Module

Learning outcomes

1

2

3

4

5

6

7

8

9

10

11

12

Module on history and philosophy of science

+ 

Psychology and Pedagogy Module

+ 

Elements and devices of automation

+ 

+ 

+ 

+ 

Neural networks and machine learning

+ 

+ 

+ 

Scientific and technical problems of control systems

+ 

+ 

+ 

Embedded control systems

+ 

+

+ 

Intelligent Control Systems

+

+ 

+

Automated control systems

+

+

+

CORE DISCIPLINES

MAJOR DISCIPLINES

RESEARCH

UNIVERSITY COMPONENT

ELECTIVE COMPONENT

UNIVERSITY COMPONENT

ELECTIVE COMPONENT

MASTER’S STUDENT RESEARCH (MSR), INCLUDING SCIENTIFIC INTERNSHIP AND DISSERTATION WRITING

20

15

31

18

35

49

24

1

Module on history and philosophy of science & Psychology and Pedagogy Module

6 ECTS

Elements and devices of automation / Neural net. and machine learning

(1 of 2)

6 ECTS

Scientific and technical problems of control systems

12 ECTS

RES.

3 ECTS

27

2

Module on history and philosophy of science & Psychology and Pedagogy Module

14 ECTS

Elements and devices of automation / Neural networks and machine learning

(1 of 2)

9 ECTS

Scientific and technical problems of control systems

6 ECTS

RES.

4 ECTS

33

3

Embedded control systems

13 ECTS

Intelligent Control Systems /

Automated control systems

(1 of 2)

18 ECTS

RES.

2

ECTS

33

4

RES.

15 ECTS

FINAL ATTESTATION

12 ECTS

27

Module/Disciplines

ECTS

Workload HPW

Term

lec.

sem.

lab.

other

Module on history and philosophy of science

9

History and philosophy of science

3

1,5

1,5

1

Foreign Language (professional)

6

6

2

Psychology and Pedagogy Module

11

Pedagogy of higher education

3

1,5

1,5

1

Psychology of Management

3

1,5

1,5

2

Pedagogical Practice

5

5

2

Elements and devices of automation

15

Power Electronic Devices and Systems

6

3

3

1

Sensors and sensor systems

9

3

6

2

Neural networks and machine learning

15

Neural networks and machine learning mechanisms

6

3

3

1

Deep neural networks

9

3

6

2

Scientific and technical problems of control systems

18

Organization and planning of scientific research

6

3

3

1

Nonlinear and adaptive control systems

6

3

3

1

         Modern methods of project management in             engineering

6

3

3

2

Embedded control systems

13

Design of embedded control systems

9

3

6

3

RESEARCH PRACTICE

4

4

3

Intelligent Control Systems

18

Intelligent data processing systems

9

3

6

3

Intelligent multi-agent systems  

9

3

6

3

Automated control systems

18

Distributed control systems

9

3

6

3

Industrial IoT

9

3

6

3

RESEARCH

24

Research Seminar

3

3

1/2/4

Dissertation Writing

14

14

1/2/3/4

Scientific Internship

3

3

4

Publication in the Proceedings of International Conferences 

4

4

4

FINAL ATTESTATION

12

4

TOTAL

120

Module Objectives. Students will be able to:

1. to describe the specifics of the relationship between the main problems and topics of the philosophy of science and the history of science;

2. explain the self-consciousness of science in its socio-philosophical perspectives;

3. classify the methods of scientific and philosophical knowledge of the world;

4. to substantiate the role of disciplinary self-determination of natural, social and technical sciences, their commonalities and differences;

5. apply professional and practical skills and abilities in research activities;

6. differentiate various philosophical concepts and concepts, generalize the results of historically important scientific discoveries;

7. integrate interdisciplinary knowledge based on a holistic systematic scientific worldview with the use of knowledge in the field of history and philosophy of science;

8. conduct research relevant to identify the philosophical content of problems in the professional field and present the results for discussion.

Module designation

History and philosophy of science

Credit points

3 

Semester(s) in which the module is taught

1

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

lecture, seminar 

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Boretsky Oleg, PhD, associate professor

Language

Kazakh / Russian / English 

Required and recommended prerequisites for joining the module

Pre-requisites: Philosophy, the complex of natural-science and socio-humanistic studies of bachelor course

Module objectives/intended learning outcomes

Knowledge base: The purpose of the discipline is to study the complex problems of science in philosophical knowledge and philosophical research through the presentation of the main directions, approaches, methodology, methods associated with the phenomenon of science, modern science, epistemology, research of science in culture, etc.

Analysis: critically analyze and evaluate the philosophical concepts of science and the "main" approaches to the "problems" of science in philosophy and philosophy of science.

Synthesis: can synthesize and transform the philosophical and interdisciplinary knowledge to solve educational and research applications, can use conceptual and methodological apparatus of philosophy and social sciences to solve creative issues of various difficulty levels, using modern computer technologies and interactive teaching methods;

Evaluation: substantiate and reveal the essence of the philosophy of science in the context of the development of philosophical knowledge and the methodology of philosophical cognition and researches;

Application: argue their own position and point of view regarding the importance of the diversity of scientific research, as well as approaches to the problems of science;

Application of skills: can work on educational and research projects to determine the context of the problem, formulate research goals and objectives, substantiate the methodology and methods of the project (using modern computer technology, resources, etc.)

Autonomy in skill use: can plan and implement basic and applied research projects, perform science projects using methods of analysis of social and individual reality and methods of research process of its transformation, present ability of design and carrying out professional, scientific and scientific pedagogical activity, based on the philosophical understanding of modern educational processes.

Content

●           Introduction to the discipline. The subject of history and philosophy of science.

●           Science as a subject of philosophy, and a variety of "scientific" and "theoretical" research in philosophy, as well as research of science itself in philosophy.

●           Classical and modern philosophy of science in the context of studying the problems of science and its evolution: comparisons and evaluations.

●           Features of science as a social institution. Classical philosophy and philosophy of science: essence, criteria and names.

●           Historical dynamics of science and its features.

●           Foundations and possibilities of internalist and externalist approaches and models of the development of scientific knowledge.

●           Scientific picture of the world and actual problems of science in modern philosophy of science.

●           The problem of scientific rationality in modern philosophy of science.

●           Science and methodological knowledge. Science and methodological culture.

●           The nature and specificity of the scientific revolution.

●           Theoretical knowledge.

●           Disciplinary structure of science: philosophical analysis.

●           Social and humanitarian knowledge and science: evolution, structure, tasks, problems, etc.

●           Scientific discovery.

Science as the basis for the development and modernization of modern society.

Examination forms

Written examination: Project work, essay

Reading list

Main:

●           Mitroshenkov, OA History and Philosophy of Science: textbook for universities / OA Mitroshenkov. - Moscow: Yurayt Publishing House, 2022. - 267 p. (Russian)

●           Franz-Peter Griesmaier, Jeffrey A. Lockwood. This is Philosophy of Science: An Introduction, 2022;

●           Nikiforov, A.L. Philosophy and history of science: Textbook. - Moscow.: Infra-M, 2018. - 384 p. (Russian)

●           Christopher Donohue and Charles T. Wolfe. Vitalism and Its Legacy in Twentieth Century Life Sciences and Philosophy (History, Philosophy and Theory of the Life Sciences, 29): 2022

Recommended:

●           Nikiforov, A.L. Philosophy and history of science: Textbook. - Moscow.: Infra-M, 2018. - 384 p. (Russian)

●           Kuzmenko, G.N. Philosophy and Methodology of Science: Textbook for Masters / - Moscow: Yurayt, 2016. - 450 p. (Russian)

●           Myrzaly S.K. History and philosophy of science. - Almaty: Bastau, 2014. (Kazakh)

●           Stepin V.S. History and philosophy of science. – Moscow: Academic Project, 2011. - 423 p. (Russian).

●           Khasanov M.Sh., Petrova V.F. History and philosophy of science. - Almaty: Kazakh University, 2013. - 150 p. (Russian)

●           Ostrovsky E.V. (2012) History and Philosophy of Science. UNITY-DANA, 160 p

●           Cover J.A., Curd M. and Pincock, C. (2012) Philosophy of Science: The Central Issues, 2nd edition. Norton. (English)

Mamchur E.A. The future of fundamental science. Conceptual, philosophical and social aspects (2011) URSS, Moscow (Russian)

Module designation

Foreign Language (professional)

Credit points

6 

Semester(s) in which the module is taught

2

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

3 hours per week for Seminar, total 45 Contact hours.

Person responsible for the module

Rustemova A.I., Teacher

Language

English 

Required and recommended prerequisites for joining the module

To study the discipline Foreign Language (Professional), an undergraduate student must have knowledge of grammatical and lexical material in the discipline "Foreign Language", as well as in the discipline "Professionally Oriented Foreign Language" during the 1st and 2nd year of study at the university.

Module objectives/intended learning outcomes

PO 1. understand the general content of professional and general informative texts  

PO 2. be able to logically, clearly and consistently express their thoughts in written and oral form, using the necessary grammatical and lexical means

RO 3. freely understand any spoken or background speech

RO 4. Justify and defend your point of view in a foreign language in discussions

RO 5. build a plan for writing resumes, descriptions of graphs, diagrams, processes and tables in a foreign language

Content

1. Reading formulas, mathematical symbols, chemical reactions and equations in English

1. Working with the text on specialty
2. Where would I like to use my knowledge as a future researcher?
3. Writing: procedure for describing graphs
4. How to describe a scientific process
5. When, While, If +ing (gerund constructions)
6. Green technologies in science (discussion)
7. The great discoveries of the 21st century
8. Adjectives for term description Writing: CV and formal letters
9. Do we need science in our life? (discussion

Examination forms

written examination

Reading list

1. physicists, chemists)

Module Objectives. Students will be able to:

1. describe the meaning of the basic concepts, concepts, tasks of higher school pedagogy, goals and content of higher professional education, explain the essence of a systematic, personality-oriented approach in education;

2. to determine the basic patterns of the emergence, development and functioning of the psyche and mental activity of a person and groups of people, to explain the specifics of methods of psychological research of an individual and a group of people;

3. classify teaching methods and control of academic achievements in higher education;

4. to substantiate the role and knowledge of the key concepts of pedagogical interaction technology as a condition for effective pedagogical activity;

5. classify the methods of research of psychological characteristics of personality, assessing its development in the perceptual, cognitive and emotional spheres;

6. identify cause-and-effect relationships when establishing patterns of detected phenomena;

7. to choose methods for the successful implementation of a systematic approach in education;

8. make diagnostic conclusions about the individual characteristics of the student

Module designation

Pedagogy of higher education

Credit points

3 

Semester(s) in which the module is taught

1

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Kudaibergenova Aliya, Candidate of Pedagogical Sciences, Senior Lecturer 

Language

Kazakh / Russian / English 

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

The purpose of this discipline Mastering the fundamentals of the professional and pedagogical culture of the teacher of higher education, familiarizing future teachers with the general problems, methodological and theoretical foundations of high school pedagogy, modern technologies of analysis, planning and organization of teaching and upbringing. 

As a result of mastering the discipline, the student is able to: 

●              to explain the general issues methodological and theoretical bases of pedagogy in higher education;  

●              to evaluate communication technologies subject-subject interaction of the teacher and the student in the educational process in higher school; 

●              analyze the system of higher professional education in Kazakhstan;  

●              to determine the content of higher education;  

to organize the learning process based on credit system of education in the higher school. 

Content

Lecture 1. The modern paradigm of higher education 

Lecture 2. History and modernity of higher professional education in Kazakhstan 

Lecture 3. Pedagogy as a science. Methodology of pedagogical science 

Lecture 4. Professional competence of a teacher of higher education 

Lecture 5 Communicative competence of a teacher of higher education 

Lecture 6 Holistic pedagogical process in the university: essence, content, structure 

Lecture 7 Didactics of higher education (theory of education at the university) 

Lecture 8. The content of higher professional education. 

Lecture 9. Traditional methods and forms of organizing training 

Lecture 10. Innovative methods and forms of education at the university. New educational technologies 

Lecture 11 Organization of independent work of students in the conditions of credit technology 

Lecture 12. The theory of scientific activity of higher education. NIRS 

Lecture 13 Technology for compiling teaching materials 

Lecture 14. Theory of education at the university. Higher School as a Social Institute for the Education and Development of a Specialist's Personality 

Lecture 15. Management in education 

Examination forms

Written examination: problem solving questions 

Reading list

1. Akhmetova G.K., Isaeva Z.A. Pedagogy: Textbook for Master's Degrees in Universities. - Almaty: Kazakh University, 2018. - 328 p.

2. Higher Education Pedagogy / Authors: Zh.R. Bashirova, N.S. Algozhaeva, U.B. Toleshova, A.Zh. Toybaev, K.B. Zhumabekov. – Almaty: Kazakh University, 2015

3. Mynbaeva A.K., Aitbaeva A.B., Kudaibergenova A.M. Fundamentals of Higher Education pedagogy: training manual. - 2016. - 236 b.

4. Mynbaeva A.K. Fundamentals of Pedagogy of Higher Education: Textbook. - Almaty, 2013. - 171 p.

5. Pionova R. Pedagogy of higher Education. - Minsk: University, 2002.

Module designation

Psychology of Management

Credit points

3 

Semester(s) in which the module is taught

2

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods  

communication technology; problem learning, critical thinking. Active and interactive forms of training, individual creative and analytical tasks, brainstorming, brainstorming, competition, quiz, decision tasks case; SWOT analysis. 

Workload (incl. contact hours, self-study hours)  

Total workload: 3 - 190 contact hours 

15 weeks, 

1 hour per week for Lecture, total 15 Contact hours. 

1 hour per week for Seminar, total 15 Contact hours. 

Contact hours (please specify whether lecture, exercise, laboratory session, etc.): lectures in the form of a mini-conference, video presentations, a traditional lecture and a heuristic conversation, the lecture is an INSERT. Seminars in the form of practical, discussion form, debates and other interactive types. 

Private study including examination preparation, specified in hours: independent work of a student and independent work under the guidance of a teacher - 60 

Person responsible for the module  

Sveta Berdibayeva (Doctor of Psychology, prof. in Kazakh)/ Maira Kabakova (Candidate of Psychological Science, Russian)/ Aidana Rizulla (PhD, in eng),  

Language  

Kazakh / Russian / English  

Required and recommended prerequisites for joining the module  

Prerequisite - Psychology at the Bachelor's degree 

Postrequisite – Foreign Language (professional) 

Module objectives/intended learning outcomes  

Analysis: carry out psychological analysis of management processes and phenomena; analyze and evaluate communication processes and processes of interpersonal perception in the organization through the application of system analysis and cross-cultural management techniques; Critically analyze the management performance of a manager based on a survey of management styles; analyze the professional activities of the manager in terms of ensuring his psychological effectiveness; 

Synthesis: factors affecting the effectiveness of the group, psychological methods of resolving conflict situations, psychological support for innovations; 

Evaluation: assess life and professional situations from the point of view of management psychology; Assess occupational risks in various management activities; 

Application:  

- interpret the processes of interpersonal perception, interpersonal and intercultural communication in the organization to maintain the corporate culture and psychological climate; 

- apply psychological technologies to regulation of emotional state, stress tolerance, personal growth, reduction of management conflicts, improvement of psychological climate and corporate culture; 

- apply skills of psychological selection of personnel, management decisions, methods of motivation of work; managing the organization's emotional environment 

Content  

Lecture 1. Introduction to management psychology 

Lecture 2. History of management psychology development 

Lecture 3. Theoretical and methodological foundations of management psychology. 

Lecture 4. Research methods in management psychology 

Lecture 5. Personality in management interaction 

Lecture 6. The identity of the leader as a subject of organization management. 

Lecture 7. Psychology of management decisions. 

Lecture 8. Motivational aspects of management. 

Lecture 9. Personality and building a business career in the organization. 

Lecture 10. Psychology of business communication and professional communication. 

Lecture 11. Psychology of interpersonal perception in the organization. 

Lecture 12. Psychology of intercultural communication. 

Lecture 13. Emotional management. 

Lecture 14. Psychology of management conflicts. 

Lecture 15. Corporate culture of the organization 

Examination forms  

The form of the exam is written - the solution of cases - grouped by the topic of situational and problematic problems. Case topics: 

1. The identity of the manager. 

2. Personality and business career 

3. Interpersonal and intercultural communication in the organization. 

4. Stereotypes of perception in the organization. 

5. Employee motivation problems. 

6. Management decision-making. 

7. Communicative barriers to business communication. 

8. Management conflicts.        

Reading list  

Module designation 

Pedagogical Practice

Credit points 

5 

Semester(s) in which the module is taught 

1 

Relation to curriculum 

UNIVERSITY COMPONENT   

PRACTICE 

Teaching methods 

- 

Workload (incl. contact hours, self-study hours) 

- 

Person responsible for the module 

Egyzbaeva M.K. associate professor

Language 

Kazakh / Russian  

Required and recommended prerequisites for joining the module 

Before teaching practice, undergraduates study the following disciplines: «Pedagogy of higher education», «Psychology of Management» 

Module objectives/intended learning outcomes 

The purpose of the pedagogical practice of magistracy studies is to prepare for scientific and pedagogical activities in a higher educational institution, to acquire and consolidate the skills of practical exercises for the implementation of the educational process in higher education, including the teaching of particular disciplines, the organization of educational activities of students, scientific and methodological work on the subject. In addition, in the course of teaching practice, a master's student should expand and deepen theoretical knowledge: 

- basic principles, methods and forms of organization of the pedagogical process; 

- methods of control and evaluation of professionally significant qualities 

students; 

- requirements for a university teacher in modern conditions.

- implementation of methodological work on the design and organization of the educational process; 

- speaking in front of an audience and creating a creative atmosphere in the course of classes; 

- analysis of difficulties arising in pedagogical activity and the adoption of an action plan to resolve them; 

- independent conduct of psychological and pedagogical research; 

- self-control and self-assessment of the process and result of pedagogical activity. 

- correct diagnosis of the pedagogical phenomenon; 

- skills are associated not only with the direct presentation of educational information but also with the methods of obtaining and processing it.  

- independently conduct classes according to the plan of the academic discipline (at least two lessons); 

- develop lecture notes for individual academic disciplines (at least one abstract); 

- form a methodological package for the chosen academic discipline; 

- accessible, taking into account the specifics of the subject, the level of preparedness of students, their life experience and age to present educational material; 

- using various teaching methods and their combinations, it is logically correct to build the process of teaching and learning information by students; 

- to formulate questions in an accessible, concise and expressive way; 

- effectively use technical training aids, visual aids, computer programs; 

- promptly diagnose the nature and level of learning by students of educational material; 

Content 

- 

Examination forms 

The student-trainee draws up the practice results in a written report, which he defends in the commission at the graduating department during the corresponding period of intermediate certification according to the academic calendar. The assessment of the student's internship results is equated to the theoretical training marks, is taken into account when considering the issue of awarding a scholarship, and when calculating the overall GPA and transferring it to the next year of study and entered in the statement of practice. The general results of the practice summarize at the Academic Councils of the faculties with the participation of representatives of the practice bases. The final grade for pedagogical practice gets rated by a commission, which includes teachers in pedagogy and psychology and the head of training from the graduating department. 

Reading list 

1. Afonin, I.D. Psychology and Pedagogy of Higher School / I.D. Afonin, A.I. Afonin. - M.: Rusayns, 2018. - 256 p. 

2. Gromkova, M.T. Pedagogy of Higher School: Textbook / M.T. Gromkov. - M.: Unity, 2017. - 80 p. 

3. Mukasheva A.B., Kasen G.A. Pedagogical practice in magistracy: guidelines. - Almaty: Kazakh University, 2011. - 84 p. 

4. Okolelov, O.P. Pedagogy of Higher School: Textbook / O.P. Okolelov. - M.: Infra-M, 2016. - 219 p. 

5. Stolyarenko, L.D. Psychology and Pedagogy of Higher School: Textbook / L.D. Stolyarenko. - Rn / D: Phoenix, 2014. - 336 p. 

Module Objectives. Students will be able to:

1. Describe the main criteria for the construction of nodes and elements of automation devices;

2. Distinguish the relationship between analog and digital control system units;

3. Identify key elements in the development of digital control systems based on sensors;

4. Apply the acquired theoretical knowledge in the field of control automation when working with sensor systems;

5. Use sensors for various purposes, in digital control systems;

6. Analyze the principles of construction of internal automation elements such as power, digital and sensor systems;

7. Develop basic electrical circuits with the integration of power devices and sensors with digital control;

8. Evaluate modern automation elements and devices and analyze their use in control systems.

Module designation

Power Electronic Devices and Systems

Credit points

6 

Semester(s) in which the module is taught

1

Relation to curriculum

ELECTIVE COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Kuttybay Nurzhigit, Senior lecturer, PhD 

Language

Kazakh / Russian / English 

Required and recommended prerequisites for joining the module

Knowledge of the main types and characteristics, structure, operating modes of power electronic devices and systems and analysis, calculation and assembly of electrical circuits

To investigate and find solutions to problems of increasing the energy efficiency of modern power systems, reliability of devices

Module objectives/intended learning outcomes

Upon completion of the training, students receive the following skills:

- Explaining the current state, achievements and problems of the branch of science of power electronics and production electronic systems;

- Be able to create new electrical circuits to solve problems of increasing energy efficiency and reliability of industrial electronic devices;

- Conducting experimental studies to modernize power devices and systems in accordance with modern requirements;

- To develop physical and mathematical models of processes and phenomena related to the object under study.

Content

1. The current state of power electronics. The use of power electronics devices in various industries: electric drives, electric power and power supply, lighting and electrical technology, transport and other areas.

2. Tasks and methods of research of power converters of electric power.

3. A systematic approach to the analysis of power converters of electric power.

4. Analysis of processes and control methods in power electronic devices.

5. Methods of analysis based on discrete transformations.

6. Phase and pulse control principles in power electronic devices.

7. Improving the quality of control of a pulsed power electronic device.

8. Application of fuzzy logic and neural networks to control power electronic devices.

9. Methods of computer modeling of power electronic devices.

10. Analysis of converters with network switching: rectifiers, inverters, frequency converters and variable voltage regulators.

11. Classification and control methods of reversible, non-reversible and direct DC converters.

12. Pulse width modulation in AC/DC converters.

13. Resonant converters in power electronic devices.

14. Modular, multi-level and cell converters in power electronic devices.

15. Devices that improve energy performance and quality of electrical energy

Examination forms

Written examination

Reading list

1. Opadchy Yu.F., et al. Analog and digital electronics (Full course) Textbook for universities. /edited by O.P. Gludkin. – M.: Hotline – Telecom, 2007.
2. Hart D. W. Power electronics. – Tata McGraw-Hill Education, 2011.
3. Tietze U., Schenk C., Gamm E. Electronic circuits: handbook for design and application. – Springer, 2015.
4. Belous A., Turtsevich A., Efimenko S. Semiconductor power electronics. – Litres, 2021.
5. Charles Platt. "Electronics for beginners" BHV-Petersburg, 2012, 480 p.

Module designation

Sensors and sensor systems

Credit points

9 

Semester(s) in which the module is taught

2 

Relation to curriculum

ELECTIVE COMPONENT 

Teaching methods

lecture, seminar 

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Nalibayev Yerkebulan, senior lecturer, PhD

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Postrequisites: Industrial IoT

Module objectives/intended learning outcomes

-          Analyze transfer function of the sensors and formation mathematical models of sensors

-          Estimating sensors with accuracy and calibration errors

-          Demonstrate knowledge in the state of the art of sensors for a wide range of applications in research and commercial products;

-          Analyze findings for synthesis big sensor systems

Content

1. Sensors and Sensor Systems and Sensor Classification
2. Metrology - Measurement in detail
3. Transfer Function of the sensors: Mathematical Model, Functional Approximations Polynomial Approximations etc.
4. Dynamic Models of Sensor Elements
5. Calibration, Calibration Error and accuracy
6. Computation sensors stimulus from Linear Piecewise Approximation and Iterative Computation of Stimulus (Newton Method)
7. Temperature measurement techniques: Temperature and Thermal Properties of Materials
8. Inductive and Magnetic Sensors: LVDT and RVDT
9. Microelectromechanical sensor (MEMS) instrumentation: Strain gauges, piezoelectric sensors and actuators, capacitive sensor interfaces
10. FET based sensors: MOSFET revision, FET based biological and chemical sensors
11. Overview of optical sensors: CCD Sensor and CMOS-Imaging Sensors
12. Lidar Sensing and Coherent Imaging Research
13. Nanosensors: nanowire sensors, nanotube sensors
14. Wireless sensor interfaces: Sensor networks and wireless power
15. Design wireless sensor systems for industrial factory

Examination forms

Written examination

Reading list

1. Gol'dshteyn, A.Ye. The physical basis of obtaining information : textbook for applied bachelor's degree. — Moscow: Publisher: Yurayt, 2018. — 291 p.
2. Vavilov V.D., Timoshenkov S.P., Timoshenkov A.S. microsystem sensors of physical quantities: monograph /— Moscow : Tekhnosfera, 2018. — 550p.
3. Radionov YU.A. microelectronic sensors and sensor devices. Study guide./ BGUIR.2019. 300 p.
4. Sensor electronics, sensors. solid-state sensor structures based on silicon : study guide for universities/ E. P. Domashevskaya [i dr.] ; edited by A. M. Khoviva. — Moscow : Publisher Yurayt, 2022. — 203 p.
5. Charl'z Platt. «Electronics for beginners» BKHV-Peterburg, 2012, 480 p.
6. Seong-Eun Yoo, Taehong Kim, Industrial Wireless Sensor Networks: Protocols and Applications, - Mdpi AG 2020, 132p.
7. Christos Koulamas, Mihai T Lazarescu, Real-Time Sensor Networks and Systems for the Industrial IoT. - Mdpi AG 2020, 242p.

Module Objectives. Students will be able to:

1. Be able to apply various methods of machine learning to solve tasks, as well as evaluate the result;

2. Use modern software packages for modeling artificial neural networks and machine learning mechanisms;

3. Apply machine learning methods in the construction of neural networks designed for intelligent control systems;

4. Analyze the principles of building modern intelligent control systems based on deep neural networks;

5. Systematize the main methods of creating and training control systems with adaptive mechanisms;

6. Compare nonlinear and adaptive control systems with control systems based on neural networks to identify the strengths and weaknesses of each of them;

7. Develop a neural network for solving control problems and train it using machine learning;

8. Evaluate the capabilities of modern intelligent control systems and classify them by type of construction.

Module designation

Neural networks and machine learning mechanisms

Credit points

6

Semester(s) in which the module is taught

1

Relation to curriculum

ELECTIVE COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Kozhagulov Yeldos, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Post- requisites - Deep neural networks

Demonstrate knowledge of the basics of artificial intelligence, machine learning and deep learning.

Apply knowledge about the analysis, testing and modeling of machine learning methods in research.

Module objectives/intended learning outcomes

Upon completion of the training, students receive the following skills:

- Explain modern machine learning methods;

- Understanding the principles of machine learning methods and their application in the field of artificial intelligence;

- Be able to develop machine learning and deep learning models based on the Scikit Learn library;

-Analyze and shape data for classification and regression

-Develop modern learning methods for neural networks

Content

1. Basic principles, tasks and approaches, use in various fields of science and industry
2. Methods for extracting signs of signals.
3. Metric classifiers.
4. Clustering Algorithms
5. Making predictions about the future based on supervised learning.
6. Solving interactive problems based on reinforcement learning.
7. Finding Hidden Structures with Unsupervised Learning.
8. Regression analysis. Linear regression. Polynomial regression. Bias and dispersion. Ridge regression.
9. Perceptron and separating hyperplane. Transition to a higher-dimensional space. Support vector machine.
10. Rules and Quality Analysis. Analysis using the ROC curve.
11. Combining Models for Ensemble Learning Methods.
12. Principal component method.
13. Diversity based learning.
14. Mixtures of Gaussian distributions.
15. Neural networks and deep learning.

Examination forms

Written examination

Reading list

1. Plas D. V. Python for complex tasks. Data science and machine learning. St. Petersburg: Peter. – 2018.
2. Muller A., Guido S. Introduction to Machine Learning using Python //A guide for data specialists. St. Petersburg: “Alfa-book” – 2017.
3. Rashka S. Python and machine learning. - Liters, 2022.
4. Khaykin S. Neural networks: a complete course, 2nd edition. – Williams Publishing House, 2008.

Module designation

Deep neural networks

Credit points

9

Semester(s) in which the module is taught

2

Relation to curriculum

ELECTIVE COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Kozhagulov Yeldos, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Pre-requisites – Neural networks and machine learning mechanisms.

Post- requisites - Intelligent multi-agent systems

Demonstrate knowledge of the basics of artificial intelligence, machine learning and deep learning.

Apply knowledge about methods of analysis, testing and modeling of deep neural networks in research and calculations.

Module objectives/intended learning outcomes

Upon completion of the training, students receive the following skills:

- Knowledge of modern neural network architectures and machine vision applications;

- Understanding the principles of neural networks and learning algorithms;

- Be able to implement and train neural networks based on Python neural network libraries;

- Have data processing skills to train a neural network;

- Know how to design an intelligent system.

Content

1. Introduction to neural networks. Basic architecture of neural networks.
2. Training of a neural network using an error back propagation algorithm.
3. Practical aspects of neural network training. Widely used optimizers.
4. Penalty-based regularization.
5. Common neural network architectures.
6. Networks of radial-basis functions.
7. Recurrent neural networks. Architecture of recurrent neural networks.
8. Long short-term memory (LSTM).
9. Managed recurrent blocks.
10. Convolutional neural networks. The basic structure of the convolutional network.
11. Convolutional network training.
12. Examples of typical convolutional architectures: AlexNet, VG, GoogLeNet, ResNet.
13. Deep reinforcement learning.
14. Basics of auto-coding. Variational autocoding.
15. Generative-adversarial networks.

Examination forms

Written examination

Reading list

1. Khaykin S. Neural networks: a complete course, 2nd edition. – Williams Publishing House, 2008.
2. Aggarwal Ch. Neural networks and deep learning: a training course //Saint Petersburg: Dialectics LLC. – 2020.
3. Michelucci U. Applied Deep learning //An approach to understanding deep neural networks based on the case method: Persian ang-St. Petersburg "BHV-Petersburg. - 2020.
4. Francois S. Deep learning in Python. – " Publishing House" " Peter", 2018.

Module Objectives. Students will be able to:

1. formulate goals and objectives of scientific research in the field of automatic control, choose methods and means of solving scientific and technical problems of automation and control

2. analyze the results of theoretical and experimental studies, make recommendations for improving automatic control devices and systems

3. organize and carry out scientific and research design and technological activities for the design and development of control systems

4. analyze scientific and technical documentation, summarize domestic and foreign experience in the field of electronics and automatic control systems

5. apply the methods of the theory of automatic control of nonlinear and adaptive systems in the design of automated control systems

6. carry out mathematical modeling of physical and technological processes in automatic control systems using modern technologies

7. develop models of the processes under study in automated systems and apply them to determine the optimal options for design, engineering and technological solutions

8. plan all stages of project development, starting from the development of the concept and technical tasks of the project, to the creation of a prototype and the completion of the project

Module designation

Organization and Planning of Scientific Research (in English)

Credit points

6

Semester(s) in which the module is taught

1

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Ryspayeva Maiya, PhD, Senior Lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Pre-requisites - Foreign Language

Post– requisites - Dissertation Writing, Research Seminar

Module objectives/intended learning outcomes

Students will:

- know the definition of science, research, experiment, information and facts.

- be able to understand different methods of research

- be able to classify scientific approaches of research

- be able to analyze scientific information

- be able to apply methods of research for organization and planning scientific research according the theme of master’s thesis

Content

1. Introductory lecture. Actuality of master’s thesis.

2. Structure of master’s thesis. Requirements to thesis. Literature review.

3. Definition of science, research and experiment. Science as a system, its distinctive features and structure. Aims and tasks of science.

4. Object and subject of research. Analysis and synthesis. Classification of types of research activities.

5. Types of information sources. Scientific facts. Principle of operation with facts. Domestic and foreign research according to the topic of the thesis.

6. Notion of scientific problem. Purpose of research. Hermeneutical circle. Hypothesis. Requirements to hypothesis.

7. Systematic and dialectic approach to study an object. Scientific paradigm.

8. Empirical method. Thinking and logical method of research. Correlation regression analysis. Correlation regression analysis.

9. Graphical methods of scientific research. Ishikawa diagram. Ishikawa diagrams to identify potential factors causing an overall effect
10. Mathematical methods of research. Differential calculation. Patent research.

11. Monte- Carlo method. History of Monte-Carlo method. Copyright and plagiarism.

12. Planning and prediction of scientific research. Essays and articles. Scientific seminar.

13. Ethics in scientific research. Principles of scientific ethics.

14. Principles of scientific polemic. Criticism. Plan of master’s thesis. Main results of the thesis.

15. General requirements for essays and reports.

Examination forms

The final examination is in the form of a Test in the DLS Moodle system. The number of test questions during the exam is 25 questions. Test time is 60 minutes, online proctoring with AERO.

Examples of test questions:

1. Systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe

a)       Research

b)       Science

c)       Hypothesis

2. Master's dissertation is a graduation work of students that contains independent scientific research, theoretical and/or practical developments of actual problems in the selected field of science.

a) true

b) false

Reading list

1. Kozhukhar V.М. Fundamentals of Scientific Research: Textbook. – М.: Dashkov&Co, 2010. – 216 pages.

2. Bui Y.N. How to write a master’s thesis. SAGE Publications, Inc.; Second edition. – 2013. 336 p.

3. Peter Pruzan. Research Methodology. The Aims, Practices and Ethics of Science. Springer. - 2016. 331 p.

4. Alexander M. Novikov, Dmitry A. Novikov. Research Methodology, 2013 by Taylor & Francis Group, LLC. 130 p.

5. Kauchak, D. Learning and teaching: research based methods. –Boston: Allyn and Bacon, 1989. – 473 pages.

6. Dipankar Deb, Rajeeb Dey, Valentina E. Balas.Engineering Research Methodology. A Practical Insight for Researchers, Springer. 2019. 113 p.

Module designation

Nonlinear and adaptive control systems

Credit points

6

Semester(s) in which the module is taught

1

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Japashov Nursultan, senior lecturer, PhD

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Pre-requisites - Automatic control systems, Optimal systems (bachelor)

Knowledge of the main types and characteristics, modes of operation of modern adaptive control systems

Analysis, calculation and assembly of adaptive control systems using modern methods of designing nonlinear and adaptive circuits.

Module objectives/intended learning outcomes

During the course of studying the discipline, students will be able to:

- explain Lyapunov stability theory and dissipation theory;

- analyze the existence and uniqueness of solutions of nonlinear differential equations;

- characterize passivity and non-expansiveness similarly to positive real and limited real systems;

- develop adaptive control laws for nonlinear systems.

Content

10.  Creation of self-regulating systems based on the dynamic properties of the control object using a characteristic analyzer.

11.  Modeling of self-regulating systems with methods of indirect determination of frequency characteristics.

12.  Modeling of searchless self-regulating systems.

13.  Non-traceable self-regulatory systems that follow the use of the object model.

14.  The use of identification methods in modeling searchless adaptive systems.

15.  Modeling of an adaptive control system using special approaches to the creation of searchless automatic systems.

Examination forms

Written examination

Reading list

1. Gaiduk A.R., Plaksienko E.A., Adaptive control systems, 2018, pp. 6-92.

2. Evsyukov V.N., Nonlinear automatic control systems: a textbook for university students/ Evsyukov V.N.-Orenburg State University of OSU, 2007, - 172 p

3. Panteleev A.V., Rudenko E.A., Bortakovsky A.C, Nonlinear control systems: description, analysis and synthesis/ - M.: University Book. 2008, -312 p

4. Kim D.P., Theory of automatic control: multidimensional, nonlinear, optimal and adaptive systems, 2018, -312 p.

5. Kim D.P., Collection of problems on the theory of automatic control. Multidimensional, nonlinear, optimal and adaptive systems. - M.: FIZMATLIT. 2008, - 328 pages.

6.   Fradkov A.L, Miroshnik I.V, Nikiforov V.O, Nonlinear and Adaptive Control of Complex Systems, pp 25-381.

7.   Sundarapandian Vaidyanathan Christos Volos, Advances and Applications in Nonlinear Control Systems, 2016, pp 215-428.

8.   Panteleev A.V., Optimal nonlinear control systems: synthesis with incomplete information / - M.: University Book, 2008, -192 p

9. Egorov A.I., Fundamentals of control theory, 2007, 132-354 p.

10. Adambayev M, Theory of Automatic Control, 2015, -152 p.

Module designation

Modern methods of project management in engineering

Credit points

6

Semester(s) in which the module is taught

2

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Saymbetov Akhmet, PhD, Associate Professor

Isa Hasanovich, PhD, Associate Professor

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

- analyze the main methodological approaches in the field of project management

- evaluate the basic procedures and methods of project management and preparation of project solutions

- analyze the conclusions and measures for the implementation of the developed projects

- synthesis of proposals for improving existing and developing projects

Content

1. The evolution of project management. Basic terms of project management

2. Popular approaches and methods of project management

3. Project management content and processes

4. Methodology and methodology of pre-project analysis

5. Methodology of project concept development

6. Methods of description and analysis of goals

7. Methodology for the development of the terms of reference and the sketch of the project

8. Allocation of resources in scientific projects

9. Calendar planning methods: time, cost and resource analysis

10. Methods of project analysis at the development stage.

11. Methods of functional and cost analysis, risk accounting, reliability

12. Stimulating the performers of scientific projects

13. Completion of the project. Analysis of data on the planned and actual progress of projects.

14. Evaluation of the results of completed projects

15. Problems of scientific project management in higher education institutions

Examination forms

written examination

Reading list

1. Matveeva L. G. Project management : textbook / L. G. Matveeva. Rostov n/A : Phoenix, 2009. 423 s

2. Mazur I. I. Project management / I. I. Mazur, V. D. Shapiro, N. G. Alderroge. M. : Ekonomika, 2003. 245 p.

3. Biafore B. Microsoft Project. 2013 / B. Biafore. The Missing Manual PDF O’Reilly Media. 2013. 812 p.

4. M.L. Razu, T.M. Bronnikova, B.M. Razu, S.A. Titov. Project management. Fundamentals of Project Management: Textbook / Under the general editorship of Prof. M.L. Razu.. - Moscow: KnoRus, 2012. - 760 p.

5. Zub, A. T. Project management: textbook and workshop for universities / A. T. Zub. – Moscow : Yurayt Publishing House, 2021. – 422 p.

6. S. A. Mamontov, N. M. Glebova. Marketing project management at the enterprise: textbook — Moscow : INFRA-M, 2019. — 174 p.

7. Yu. I. Popov, O. V. Yakovenko. Project management: textbook – Moscow: INFRA-M, 2021. – 208 p.

8. Heldman, K. Professional project management. 5th ed. / K. Heldman, W. Heldman. - M.: Binom. Laboratory of Knowledge, 2012. - 728 p.

Module Objectives. Students will be able to:

1. Explain the design and creation of modern embedded systems used in control systems;

2. Formulate the main criteria for the use of embedded systems in various fields of electronics;

3. Use modern digital technologies and appropriate software to solve technical problems of production;

4. Apply low-level programming languages when designing applications based on embedded systems;

5. Analyze embedded systems and its internal components to determine the degree of their reliability;

6. Design embedded systems based on microcontrollers and FPGAs, depending on the complexity of the task and the scope of application;

7. Develop control units based on embedded systems using microcontrollers and FPGAs;

8. Evaluation of microprocessors and design tools used for the development of modern embedded systems.

Module designation

Design of embedded control systems

Credit points

9

Semester(s) in which the module is taught

3

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Akhtanov Sayat, senior lecturer, PhD

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Knowledge of the basics of programming algorithms and design of logic electronic circuits on microprocessor systems.

Module objectives/intended learning outcomes

Upon completion of the training, students receive the following skills:

- knowledge of the main types of embedded control systems and computing systems designed for monitoring and managing physical objects.

- possess the skills of designing finite state machines based on programmable logic controllers and integrated circuits, widely used in industry.

- be able to analyze and evaluate the required performance with a minimum amount of equipment for control systems.

Content

1. Introduction into embedded control systems
2. Сommon features and requirements for embedded control         systems
3. Methodologies of design of embedded control systems
4. Platform-based design of embedded systems
5. Hardware and software to be used in the embedded systems
6. Fundamentals of digital control
7. Implementation and computational algorithms in embedded systems
8. Design with field programmable gate arrays.
9. Implementing control algorithms with field programmable gate arrays and microcontrollers.
10. Programmable logic controllers
11. Finite state machines
12. Conversion between analog and digital forms
13. Constructing transfer function of a system
14. Transfer function based controller design
15. Advanced applications. Nonlinear control. Robust control.

Examination forms

Written examination

Reading list

1. A. Barkalov, L. Titarenko, M. Mazurkiewicz, Foundations of еmbedded systems.- Springer. - 2019 . – 167 p.
2. C. Unsalan, D. E. Barkana, H. D. Gurhan, Embedded digital control with microcontrollers: implementation with C and Python, John Wiley & Sons.- 2021. – 368 p.
3. R. Kamal, Embedded Systems - SoC, IoT, AI and real-time systems, McGraw Hill Education (India) Private Limited.- 2020. - 598 p.
4. R. Hu, Embedded system development process: plan, design, integrated development, and design verification. - Independently Published.- 2021.- 256 p.
5. E. M. David, Hand-on embedded system architecture: introduction to robotics and the AVR microcontroller practical guide for students and professionals.- Amazon Digital Services LLC - KDP Print US.- 2021.-88 p.
6. J. R. Raol, R. Ayyagari, Control systems: classical, modern, and AI-based approaches.- CRC Press. 2019. – 668 p.
7. J. W. Valvano, Embedded systems: introduction to robotics, Independently Published.- 2019.- 494 p.

Module designation

RESEARCH PRACTICE

Credit points

4

Semester(s) in which the module is taught

3

Relation to curriculum

UNIVERSITY COMPONENT

Teaching methods

Workload (incl. contact hours, self-study hours)

Person responsible for the module

Sagidolda Erulan, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

Improving the level of training of masters through the development of methods, techniques and skills in the process of teaching, the development of their creative abilities, independence, initiative in studies and future activities.

- Apply deep scientific and mathematical knowledge to solve scientific and engineering problems in the field of analysis, synthesis, design, production and operation of automation and control systems of technical objects

- Be able to process, analyze and summarize scientific and technical information, advanced domestic and foreign experience in the field of theory, design, production and operation of automation and control systems for technical facilities, take part in teams for the development and operation of such systems.

- Apply the acquired knowledge to solve innovative engineering problems in the development, production and operation of modern automation and control systems

- Plan and conduct analytical, simulation, experimental research and mathematical modeling for design purposes

Content

1. Scientific and methodological foundations of the implementation of research practice, an idea of the methods of scientific modeling and evaluation of the effectiveness of the obtained research results;
2. Planning of scientific research;
3. Techniques of presentations with scientific reports, reports, opposition;
4. Methods and procedures for working with diverse arrays of scientific information, scientific literature and other sources in printed and electronic forms;
5. Scientific and bibliographic works, annotations, abstracts;
6. Software tools for the formation and statistical processing of research data arrays;
7. Practical steps of empirical research;
8. Culture of speech, argumentation of public speeches, consulting, negotiation;
9. Language training, acquisition of skills of professionally-oriented foreign language proficiency;
10. Computer technology in solving research tasks;
11. Standards and rules for the preparation of manuscripts of scientific papers for publication;
12. Preparation of abstracts and reports, writing scientific articles in accordance with the requirements for the design of the scientific reference apparatus of research and maintaining scientific documentation

Examination forms

written examination

Reading list

1. Ermachenko, Nadezhda Ivanovna. Fundamentals of scientific research: theoretical and methodological approach / N. I. Ermachenko. — Krasnoyarsk: Siberian Institute of Business, Management and Psychology, 2012. — 119 p.
2. Zhuravleva, Elena Yurievna. Internet-research: essence, structure and methods / E. Y. Zhuravleva ; Sev.-Zap. Academy of Public Services, Phil. Sev.-Zap. Academy of Public Services in Vologda. — Vologda : Phil. SZAGS, 2009. — 223 p.
3. Zakharov A.A. How to write and defend a thesis / A. A. Zakharov, T. G. Zakharova. — St. Petersburg: "Peter", 2006. — 160 p.
4. Ilyin, Alexander Alekseevich. The procedure for preparing and submitting dissertations for defense: [educational and methodological textbook for postgraduates, doctoral students and applicants] / A. A. Ilyin, S. Yu. Belyan, Yu. A. Moskvichev; Ministry of Education and Science of the Russian Federation, Yaroslav State Technical University. un-T. — Yaroslavl : YAGTU, 2011. — 72 p.
5. Ippolitova, Natalia Viktorovna. Methodology and methods of scientific research : studies. manual / Ippolitova N. V., Sterkhova N. S. ; Shadrin. gos. ped. in-t, Center "Continuous ped. education". — Shadrinsk : Shadrinsky House of Printing, 2011. — 208 p.
6. Ishkova, Lyudmila Viktorovna. Fundamentals of scientific research: general methodology and private methods: textbook for organizers of scientific work, students, postgraduates: [on the discipline "Fundamentals of scientific research"] / L. V. Ishkova; Novokuznetsk. phil. un-t Kemer. state University. — Kemerovo: Kuzbassvuzizdat; Moscow: Russian University, 2005. — 250, [1] p.
7. Kashirin, Vladimir Petrovich. Theory of scientific research / V. P. Kashirin; The Ministry of Agriculture of the Russian Federation, Krasnoyar. state agrarian. un-t, Sib. in-t of science studies. — Krasnoyarsk : Publishing house of the Krasnoyar State Agrarian. un-t, 2007. — 184 p.

Module Objectives. Students will be able to:

1. Explain the features of different types of neural networks for the implementation of intelligent control systems;

2. Apply methods of training and automatic adjustment of parameters of intelligent control algorithms;

3. Use mathematical, software and technical devices for the implementation of intelligent control systems;

4. Analyze the advantages and disadvantages of neural network methods in comparison with other management methods;

5. Design multi-agent systems to optimize the decision-making process in production;

6. Design data processing and analysis systems for solving recognition, forecasting and management tasks;

7. Design neural network process control systems;

8. Develop automated control and data processing systems based on neural network technologies.

Module designation

Intelligent data processing systems

Credit points

9

Semester(s) in which the module is taught

3

Relation to curriculum

ELECTIVE COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Zhexebay Dauren, senior lecturer, PhD

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Definition of intelligent systems, the structure of static and dynamic expert systems

Theoretical foundations for the construction and operation of applied intelligent systems and decision support systems, key areas of application of new information systems in automating managerial decision-making processes

Methods for constructing the operation and development of intelligent systems

Theory of artificial intelligence technologies

Module objectives/intended learning outcomes

Upon completion of the training, students receive the following skills:

●       Search for the necessary sources of information and data, perceive, analyze, memorize and transmit information using digital means, as well as using algorithms when working with data received from various sources in order to effectively use the information received to solve problems; evaluate information, its reliability, build logical conclusions based on incoming information and data.

●       Able to put into practice new scientific principles and research methods

●       Possess data processing skills for classification and regression;

●       Organizational and technological support for the design and design of artificial intelligence

Content

1.   The nature of data and modern data analysis tools.

2. Data types and various file formats.

3.     Stages of data analysis.

4. Database management system for big data analysis.

5. Statistical methods of data mining.

6.     Methods of data mining.

7. Knowledge Discovery in Data Mining.

8.     Classification. Cluster analysis.

9.     Association. Decision tree induction.

10.   Deep learning and visualization in data analysis.

11.   Data Analysis Using K-Means Clustering Algorithm.

12.   Data Mining Using Hadoop Cluster.

13. Analytics of learning in education.

14.   Image pre-processing methods.

15. Texture feature extraction methods for image recognition.

Examination forms

Written examination

Reading list

1.     Gupta D. et al. (ed.). Intelligent Data Analysis: From Data Gathering to Data Comprehension. – John Wiley & Sons, 2020.

2.     Chaki J., Dey N. A beginner’s guide to image shape feature extraction techniques. – CRC Press, 2019.

3.     Chaki J., Dey N. A beginner's guide to image preprocessing techniques. – CRC Press, 2018.

4.     Chaki J., Dey N. Texture feature extraction techniques for image recognition. – Springer Singapore, 2020.

Module designation

Intelligent multi-agent systems

Credit points

9

Semester(s) in which the module is taught

3

Relation to curriculum

ELECTIVE COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Zhexebay Dauren,senior lecturer, PhD

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Neural networks and machine learning mechanisms

Deep neural networks

Demonstrate knowledge of the basics of artificial intelligence, multi-agent systems

Application of knowledge on the implementation of intelligent multi-agent systems in scientific research

Module objectives/intended learning outcomes

Upon completion of the training, students receive the following skills:

- Knowledge of the basic properties of agents and their environment;

- Understanding the principles of the agent when solving problems through search;

-   Be able to create agents capable of forming their own ideas about a complex world;

-   Know algorithms for reasoning agents under uncertainty;

-   Know how to design an intelligent multi-agent system.

Content

1.     Introduction to artificial intelligence. History and current state of artificial intelligence.

2.     Intelligent agents. rational agents.

3.     Environment properties for the agent.

4.     Agents with simple reflex behavior. Agents with model-based behavior.

5.     Agents acting on the basis of purpose and utility.

6.     Learning agents.

7.     Agents that solve problems through search.

8.     Logical agents. Knowledge based agents.

9.     Ontological engineering.

10.   Automated planning.

11. Action of an agent under conditions of uncertainty. Probabilistic reasoning.

12. Making simple and complex decisions.

13. Decision making in the presence of several agents.

14. Properties of a multi-agent environment.

15. Making collective decisions.

Examination forms

Written examination

Reading list

1. Russell S., Norvig P. Artificial intelligence. A modern approach. Volume I. Solving problems: knowledge and reasoning //Moscow: Williams. – 2021. - 704.

2. Russell S., Norvig P. Artificial intelligence. A modern approach. Volume II. Knowledge and reasoning in conditions of uncertainty //M: Williams. – 2021. – 480.

3.     Wooldridge M. An introduction to multiagent systems. – John wiley & sons, 2009. (https://cgi.csc.liv.ac.uk/~trp/COMP310.html)

Module Objectives. Students will be able to:

1. Explain the architecture and principle of operation of automated control systems;

2. Apply theoretical and practical methods of creating and implementing automated control systems;

3. Use software and mathematical tools to create automated control systems;

4. Use modern information technologies to create industrial automation systems and production applications;

5. Develop software for distributed control systems, using the appropriate software;

6. Design and develop industrial applications using ready-made hardware and software solutions;

7. Develop documentation of an automated dispatch control system for operation and maintenance;

8. Organize the smooth operation of the technological process and the safety of the system using an intelligent automated control system.

Module designation

Distributed control systems

Credit points

9

Semester(s) in which the module is taught

3

Relation to curriculum

ELECTIVE COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Nurgaliyev Madiyar, Senior lecturer, PhD

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Knowledge and understanding of the design stages of automation and control systems;

Analysis of physical processes occurring in automated systems.

Module objectives/intended learning outcomes

Upon completion of the training, students receive the following skills:

- Knowledge of modern achievements in the field of automation of control systems;

- Understanding of the principles of building modern distributed process control systems;

- Analyze and synthesize the logic of programmable logic controllers for automation of distributed control systems;

- Have the skills to design the architecture of communication systems and interfaces for agent interaction in distributed control systems;

- Design of SCADA computer control systems.

Content

1. Introduction to the architecture of computer measurement and control systems and the human-machine interface.
2. Modern programmable logic controllers for distributed automation and control systems.
3. Evolution, architecture and basic principles of distributed control systems.
4. SCADA systems for automated remote data collection.
5. Architecture and algorithms of a programmable logic controller.
6. Basic configurations of a programmable logic controller for a distributed control system.
7. Communication systems for distributed control systems and SCADA systems.
8. Algorithmization and programming of controllers of modern distributed control systems.
9. Security system in distributed control systems.
10. Notification systems in distributed control systems.
11. Configuration of distributed control systems.
12. Requirements for project documentation of distributed control systems.
13. Distributed control systems used in modern automated enterprises.
14. Stages of implementation of project documentation of the distributed control system in production.
15. Technological, economic, environmental and social effects of the introduction of automated and robotic production.

Examination forms

Written examination

Reading list

1. Webb, John. "Ronald. R, Programmable Logic Controllers Principle and Applications." (1995).
2. Petruzella, Frank D. Programmable logic controllers. Tata McGraw-Hill Education, 2005.
3. Benítez-Pérez, Héctor, and Fabian Garcia-Nocetti. Reconfigurable distributed control. Berlin: Springer, 2005.
4. Stouffer, Keith, Joe Falco, and Karen Ann Kent. Guide to Industrial Control Systems (ICS) Security: Supervisory Control and Data Acquisition (SCADA) Systems, Distributed Control Systems (DCS), and Other Control System Configurations Such as Programmable Logic Controllers (PLC): Recommendations of the National Institute of Standards and Technology. US Department of Commerce, National Institute of Standards and Technology, 2008.

Module designation

Industrial IoT

Credit points

9

Semester(s) in which the module is taught

3

Relation to curriculum

ELECTIVE COMPONENT

Teaching methods

lecture, seminar

Workload (incl. contact hours, self-study hours)

15 weeks,

1 hour per week for Lecture, total 15 Contact hours.

2 hours per week for Seminar, total 30 Contact hours.

Person responsible for the module

Nalibayev Yerkebulan, senior lecturer, PhD

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Use modern digital data transmission systems to create wired and wireless communication channels using the Internet of Things technology in automated control systems.

Analysis, calculation and assembly of industrial systems based on IoT technology.

Module objectives/intended learning outcomes

- Knowledge of the main technologies and use cases of the Industrial Internet of Things.

- build a reliable and efficient IoT infrastructure at the industry and enterprise level.

-analyze and evaluate industrial processes and specialized IoT control devices.

-develop industrial devices related to the processing of confidential information, cybersecurity.

Content

1. Preliminaries, overview, design principles and challenges of industrial IoT (IIoT).
2. IoT-driven advances in industrial building
3. Industry 4.0: Basics. Automation trends in industrial networks and industrial IoT.
4. Industrial processes, devices and protocols
5. Models and reference architecture of IIoT
6. Get to grips with popular cloud-based platforms
7. Architecture modeling of industrial IoT systems
8. Blockchain mechanisms as security-enabler for industrial IoT applications
9. Design and implement the industrial IoT network flow
10. Implement equipment and process management
11. Implementation of industrial IoT in the renewable energy sector
12. Diagnostic analytics to answer critical workforce questions
13. Technology trade-offs for IIoT systems and applications.
14. Plant safety and security of IIoT
15. Manufacturing industry, automotive industry, mining industry application of IIoT.

Examination forms

Written examination

Reading list

1. I. Butun, Industrial IoT: сhallenges, design principles, applications, and security.-Springer Nature.- 2020. - 241 p.
2. G. Veneri, A. Capasso, Hands-on industrial internet of things: create a powerful industrial IoT infrastructure using industry 4.0.- Packt Publishing.- 2018. - 556 p.
3. Z. Mahmood, The internet of things in the industrial sector: security and device connectivity, smart environments, and industry 4.0.-Springer.- 2019. - 326 p.
4. M. Stremlow, Industrial internet of things: create a powerful industrial IoT infrastructure using industry 4.0: chemical process safety.-Independently Published.- 2021. - 64 p.
5. A. Suresh, M. Nandagopal, P. Raj, E. A. Neeba, J.-W. Lin, Industrial IoT application architectures and use cases.-CRC Press.- 2020. - 204 p.
6. N. Malarvizhi, Industrial IoT application architectures and use cases.-Auerbach Publishers, Incorporated.- 2020. - 182 p.
7. S. Bhattacharjee, Practical industrial internet of things security: a practitioner's guide to securing connected industries.-Packt Publishing Ltd.- 2018. - 324 p.

Module Objectives. Students will be able to:

1. have an idea of modern methods of solving research and professional problems;
2. know the general theoretical foundations of the formation of scientific research and the formulation of scientific research
3. freely navigate in the choice of experimental research methods;
4. formulate and solve research tasks;
5. analyze the results obtained and apply them in practice;
6. acquire practical skills in organizational and managerial, design and research activities
7. plan, structure and create scientific texts
8. have the ability to conduct qualified scientific research

Module designation

Research Seminar

Credit points

3

Semester(s) in which the module is taught

1/2/4

Relation to curriculum

Teaching methods

Workload (incl. contact hours, self-study hours)

Person responsible for the module

Sagidolda Erulan, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

Familiarization of students with the basic provisions of science and the basics of research work

- The ability to conduct qualified scientific research

- Analyze the methodological side of research activities, methodically competently organize and conduct scientific research

- Possess the skills of describing the object and subject, goals and objectives, determining the plan and methodology of the study;

- Possess the skills of using theoretical knowledge in the field of electronics and control systems

Content

1. Science and scientific research. The concept of science. Classification of sciences.
2. Scientific research: concept, types, levels and their components. Stages of research work
3. The teacher as the organizer of the scientific process at the university
4. The concepts of the method and methodology of scientific research. Philosophical and general scientific methods of scientific research.
5. Choosing the topic of scientific research. Development of a task to perform scientific research.
6. The main sources of scientific information.
7. Structure of the master's thesis.
8. Work on the content of the master's thesis. Ways of writing a scientific text
9. Presentation of the results of legal research. Participation in scientific research conferences

Examination forms

written examination

Reading list

1. Ilyin, Alexander Alekseevich. The procedure for preparing and submitting dissertations for defense: [educational and methodological textbook for postgraduates, doctoral students and applicants] / A. A. Ilyin, S. Yu. Belyan, Yu. A. Moskvichev; Ministry of Education and Science of the Russian Federation, Yaroslav State Technical University. un-T. — Yaroslavl : YSTU, 2011. — 72 p.
2. Ippolitova, Natalia Viktorovna. Methodology and methods of scientific research : textbook / Ippolitova N. V., Sterkhova N. S. ; Shadrin. state. ped. in-t, Center "Continuous ped. education". — Shadrinsk : Shadrinsky House of Printing, 2011. — 208 p.
3. Ishkova, Lyudmila Viktorovna. Fundamentals of scientific research: general methodology and private methods : studies. manual for organizers of scientific work, students, postgraduates: [on the discipline "Fundamentals of scientific research"] / L. V. Ishkova ; Novokuznetsk. phil.-in-t Kemer. state University. — Kemerovo : Kuzbassvuzizdat ; Moscow : Russian University, 2005. — 250, [1] p.
4. Kashirin, Vladimir Petrovich. Theory of scientific research / V. P. Kashirin; Ministry of Agriculture of the Russian Federation, Krasnoyar. state agrarian. un-t, Sib. in-t of science studies. — Krasnoyarsk: Publishing house of the Krasnoyar State Agrarian. un-ta, 2007. — 184 p.
5. Salikhov, V.A. Fundamentals of scientific research: a textbook / V.A. Salikhov. - 2nd ed., ster. - Moscow; Berlin: Direct-Media, 2017
6. Shklyar, M.F. Fundamentals of scientific research: textbook / M.F. Shklyar. - 6th ed. - Moscow : Publishing and Trading Corporation "Dashkov and Co.", 2017. –
7. Sabitov, R.A. Fundamentals of scientific research: textbook. manual / R.A. Sabitov. Chelyabinsk: ChelSU, 2017.

Module designation

Dissertation Writing

Credit points

15

Semester(s) in which the module is taught

1/2/3/4

Relation to curriculum

Teaching methods

Workload (incl. contact hours, self-study hours)

Person responsible for the module

Sagidolda Erulan, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

the development of masters competencies necessary for them in the preparation of scientific publications and scientific qualification work (dissertation) provided for in the curricula of educational programs for the training of scientific and pedagogical personnel.

- be able to formulate the purpose and objectives of scientific research, including dissertation research, to determine the scientific novelty and practical significance of the results of research activities;

-apply methods of searching for scientific information on the topic of upcoming scientific research in their professional field;

-analyze and publicly present the results of scientific research.

Content

1. Science and thesis. Thesis as a means of developing science.
2. Requirements for dissertations.
3. Analysis of the state of science and practice in the relevant field.
4. Statement of the purpose and objectives of the dissertation work.
5. Search and definition of the scientific idea of the dissertation
6. Methodology for obtaining an array of primary data: calculated, experimental, analytical, etc.
7. Development of the structural and methodological scheme of the dissertation work
8. Conclusions on the work.
9. The basic rules of presentation and presentation of the dissertation.
10. Publication of the results of the dissertation research.

Examination forms

written examination

Reading list

1.      Zhuravleva, Elena Yurievna. Internet-research: essence, structure and methods / E. Y. Zhuravleva; Northwestern Academy of Public Services, Phil. Northwestern Academy of Public Services in Vologda. — Vologda: Phil. Northwestern Institute of Management, 2009. — 223 p.

1. Zakharov A.A. How to write and defend a dissertation / A. A. Zakharov, T. G. Zakharova. — St. Petersburg: "Peter", 2006. — 160 p.
2. 3. Ilyin, Alexander Alekseevich. The procedure for preparing and submitting dissertations for defense: [educational and methodological textbook for postgraduates, doctoral students and applicants] / A. A. Ilyin, S. Yu. Belyan, Yu. A. Moskvichev; Ministry of Education and Science of the Russian Federation, Yaroslav State Technical University. — Yaroslavl: YSTU, 2011. — 72 p.

Module designation

Scientific Internship

Credit points

3

Semester(s) in which the module is taught

4

Relation to curriculum

Teaching methods

Workload (incl. contact hours, self-study hours)

Person responsible for the module

Sagidolda Erulan, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

The scientific internship is organized in order to get acquainted with innovative technologies and new types of production in scientific organizations and organizations of relevant industries or fields of activity, including abroad. The base of the scientific internship corresponds to the profile of the training of master’s students.

The internship of a research nature of a master's student is aimed at:

- consolidating key competencies, improving the professional level of training, qualification in the specialty of training and improving practical skills;

− familiarization with the latest foreign developments in the specialty being studied;

− advanced training in foreign universities;

− participation in international educational programs and projects;

− improving knowledge of a foreign language and acquaintance with the host country;

− improving the cultural and general educational level

Content

Master’s students can take a scientific internship in the framework of summer/winter schools of leading foreign and domestic universities, research institutes, partner universities, scientific organizations, including abroad (having an invitation).

Examination forms

Internship Certificate

Reading list

1. Regulations on the Master's degree program at the Al-Farabi Kazakh National University;

2. Law of the Republic of Kazakhstan "On Education" dated July 27, 2007 No. 319-III LRK;

Module designation

Publication in the Proceedings of International Conferences

Credit points

4

Semester(s) in which the module is taught

4

Relation to curriculum

Teaching methods

Workload (incl. contact hours, self-study hours)

Person responsible for the module

Sagidolda Erulan, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

Students will:

- be able to discuss the connection between the basic tasks of their own researching area with the other scientific sight.

- optimize and provide the widely discussion on the research theme of master students.

- get new ideas during solving of specific tasks of own research field, they can develop the fresh sight for the problem solving with using the modern methods and achievements.

- be able to accurately organize and manage research, planning and execution of works

- be able to formulate and solve problems, competently handle, analyze and evaluate obtained results

Content

Content requirements are consists of preparation of report and defense of it with presentation. The parts of the research seminars are include the existing done work on the dissertation thesis also the published scientific articles. The dissertation thesis must be prepared and written by the following steps:

1. Reflection of the dissertation work goals and objectives in a concise and in clear manner

2. Characterization of the state of knowledge of the issue (literature review)

3. Justification and description of the used scientific methods

4. Summary and analysis of the results

5. Determination of the scope of the possible use of the results

6. Conclusion

7. References

Requirements to the report and presentation of research seminars are:

- Literacy, clear, concrete and logical sequence of defensed material;

- Credibility of the argument;

- Brevity and precision of the wording, excluding the possibility of ambiguous interpretation.

Examination forms

written examination: report on the conference

Reading list

1. Al-Farabi Kazakh National University’s library.

2. Kazakh National library.

3. Republican Scientific and Technical Libraries.

4. Special literature on major, it depends on the field which master student is going to investigate.

5. Al-Farabi Kazakh National University’s electronic library.

6. Scopus database.

7. Thomson Reuters database.

8. Elsevier, Taylor and Francis, John Wiley publishing houses.

Module designation

FINAL ATTESTATION

Credit points

12

Semester(s) in which the module is taught

4

Relation to curriculum

Teaching methods

Workload (incl. contact hours, self-study hours)

Person responsible for the module

Sagidolda Erulan, PhD, senior lecturer

Language

Kazakh / Russian / English

Required and recommended prerequisites for joining the module

Module objectives/intended learning outcomes

The purpose of the master's thesis is to demonstrate the level of scientific / research qualifications of a graduate student, the ability to independently conduct scientific research, test the ability to independently conduct scientific research, perform project work, systematize, summarize factual materials, as well as independently substantiate conclusions and practical recommendations based on the results of research.

The results of the master's thesis defense are drawn up by a protocol of the established form, individually for each master’s student, and are announced on the day of defense after the minutes of the AС meeting are drawn up. The minutes are filled in by the Secretary of the AС and signed by the Chairman and members of the attestation Commission who participated in the meeting. A student who has passed the final certification, by the decision of the attestation commission, is awarded a master's degree, a diploma with an appendix is issued free of charge.

be able to analyze modern theoretical and technological achievements of science and technology.

- be able to generalize and systemize knowledge and skills acquired during the training of master student in the Master’s program.

- obtain the ability of acting on the basis of ethical reasoning.

- be able to formulate and develop of skills for independent research work, the ability to process the results, analyze, and interpret them in the light of existing literature, on their own justify the conclusions and practical recommendations based on the results of the study

-be able to demonstrate of knowledge in the chosen problems (both in terms of areas of training, and in terms of specializations), research, analytical and methodological skills of a student, creative independence

Content

The topic of the master's thesis is discussed at a meeting of the graduating department, the Academic Council of the faculty, the university and is approved by the order of the university during the first two months of study. At the same time, the scientific supervisor of the master’s student is appointed, under whose supervision the research work and the execution of the dissertation are carried out, with the assignment of a master's degree. In the case of a master's thesis at the junction of various specialties, the appointment of scientific consultants and co-supervisors of the dissertation research is allowed.

Examination forms

Defense of the master's thesis

Reading list

1. Law of the Republic of Kazakhstan "On Education" dated July 27, 2007 No. 319-III LRK;

2. The state mandatory standard of postgraduate education "Magistracy" as amended by the Decree of the Government of the Republic of Kazakhstan dated 13.05.2016 No. 292.