Master degree program
Computer Science

Computer Science

QUALIFICATION

  • Scientific and pedagogical direction - Master of Engineering Sciences

MODEL OF GRADUATING STUDENT

ON1 Explaining the principles of organizing and planning research.
ON2 Describing how to evaluate the computational complexity of algorithms.
ON3 Choosing software design and development methods, programming languages, architectures, taking into account their inherent limitations.
ON4 Simulating tasks and develop new tools and applications for collecting, storing, analyzing and managing data.
ON5 Developing advanced networked computer systems with an emphasis on reliability and security.
ON6 Performing high-performance scientific calculations, evaluate the performance of parallel computing systems.
ON7 Applying pattern recognition theory and machine learning methods to solve problems from different subject areas.
ON8 Restructuring existing software, identifying problem components, choosing solution strategies.
ON9 Carrying out research and development in an environment focused on the final product, scientifically substantiate strategic decisions.
ON10 Analyzing and critically treating various sources of information, applying them to structure and formulating reasoning.
ON11 Independently conducting research: understanding current research questions, independently applying published results or methods in a new context.
ON12 Conducting scientific and pedagogical activities, leading a research team: evaluating the necessary funds, sharing tasks, planning the time to complete tasks, provide reports.

Program passport

Speciality Name
Computer Science
Speciality Code
7M06104
Faculty
Information technology

disciplines

Advanced Data Structures, Algorithms and Analysis
  • Number of credits - 6
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Basic algorithms: asymptotic writing, recursion, the divide and conquer paradigm, basic data structures; fast Fourier transform. Algorithms of sorting. Data structures: priority queues and heaps, dictionaries, hash tables, Bloom filters, binary search trees, interval trees. Dynamic programming, graph algorithms: DFS, BFS, topological sorting, shortest path algorithms, network flow problems.

Distributed Systems Theory
  • Number of credits - 6
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Introduction to distributed computing models. Clock synchronization. Termination detection algorithms. Distributed mutual exclusion algorithms. Deadlock detection algorithms. Distributed shared memory. Distributed file servers. Distributed programming environments: communication primitives, individual case studies.

Foreign Language (professional)
  • Number of credits - 6
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The purpose is to acquire and improve competencies by international standards of foreign language education and to communicate in an intercultural, professional, and scientific environment. A master's student must integrate new information, understand the organization of languages, interact in society, and defend his point of view.

History and Philosophy of Science
  • Number of credits - 3
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The course forms knowledge about the history and theory of science; on the laws of the development of science and the structure of scientific knowledge; about science as a profession and social institution; оn the methods of conducting scientific research; the role of science in the development of society.

Neural networks for pattern recognition
  • Number of credits - 5
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The course is designed to implement a convolutional neural network, which is used in computer vision for pattern recognition, mastering the practical foundations of forming a database for training, the basic principles of training, testing and developing the structure of neural networks.

Organization and Planning of Scientific Research (in English)
  • Number of credits - 6
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The purpose of the discipline is to train masters in conducting scientific research, carrying out scientific and methodological work, socializing young students and their participation in the corporate governance system of Organization of higher and postgraduate education (OHPE). Undergraduates learn to interact with OHPE stakeholders, participate in research projects.

Pedagogy of Higher education
  • Number of credits - 5
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The purpose is the formation of the ability of pedagogical activity through the knowledge of higher education didactics, theories of upbringing and education management, analysis, and self-assessment of teaching activities. The course covers the educational activity design of specialists, Bologna process implementation, acquiring a lecturer, and curatorial skills by TLA-strategies.

Psychology of Management
  • Number of credits - 3
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The course reveals the subject, the basic principles of management psychology, personality in managerial interactions, personal behavior management, psychology of managing group phenomena and processes, psychological characteristics of the leader's personality, individual management style, psychology of influence in management activities, conflict management.

Software Engineering Technology
  • Number of credits - 5
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - This course is intended to describe a set of processes and methods for creating a software product. Software engineering technology is a system of engineering principles for creating cost-effective software that runs reliably and efficiently on real computers.

Theory of pattern recognition
  • Number of credits - 9
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Statement of the pattern recognition problem. Representation of images in digital form. Methods of analysis and primary image processing. The task of selecting informative features. Pattern recognition methods: deterministic, statistical, structural methods for solving recognition problems; algebraic methods for constructing decision rules and pattern recognition;

Data for 2021-2024 years

disciplines

Advanced object oriented programming
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The following aspects are considered within the discipline: Use case diagrams and scenarios to support understanding of user requirements. Object-oriented design notations, including UML class diagrams and state diagrams for modeling problem solving. Basic object-oriented design patterns for structuring solutions to software design problems.

Advanced Design and Analysis of Algorithms
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - This course is aimed at studying approaches to solving problems from various fields (mathematical analysis, discrete analysis, graph theory, combinatorial game theory, optimal software development, etc.), which are not covered in classical courses on algorithms and data structures, but can be useful as part of the mathematical apparatus .

Advanced mobile application development
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - This course is aimed at studying the technology of software development for mobile devices with the Android operating system, the basics of quality management and standardization of software development, the formation of skills in the use of modern programming technologies, the application of object-oriented programming approaches in the development of mobile applications and the use of databases in mobile applications .

Advanced network security
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The task of the discipline is to give an idea of the basic principles and structures of information, to teach how to program multifunctional security applications, to develop security models. To form a system of basic theoretical knowledge for undergraduates with ways to protect network technologies. To help undergraduates acquire the skills to counter the vulnerability of basic mobile technologies, protect against attacks exploiting the vulnerabilities of SMS technologies.

Big Data analysis
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Conceptualization and synthesis: data presentation. Simulation of machine learning techniques. Application of big data processing technologies. Trivial data against big data: representative training. Publicly available data sets. Scalability and scaling methods. Big data processing environment: modern data analysis technologies. Programming languages for big data analytics: Python, Java, and C.

Cloud computing
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - When studying the discipline, will study the following aspects: The main trends in the development of cloud computing and technology. Architecture "cloud" technology. Methods and features of the design of "cloud" services. The main models for the provision of cloud computing services. Solutions from leading vendors - Microsoft, Amazon, Google. The main advantages and disadvantages of cloud computing models and solutions proposed on their basis.

Computer system development technologies
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Principles of building architectures of supercomputers and cluster systems. Architecture of multiprocessor computing systems: vector-conveyor supercomputers, symmetric multiprocessor systems (SMP), massively parallel processing systems (MPP), cluster systems. Introduction to the topic of supercomputer technology. The main elements of software supercomputers and cluster systems. Administration of supercomputers and cluster systems.

Deep learning
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The subject covers the following aspects: Architecture of deep neural networks. Customize hyperparameters and deep learning frameworks. Convolutional neural networks, their applications. Classification of objects and similar methods. Convolutional neural networks, their applications. Recurrent neural networks, their applications. Parallel deep learning algorithms. Acceleration of neural network learning.

Developing dynamic web applications
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - As a result of studying the discipline, the following abilities of master students will be formed: - describe and compare modern tools used for programming web application servers; - apply the basic concepts of software development to the design and programming of web applications; - programming web application servers; - summarize web application concepts using Django / Python for other web application technologies and tools;

Formal Methods and Applications
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - As part of the course, the basic principles of using formal methods in software development are studied, including the basic mathematical models and methods for their analysis and synthesis, and the skills of analyzing and designing software using formal methods are formed.

Fundamentals of Reinforcement Learning
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - To develop the ability of masters' to analyze data, use machine learning methods in real problems, conduct independent research on real data, to introduce new research in the field of ML. Also to acquaint undergraduates with the basic concepts and terminology of machine learning; learn to perform statistical analysis of data and visualize them; The main purpose of the course is to acquaint with the technology of large-scale data processing.

High-Performance Computer Architecture and Parallel Computing
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: A modern multi-core processor. Models of parallel programming. GPU architecture and CUDA programming. Performance Optimization. Distribution and scheduling. Performance evaluation based on workload. Basic multiprocessing implementation. Transactional Memory. Heterogeneous parallelism and hardware specialization. Distributed computing in memory.

Mathematical methods of pattern recognition
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Representation of images and basic approaches to machine recognition. Applications of pattern recognition methods: computer vision, handwriting recognition, speech recognition. Classification based on Bayesian decision theory. Linear and nonlinear classifiers. Committee methods for solving recognition problems. Pattern recognition methods based on neural networks. Pattern recognition methods based on cluster analysis.

Mobile Application Development
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - This course is aimed at studying the technology of software development for mobile devices with the Android operating system, the basics of quality management and standardization of software development, the formation of skills in the use of modern programming technologies, the application of object-oriented programming approaches in the development of mobile applications and the use of databases in mobile applications .

Modeling and Simulation for Computer Science
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the framework of the course, it is planned to conduct an in-depth analysis of problems, to substantiate physical problems, to reveal their natural scientific essence in the course of scientific and research activities, to apply the appropriate mathematical apparatus and numerical algorithm to solve them. Implementation of Analyze, design and conduct numerical experiments of the constructed mathematical models of industrial, physical and technological, non-linear non-stationary physical, chemical, biomedical, financial processes.

Models of machine learning
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Formal model of machine learning. Basic algorithms for solving problems of classification and regression recovery. Metric methods of machine learning. Bayesian methods of machine learning. The task of the reconstruction of the density distribution. Separation of the mixture of distributions. The EM-algorithm. Linear machine learning methods and their generalizations. Visualization and clustering. Artificial neural network.

Models of speech technologies
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The purpose of discipline: formation of the ability to set tasks in the field of processing and analyzing speech information and find solutions based on modern approaches. As a result of studying the discipline, the following abilities of master students will be formed: - Solve the problem of processing natural speech based on machine learning and pattern recognition; - perform independent scientific research in the field of speech technology; - effectively use in practice the theoretical components of science; - to present a panorama of universal methods and laws of modern natural science; - plan the process of modeling and computational experiment. Within the framework of the discipline, the following aspects are considered: Within the discipline the following aspects will be considered: Mathematical models of speech signal. Wavelet speech signal analysis for speech synthesis and recognition. Signal processing in the frequency domain. Short-term analysis. FFT. Parametric and indicative description of speech images in the frequency domain. Parametric description of speech signals in the time domain. Model of linear speech prediction. Coding of speech signals. Vector quantization. Examples of modern speech codecs. Silent Speech Interfaces - speech processing systems. Structure of speech recognition systems. Statistical approach to speech recognition. Criteria of efficiency of speech recognition system.

Neural networks in data analysis
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - Within the discipline the following aspects will be considered: Data analysis process based on neural network. Interneuron connections. Artificial neuron. Architecture of NS. Preliminary selection of network architecture. Selection of optimal network architecture. Methods of building a network. Pattern recognition and classification. Neural network for data compression. Neurons of type WTA. The model of a Hebb’s neuron. Stochastic model of a neuron.

Servers and Data Warehouse
  • Type of control - [RK1+MT+RK2+Exam] (100)
  • Description - The purpose of discipline: formation of the ability to implement a data warehouse platform to support business decisions, validate and clear data using data quality services. As a result of studying the discipline, the following abilities of master students will be formed: - describe the key elements of the solution for data warehouses; - implement the logical and physical design of the data warehouse; - deploy a data warehouse; - implement data quality services; - create models of master data services. Within the discipline the following aspects will be considered: Introduction to the data warehouse. Data storage infrastructure planning. Development and implementation of data warehouse. The implementation of the data warehouse. Implementing control flow in a service package. Debugging and troubleshooting service packages. Ensure data quality. Use of master data services. The use of data in the data warehouse. Introduction to data analysis.

Data for 2021-2024 years

INTERNSHIPS

Pedagogical
  • Type of control - Защита практики
  • Description - Aim оf discipline: formation of the ability to carry out educational activities in universities, to design the educational process and conduct certain types of training sessions using innovative educational technologies.

Research
  • Type of control - Защита практики
  • Description - The purpose of the practice: gaining experience in the study of an actual scientific problem, expand the professional knowledge gained in the learning process, and developing practical skills for conducting independent scientific work. The practice is aimed at developing the skills of research, analysis and application of economic knowledge.

Data for 2021-2024 years