to introduce with modern computer aided design systems. Projection drawing. Views, arrangement of views in drawings. Simple and complex sections.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -45
Laboratory works – 0
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -10
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -116

Annotation of Course

The module presents the basics of projection drawing. It introduces machine production drawings, teaches to read assembly drawings and provides detailed information about the development of working drawings of detail. It shows the application of computer systems for drawing.
Students are required to attend at least 80% of the practical and laboratory classes at the scheduled time during the semester. Mandatory minimum attendance of module lectures – 50%.

Aim of Course

To introduce the projection drawing on common principles and their application to engineering drawings. Develop skills to read and create drawings using a collection of computer graphics systems and drawing standards.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 30
Consultations -4
Individual work -81

Annotation of Course

In this course students learn the concepts of computer arithmetic, stability and computational complexity of numerical algorithms. Students learn numerical methods for solving nonlinear equations and systems of equations, direct and iterative methods for solving linear systems of equations, finite difference method for solving differential equations, interpolation and approximation methods, and numerical integration methods.

Aim of Course

The goal is to introduce the basic numerical methods and to learn how to apply these methods for solution of specific problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -4
Individual work -111

Annotation of Course

In this course students learn the concepts of computer arithmetic and stability of numerical algorithms, numerical methods for solution of nonlinear equations and systems of equations, direct and iterative methods for solution of linear systems of equations, interpolation and approximation, numerical methods for solution of eigenvalue and eigenfunction problems, optimization methods, and numerical integration methods.

Students must attend at least 60% of the time scheduled practical works and 50% of the lectures.

Aim of Course

The goal is to introduce the basic numerical methods and to learn how to apply these methods for solution of specific problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

The basic probability theory concepts and theorems. The distribution functions of random variables and numerical characteristics. The problems of mathematical statistics. Empirical characteristics. The point and interval estimates of unknown parameters. Statistical hypothesis testing, elements of correlation theory, regression.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

To introduce the basics of probability theory and mathematical statistics, to train a student to use obtained knowledge for solving real-world problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96

Annotation of Course

The subject course deals with application-important calculus issues and includes the theory of functions of a complex variable, Fourier and Laplace transforms and some elements of probability theory.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

To present basic knowledge of Fourier analysis, complex analysis, operational calculus, probability theory and mathematical
statistics.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -18
Practical works -8
Laboratory works – 8
Consultations -4
Individual work -122

Annotation of Course

The basic probability theory concepts and theorems. The distribution functions of random variables and numerical characteristics. The problems of mathematical statistics. Empirical characteristics. The point and interval estimates of unknown parameters. Statistical hypothesis testing, elements of correlation theory, regression.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works (full-time studies and part-time, distance learning studies) and 50% of the lectures (only full-time studies).

Aim of Course

To introduce basics of probability theory and mathematical statistics, to train a student to use obtained knowledge for solving of real world problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -16
Practical works -10
Laboratory works – 8
Consultations -4
Individual work -122
Part-time, distance learning studies:
Lectures -20
Practical works -10
Laboratory works – 10
Consultations -0
Individual work -120

Annotation of Course

Introduction into set theory. Complex numbers. Matrices, determinants, elements of vector algebra and analytical geometry. Solution of systems of linear algebraic equations. Limit calculus of functions of single variable. Differential calculus.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works (full-time studies and part-time, distance learning studies) and 50% of the lectures (only full-time studies).

Aim of Course

To introduce basics of linear algebra, analytical geometry and differential calculation.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -18
Practical works -10
Laboratory works – 8
Consultations -4
Individual work -120
Part-time, distance learning studies:
Lectures -24
Practical works -15
Laboratory works – 10
Consultations -0
Individual work -111

Annotation of Course

Matrices, determinants, elements of vector algebra and analytical geometry. Solution of systems of linear algebraic equations. Limit calculus of functions of single variable, fundamental theorems of analysis.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

To give basic knowledge of linear and vector algebra, analytic geometry , differential and integral calculus.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 15
Consultations -2
Individual work -83

Annotation of Course

Matrices, determinants, systems of linear equations. Vector algebra. Analytical geometry. Function’s limit and continuity. Derivatives of single-variable functions and their applications.

Students must attend at least 60% of the time scheduled practical works (full-time studies and part-time, distance learning studies) and 50% of the lectures (only full-time studies).

Aim of Course

To give basic knowledge of linear and vector algebra, analytic geometry, differential calculus.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -18
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -130

Annotation of Course

The module of study subject introduces the main concepts and definitions of Probability Theory – a random event, its probability, sum and multiplication of probabilities theorem, total-probability and Bayes formulas, the Normal and Poisson approximations to the Binomial probability. Random variables and their distribution analysis, independence of random variables. The most common distribution laws of random variables (vectors), the analysis of numeric characteristics of random variables and their dependence are introduced. The empirical analogues of the theoretical distribution characteristics and the basic concepts of mathematical statistics are defined.

Students must attend at least 60% of the time scheduled practical works and 50% of the lectures.

Aim of Course

Provide a basic knowledge of stochastic nature of events and their mathematical models and the ability to apply this knowledge practically.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -2
Individual work -33

Annotation of Course

Discrete mathematics is a branch of mathematics that studies discrete structures and discrete mathematical models of real phenomena. It emerged as an independent field in the middle of the 20th century due to the emergence of cybernetics and computer science and the development of computer technology. Discrete mathematics deals with combinatorics, graph theory, mathematical logic, information coding, finite automata, formal grammars, etc. It also covers issues of number theory, computational mathematics, probability theory, and mathematical programming. Discrete mathematics is important in informatics and cybernetics and has practical application possibilities in algorithms, data storage and transmission, and information processing.

Students must attend at least 60% of the time scheduled practical works and 50% of the lectures.

Aim of Course

To acquaint with basic concepts of mathematical logic, combinatorics, relations, sets. Students must be able solve typical problems, apply modern mathematical methods to solve real life problems, to modify and generalize formulation of problem.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -2
Individual work -33

Annotation of Course

Study course consists of linear algebra basics: algebraic, trigonometric and exponential forms of complex numbers, power and root of complex number, de Moivre’s formula, Riemann sphere, matrices and determinants, matrix operations, properties of determinants, systems of linear equations, solving systems using Cramer’s rule, inverse matrices, Gauss and Jordan methods, structure of general solution of systems, linear spaces, linear independence of vectors, vector space basis, change of basis, orthonormal basis, orthogonalization of given basis, Hermitian space, linear operators and matrices of them, operator matrix and change of basis, eigenvalues and eigenvectors of linear operator, canonical shape of operator, orthogonal, self-dual operators, quadratic forms, their invariants, general algebraic operations and structures, samples of them.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

Linear algebra course is designed to introduce concepts and methods of linear algebra in conjunction with applications of linear methods in various fields, to develop the capacity to solve problems using principles of linear algebra.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96

Annotation of Course

The module of study subject introduces the main concepts and definitions of Probability Theory – a random event, its probability, sum and multiplication of probabilities theorem, total-probability and Bayes formulas, the Normal and Poisson approximations to the Binomial probability. Random variables and their distribution analysis. Independence of random variables. The most common distribution laws of random variables (vectors), the analysis of numeric characteristics of random variables and their dependence are introduced. The empirical analogues of the theoretical distribution characteristics and the basic concepts of mathematical statistics are defined.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

Provide a basic knowledge of stochastic nature of events and their mathematical models and the ability to apply this knowledge practically. To acquire the basic knowledge of mathematical statistics.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96

Annotation of Course

The Differential Calculus course consists of general theory of functions of one variable and of several variables.Properties of sets of real numbers. Sequences and their properties. Limits and continuity of functions. Basic concepts of differential calculus. Application of the derivarives to solution of practical problems and limits of the functions, derivatives, unconditional and conditional extremal values, application to solution of practical problems. Basic methods of integration: direct integration, integration by parts, integration by substitution, integration of rational, irrational and transcedential functions.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

To provide a knowledge about functions of one and several variables and their applications for solution of practical problems.To provide theoretical knowledges for study modules that require studies of differential calculus. To develop ability of independent study, to explore and analyse models in the different practical applications, get results, analyze and interpret them.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96

Annotation of Course

In this course students learn the concepts of complex numer and complex functions, complex integration, complex series, residues, Fourier series, integrals and tranfsorms, Laplace transform and its applications, vector differential calculus.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

The goal is to introduce complex analysis, Fourier analysis, Laplace transform, vector differential calculus basics and to present their principal applications.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -45
Practical works -30
Laboratory works – 15
Consultations -6
Individual work -144

Annotation of Course

Elements of mathematical logic. Boolean functions. Finit sets and combinations. Combinatorical numbers. Generating functions. Recurrence relations. Set theory Mathematical induction.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

To acquaint with basic concepts of mathematical logic, combinatorics, relations, sets.. Students must be able solve typical problems, apply modern mathematical methods to solve real life problems, to modify and generalize formulation of problem.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96

Annotation of Course

The basic probability theory concepts and theorems. The distribution functions of random variables and numerical
characteristics. The problems of mathematical statistics. Empirical characteristics. The point and interval estimates of
unknown parameters. Statistical hypothesis testing, elements of correlation theory, regression.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works and 50% of the lectures.

Aim of Course

To introduce basics of probability theory and mathematical statistics, to train a student to use obtained knowledge for solving

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96

Annotation of Course

The course presents the basic concepts and ideas of analytic geometry and mathematical analy-sis. Contains the general information of basic mathematical models and scientific approaches for contemporary architectural theory and practice.

Students must attend at least 60% of the time scheduled practical works and 50% of the lectures.

Aim of Course

To introduce basics of analytical geometry and mathematical analysis. To develop logical and ana-lytical thinking, ability to generalize information and ground the conclusions, to communicate effectively with specialists of different fields, to formulate and solve practical problems, to learn new knowledge.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -15
Practical works -15
Laboratory works – 0
Consultations -2
Individual work -48

Annotation of Course

The course covers the elements of linear algebra (matrices, determinants, systems of linear equations), analytical geometry (vectors, straight lines, planes, curves and surfaces of second order) and differential calculus of functions of one variable (limits, derivatives, investigation of functions). The questions of their practical application are touched upon.

Students must attend at least 60% of the time scheduled practical works and 50% of the lectures.

Aim of Course

To introduce basics of linear algebra, analytical geometry and differential calculus. To develop the ability to formulate and solve practical problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96

Annotation of Course

The basic probability theory concepts and theorems. The distribution functions of random variables and numerical characteristics. The problems of mathematical statistics. Empirical characteristics. The point and interval estimates of unknown parameters. Statistical hypothesis testing, elements of correlation theory, regression.

Students must attend at least 60% of the time scheduled practical works, 80% of the time scheduled laboratory works (full-time studies and part-time, distance learning studies) and 50% of the lectures (only full-time studies).

Aim of Course

To introduce basics of probability theory and mathematical statistics, to train a student to use obtained knowledge for solving of real world problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -16
Practical works -10
Laboratory works – 10
Consultations -4
Individual work -120

Annotation of Course

The course covers the elements of linear algebra (matrices, determinants, systems of linear equations), analytical geometry (vectors, straight lines, planes) and differential calculus of functions of one variable (limits, derivatives, investigation of functions). The questions of their practical application are touched upon.
Students must attend at least 60% of the time scheduled practical works (full-time studies and part-time, distance learning studies) and 50% of the lectures (only full-time studies).

Aim of Course

To introduce basics of linear algebra, analytical geometry and differential calculus

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -16
Practical works -16
Laboratory works – 0
Consultations -4
Individual work -124

Annotation of Course

Examples of algorithms. The main data structures and their implementation. Data search and sorting algorithms. Basic principles for development of algorithms. Complexity of algorithms. Greedy algorithms, dynamic programming. Algorithms for solution of graph problems.
Students must attend at least 60% of the time scheduled practical lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

To introduce data structures, to present principles for development and implementation of algorithms, to show how the complexity of algorithms is analyzed, to solve sorting, search, combinatorial, graph problems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -8
Practical works -4
Laboratory works – 4
Consultations -4
Individual work -140

Annotation of Course

The module provides an overview of the ethical, legal and human factor information security aspects: IT security, internet and intellectual property regulation, the fundamentals of legal regulation of privacy and personal data, cybercrime and regulation of their research, the principles of professional ethics of cyber security and the main professional codes of ethics and the influence of the human factor in information and cyber security

Aim of Course

The aim of the subject is to familiarize students with the ethical, legal and human aspects of information security and to teach them to apply in practice.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

The module presents data modelling theoretical and practical methods and various data management strategies and techniques. The module provides topics on data modelling and different aspects of their application in information systems. The module discusses various relational and non-relational data modelling patterns in differnt types of database management systems. It presents data management processes in organistaions which are related to data security, including access control, data quality, redundancy and backup strategies and methods. Finally, the module introduces to data transformation, analysis and knowledge discovery processes using data.

Aim of Course

To provide students with the knowledge on data modelling techniques and application of various database types during the design of information systems and data management and analysis during information system lifecycle. The students will deepen knowledge on relational database design and will understand how and when to apply non-relational databases. The students will acquire knowledge on data backup strategies, performance management and knowledge on data warehouse modelling and design, data analysis methods.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -180

Annotation of Course

The implementation of software design rules in the context of different programming languages is analyzed. The module presents software design principles by grouping the implementation context of the domain analysis scope, using best practice in the implementation of the rules.

Aim of Course

To get knowledges and practical skills by using software object-oriented design practices.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -180

Annotation of Course

This module provides an overview of main modern information system security insurance principles and methods, gives the basics on network security, introduces main cryptographic algorithms and protocols, familiarizes with physical security and business continuity insurance elements. The basic aspects of information security management, utilization of security audit and ethical hacking methods for information system protection, as well as legal and ethical aspects of data protection are analyzed.

Aim of Course

To provide basic knowledge on methods and principles of information system security insurance.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

The module is designed to provide students with an understanding of the technological, technical, social, legal, and management dimensions of information systems. It is an advanced level module addressed to all carrier tracks. The primary objective of the module is to introduce the issues innovated in identifying, developing, implementing, and maintaining IS. The students will gain the understanding of the elements that comprise IS and how these elements are created and co-ordinated to support decision making. An emphasis will be placed on the IS interoperability, integration of enterprise-wide information infrastructures into global infrastructures.

Aim of Course

The primary objective of the module is to introduce the issues innovated in identifying, developing, implementing, and maintaining IS.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 30
Consultations -0
Individual work -180

Annotation of Course

The module presents a framework for understanding the role of AI in information systems, problem solving, knowledge representation, reasoning, knowledge-based systems and knowledge management. It is an advanced level module covering broad subject area and addressed to career tracks Academic, IS engineer, Knowledge engineer, Data manager, Systems integrator, Systems (business) analyst and IS consultant. The module trains to create human-centred flexible enterprise-wide information infrastructure that effectively supports decision making and knowledge management. It introduces the advanced AI methods and technologies, agent technologies and their application in IS, advanced knowledge management concepts, methods and tools. The module also teaches how to decompose given phenomena into its components, break large problems into smaller sub-problems, model problems at different abstraction levels, use an analytical and systemic approach to problem solving and decision making.

Aim of Course

The module presents a framework for understanding the role of AI in information systems, problem solving, knowledge representation, reasoning, knowledge-based systems and knowledge management.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -100

Annotation of Course

Subject to provide students about requirement engineering and its processes: requirements elicitation and analysis, requirements specification, requirements validation and requirements management. Student analyze and get practical skills about types of requirement: users, functional, non-functional and their quality criteria. To provide students about types of requirement specification and their validation. During the module, students get knowledge about types of requirement specification, requirements verification and validation. Requirements management: prioritization, traceability, changes and risks management, standards and regulations.

Aim of Course

To provide knowledge and skills about processes of requirement engineering, during them applied methods and standards.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

This module presents modern information technology security insurance aspects, necessary while studying the “Information and IT security” Master course. Basic concepts and models are being described and analyzed; major information security insurance technologies are presented and described. Primary attention is dedicated to technological information security aspects

Aim of Course

To provide knowledge on information technology security methods and principles.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -180

Annotation of Course

Theoretical and practical foundations of cryptographic information security methods are acquired. Popular and advanced cryptosystems are analyzed, which provide information confidentiality, integrity and authenticity. Abilities to used obtained knowledge in information society technologies (e-business, e-money, bitcoin, e-government, e-voting etc.) are provided. Main module topics are: problems of information security; history of coding; symmetric and public key cryptography; DES; AES; RSA; stream ciphers; cryptographic protocols; authentication; electronic signature; management of electronic identity; block chain technology.

Aim of Course

To expand knowledge of applied cryptography and information protection technologies used in computer systems.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -180

Annotation of Course

Increase of cyber crime has increased the need for organizations to have specialists with specific knowledge, necessary to identify, investigate them and take actions to minimize such cyber crime consequences. Demand for such specialists can be seen both from commercial organizations (for such event identification, informal investigation and response) and legal enforcement institutions (formal cyber crime investigation). In this module specific technical, law and organizational methods are analyzed, that are necessary to handle cyber crime cases and perform computer forensics tasks.

Aim of Course

To provide specific knowledge, necessary to identify cyber crime events, implement reaction procedures and perfrom computer forensics tasks.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 30
Consultations -0
Individual work -180

Annotation of Course

The course content oriented toward state of the art in information security management problems and solutions. The content contains most relevant and important topics about information security management purpose, tools and organization, processes and information sources particularities, vulnerabilities and associated risk. The course is adapted for MSc students, who have the Informatics or informatics engineering BS degree.

Aim of Course

To provide students with knowledge and skills necessary manage information security related processes of an organization.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 0
Consultations -0
Individual work -115

Annotation of Course

Concept of data structures. Linear data structures: vector, list, stack, queue, deck, heap. Hierarchical data structures: binary tree, AVL tree, Bayer tree, Red-Black tree. Memory demand and efficiency of data structures. Algorithms, complexity, asymptotic analysis. Sorting algorithms. Searching algorithms. Recursive algoritms, memory allocation. Data exchange between external and internal memory in sorting and searching algoritms.
Students must attend at least 80% of the time scheduled laboratory work. Mandatory minimum attendance of module lectures – 50%.

Aim of Course

The aim of the course is to introduce students to the data structures and their practical realization by creating the corresponding functions and classes, teaching algorithms, analyzing and evaluating them.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -12
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -136

Annotation of Course

The module introduces the concept of software engineering. Students are familiarized with the process of software systems development and main concepts of a system, system engineering, software systems, software systems engineering, information systems, business systems and requirements. Students are familiarized with possible software systems in organizations and their types. Another topic covered is software crisis and why it arises. The following topics are covered during the lectures also: main software development principles and paradigms, domain analysis and conceptual modelling, including modelling with UML. Students are taught to begin creating software systems that meet the needs of customers. The module is also taught how to write technical reports and other technical documents.
Students must attend at least 80% of the time scheduled laboratory work. Mandatory minimum attendance of module lectures – 50%.

Aim of Course

The primary objective of the module is to introduce main concepts of software systems engineering, principles and methods.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -14
Practical works -8
Laboratory works – 0
Consultations -4
Individual work -134

Annotation of Course

This module covers a wide range of topics in area of secure programming, such as safe initialization, access control, input validation, symmetric and public key cryptography, typical programming mistakes and vulnerabilities, secure and vulnerable libraries, code parsing and analyzing methods and tools, software testing and evalution methods. Specific secure programming issues for different operating systems and WEB environment.

Aim of Course

To present secure programming methods to students and form practical skills of using them.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -30
Laboratory works – 0
Consultations -0
Individual work -100

Annotation of Course

Physics, the subject of the study, is a combination of theory and practice, designed to provide students with understanding of fundamental mechanics, molecular physics and thermodynamics, electrostatics, electrodynamics, electromagnetism, optics and atomic physics, all needed for civil engineering studies. The knowledge is provided about mechanical oscillations and vibrations and their manifestation in engineering devices and construction structures, thermal phenomena, electrical and magnetic parameters, electrical measuring devices. The ability to interpret and efficiently explain the results of experimental research obtained in laboratories is developed.
Students must attend at least 60% of the time scheduled of the lectures.
Students must attend at least 60% of the time scheduled practical lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

To give knowledge about basic interactions in nature, gravitational, electrical and magnetic fields, nature of mechanical and electrical phenomena and processes, states of solid and gaseous material, to educate skills of scientific thinking, to teach how to estimate theoretically and experimentally data and reliability, to prepare for the engineering studies.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -16
Practical works -10
Laboratory works – 10
Consultations -4
Individual work -120

Annotation of Course

Physics course gives knowledge on translation and rotation motions of rigid body, kinematics and dynamics of both types of motion. The course explains a nature of mechanical oscillations, a propagation of waves through various media, as well as clarifies basic questions of molecular physics and thermodynamics. The course emphasizes fluid and gas dynamics, acoustics, transport phenomena in non-equilibrium thermodynamic systems taking into account specifics of studies in Transport engineering faculty.
Students must attend at least 60% of the time scheduled practical lectures.
Students must attend at least 60% of the time scheduled of the lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

To give a comprehension about basic interactions, about nature of mechanical phenomena and processes in gases, liquids and solids. To formulate practical abilities to apply fundamental nature laws and teach, and anable to solve quantitative and qualitative tasks.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -10
Practical works -0
Laboratory works – 10
Consultations -4
Individual work -136

Annotation of Course

This course introduces the fundamental principles of optics and the operation of lenses, optical systems. It then explores the physics and engineering of lasers. Beyond core physical concepts, the course connects optics with applied artificial intelligent using machine learning models. Students will gain practical experience through mini-projects applying AI tools to process optical data, enabling them to bridge physical systems with intelligent computing solutions.
Students must attend at least 60% of the time scheduled of the lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

The aim of this course is to provide foundational understanding of optical physics, laser systems and photonic technologies, while equipping them with practical knowledge to integrate optical data and systems in to artificial intelligent driven applications.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -0
Laboratory works – 15
Consultations -2
Individual work -33

Annotation of Course

The study subject is intended to provide the basics of classical mechanics, molecular physics, and thermodynamics. During the studies, the main laws of translational and rotational motion, laws of molecular physics and thermodynamics are examined.
Students must attend at least 60% of the time scheduled of the lectures.
Students must attend at least 60% of the time scheduled practical lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

To provide knowledge of mechanics, molecular physics and thermodynamic phenomena. To establish the theoretical and practical basis necessary for the study of advanced and specialized disciplines.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time studies:
Lectures -18
Practical works -12
Laboratory works – 12
Consultations -4
Individual work -114
Part-time, distance learning studies:
Lectures -20
Practical works -10
Laboratory works – 10
Consultations -0
Individual work -120

Annotation of Course

Fundamental interactions in the nature, their characteristics and laws and their interpretation in the bioengineering studies. Mechanical fluctuations and oscillations and their occurrence in the engineering equipment and constructions. Ideal and real gases, their characteristics and laws. Liquid state of material and its peculiarities.
Students must attend at least 60% of the time scheduled of the lectures.
Students must attend at least 60% of the time scheduled practical lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

To give knowledge about basic interactions in nature, gravitational, electrical and magnetic fields, nature of mechanical and electrical phenomena and processes, states of gas and liquid material, to characterize the content of created technologies achieved by physics science, to educate skills of the scientific thinking, to teach to estimate theoretical and experimental got data and their reliability, to prepare for the engineering studies. To give practical skills of laboratory works

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 30
Consultations -4
Individual work -81

Annotation of Course

The methods of research in physics, their applications and limits. Fundamental interactions in nature. Kinematics and dynamics of translational and rotational motion and coresponding differential equations. Mechanical inertia. Conservation laws in mechanics. Mechanical oscillations and waves. Thermodynamics and statistical methods. Laws of thermodynamics. Heat based engines. Cyclical processes in thermal based engines. Entropy. Thermal and mechanical properties of materials.
Students must attend at least 60% of the time scheduled of the lectures.
Students must attend at least 60% of the time scheduled practical lectures.
Students must attend at least 80% of the time scheduled laboratory work.

Aim of Course

To provide fundamental knowledge about the nature of mechanical and thermal properties and phenomena; to develop abilities for special courses.

Distribution of course hours by study forms and ways

Full-time studies:
Lectures -30
Practical works -15
Laboratory works – 15
Consultations -4
Individual work -96
Part-time, distance learning studies:
Lectures -18
Practical works -8
Laboratory works – 8
Consultations -4
Individual work -122