Computer System Engineering, Automation and Robotics – 2022

ObjectivesLearning outcomesIIIIIIIVVVIVIIVIIIElective Courses

Study Programme
Computer System Engineering, Automation and Robotics

Degree Programme
First cycle degree programme

Level of qualification
Bachelor of Science in Electrical Engineering and Information Technologies, in Computer System Engineering, Automation and Robotics

Occupational Profiles of Graduates
The ever present increase in production efficiency, quality and optimization, demands a constant exploitation of integrated and advanced automation concepts in both technical and non-technical systems (eco-systems, economic systems, medical systems, etc.). Therefore, the programme strives to insure that engineers graduated through it find a wide variety of employment and advancement opportunities: they will be able to identify, analyze, understand and solve problems in different environments, from industrial plants to non-technical settings. They will be competent to work with modern industrial automation, with supervision, remote control and data acquisition systems, as programmers and hardware or software engineers, in academic institutions and/or research centers, etc.

The Programme Learning Outcomes
Students gain extensive fundamental and practical knowledge from all disciplines in system engineering, control theory, automation and robotics. The acquired knowledge and skills are based on modern scientific knowledge in the fields of automation and robotics, computer information technologies, process control, management, bioengineering, cybernetics in medicine, measurement-process technology, industrial internet of things, etc. Students will gain knowledge of:  presenting, modeling and analyzing the behavior of systems of different natures (not only technical ones), application of methods, techniques and tools for mathematical systems analysis and problem solving using a systemic approach,  comprehension of methods for information processing and data acquisition in the control and automation systems, analysis and synthesis of automatic control systems, robotic systems, artificial intelligence and machine learning systems, intelligent control systems and more,  application of control systems elements (hardware and software modules) for process automation, automation of manufacturing plants, computer-controlled systems, electromechanical systems, and process measurements and actuators, analysis and design of SCADA systems for various industrial processes, computer process control and remote control, work with highly automated robotic systems etc. Using the acquired knowledge, the engineer of this study program will be trained for creative thinking and problem solving, individual and team work, effective communication, decision making and lifelong learning. This is all expected to make them well suited for and competitive in the domestic and the European labor market.

International Accreditation
The first cycle study programs at FEEIT are accredited by the German Accreditation Agency for Study Programmes in Engineering, Informatics, Natural Sciences and Mathematics (ASIIN), which is a world leader in quality assurance in higher education. This accreditation confirms that the study programs satisfies the criteria for Bachelor degree programs specified in EUR-ACE Framework standards for the accreditation of engineering programs and the content studied are relevant to areas covered in study programs.

General Learning Outcomes

Knowledge and understanding
  • Demonstrate knowledge and understanding in the scientific field of electrical engineering, based on education and training, including knowledge of theoretical, practical, conceptual, comparative, and critical perspectives in the scientific field according to the appropriate methodology.
Application of knowledge and understanding
  • Demonstrate the ability to apply acquired knowledge and understanding in a professional manner.
  • An ability to identify, analyze and solve complex engineering problems by selecting an appropriate method.
Ability to assess
  • An ability to collect, analyze, evaluate and present information, ideas, and concepts based on relevant data.
  • Making an appropriate assessment taking into account personal, social, scientific and ethical aspects.
Communication skills
  • An ability to communicate effectively in both verbal and written forms with professional and non-professional audiences.
  • An ability to work effectively as an individual or as a member of a team taking shared responsibility for collective results.
  • Ability to participate independently, in a professional manner, in regards to scientific and interdisciplinary discussions.
Learning skills
  • Commitment to the professional development and lifelong learning achieved through higher education, technical training, membership in professional societies, and other activities in order to update already acquired knowledge in the relevant field to achieve continuous professional growth.
  • An ability to acquire and apply new knowledge as needed using appropriate learning strategies.


Specific
 Learning Outcomes

Knowledge and understanding
  • Demonstrate knowledge and understanding in the scientific field of electrical engineering, based on education and training, including knowledge of theoretical, practical, conceptual, comparative, and critical perspectives in the scientific field according to the appropriate methodology.
  • Demonstrates knowledge and understanding of research, development, and application of knowledge in computer system engineering, automation and robotics, as well as engineering design in industrial processes.
  • Understanding and knowledge of current issues related to scientific research and new sources of knowledge.
Application of knowledge and understanding
  • An ability to identify, analyze and solve complex engineering problems.
  • An ability to apply knowledge and understanding in a way that demonstrates professionalism to the relevant field or profession.
  • An ability to identify, analyze and solve problems related to computer system engineering, automation and robotics.
Ability to assess
  • An ability to collect, analyze, evaluate and present information, ideas and concepts from relevant data.
  • Making an appropriate assessment taking into account personal, social, scientific and ethical aspects.
  • An ability to provide answers to both theoretical and practical issues, in order to give explanations and choose the appropriate solution.
  • An ability to collect, analyze, evaluate and present information, ideas and concepts from relevant data in the field of computer system engineering, automation and robotics.
Communication skills
  • An ability to communicate effectively in both verbal and written forms with professional and non-professional audiences.
  • An ability to work effectively as an individual or as a member of a team taking shared responsibility for collective results.
  • An ability to participate independently and professionally in specific, scientific and interdisciplinary discussions.
Learning skills
  • Commitment to professional development and lifelong learning through higher education, technical training, membership in professional societies, and other activities in order to update already acquired knowledge in the field and to achieve continuous professional growth.
  • An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
  • Demonstrate a high degree of independence initiative for learning and professional development.
  • Understanding the need for learning and ability for continuous professional development, through the use of professional and scientific literature, professional training, continuing formal education, membership in professional organizations, etc.
  • Awareness of new technologies and the ability to evaluate and use modern software development tools.
  • An ability to use information technologies for distance and e-learning.
  • Skills for cooperative, competitive and individual learning.
  • Applying active teaching and learning techniques.

Semester 1
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ08З007 Mathematics 1 8 4+3+0+0
4ФЕИТ08З015 Physics 1 7 3+2+1+0
4ФЕИТ06З006 Fundamentals of Electrical Engineering 8 3+3+1+0
4ФЕИТ07З019 Programming and Algorithms 7 2+2+2+0

Semester 2
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ11Л001 Practicum for engineering tools 3 1+0+2+0
4ФЕИТ06Л005 Fundamentals of Electric Circuits 7 3+2+1+0
4ФЕИТ08Л008 Mathematics 2 7 3+3+0+0
4ФЕИТ07Л018 Data Structures and Programming 6 2+2+2+0
4ФЕИТ08Л016 Physics 2 7 3+2+1+0

Semester 3
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ08З009 Mathematics 3 6 3+3+0+0
4ФЕИТ03З006 Electrical Measurements 6 3+1+1+0
4ФЕИТ05З033 Signals and Systems 6 3+2+0+0
4ФЕИТ05З018 Electronics 1 6 3+1+1+0
4ФЕИТ05З022 Logic Design 6 3+1+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 4
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ05Л009 Digital and Power Electronics 6 3+1+1+0
4ФЕИТ05Л014 Electromagnetics 6 3+2+0+0
4ФЕИТ01Л004 Elements of Automation and Robotics 6 2+2+1+0
4ФЕИТ08Л010 Mathematics 4 6 3+3+0+0
4ФЕИТ01Л020 Automatic Control 1 6 2+2+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 5
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ02З008 Electric Power Devices 6 3+1+1+0
4ФЕИТ10З013 Communication Technologies 6 3+1+1+0
4ФЕИТ01З021 Automatic Control 2 6 2+2+1+0
4ФЕИТ01З022 Systems Thinking 6 2+2+1+0
Elective course 1 6
Elective course 1
Code Title ECTS No of classes per week
4ФЕИТ01З002 Discrete-event Systems and Flexible Manufacturing 6 2+2+1+0
4ФЕИТ01З013 Introduction to Artificial Intelligence 6 2+2+1+0
4ФЕИТ03З009 Process Measurements 6 3+1+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 6
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ01Л006 Computer Process Control 6 2+2+1+0
4ФЕИТ01Л009 Мodeling, Identification and Simulation 6 2+2+1+0
4ФЕИТ01Л017 Robotics 1 6 2+2+1+0
Elective course 1 6
Elective course 2 6
Elective course 1 & 2
Code Title ECTS No of classes per week
4ФЕИТ10Л010 Industrial Communication Networks 6 3+1+1+0
4ФЕИТ01Л005 Inteligent Control Systems 6 2+2+1+0
4ФЕИТ07Л005 Computer Architectures 6 2+2+1+0
4ФЕИТ07Л009 Data Modeling and Database Systems 6 2+2+1+0
4ФЕИТ01Л015 Design of Security Systems 6 2+2+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 7
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ01З010 Nonlinear Control Systems 6 2+2+1+0
4ФЕИТ01З014 Programmable Logic Controllers 6 2+2+1+0
4ФЕИТ01З016 Control System Design 6 2+2+1+0
Elective course 1 6
Elective course 2 6
Elective course 1 & 2
Code Title ECTS No of classes per week
4ФЕИТ01З001 Manufacturing Plant and Process Automation 6 2+2+1+0
4ФЕИТ01З007 Machine Learning 6 2+2+1+0
4ФЕИТ01З011 Operations Research 6 2+2+1+0
4ФЕИТ01З018 Robotics 2 6 2+2+1+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

Semester 8
Mandatory courses
Code Title ECTS No of classes per week
4ФЕИТ12Л006 Final Thesis 9
4ФЕИТ12Л011 Internship 3
Elective course 1 6
Elective course 2 6
Elective course 3 6
Elective course 1
Code Title ECTS No of classes per week
4ФЕИТ09Л005 Engineering Economics 6 3+2+0+0
4ФЕИТ04Л016 Entrepreneurship and Business for Engineers 6 3+2+0+0
4ФЕИТ03Л008 Principles of Quality Management 6 3+2+0+0
4ФЕИТ04Л018 Project management and Ethics in Engineering 6 3+2+0+0
Elective course 2 & 3
Code Title ECTS No of classes per week
4ФЕИТ01Л003 Distributed Control Systems and SCADA 6 2+1+0+0
4ФЕИТ05Л023 Machine Vision 6 3+1+1+0
4ФЕИТ07Л007 Microprocessor Systems 6 2+1+0+0
4ФЕИТ01Л008 Mobile Robotics 6 2+1+0+0
4ФЕИТ01Л012 Optimal Controllers and Observers 6 2+1+0+0

 

During studying, the student may choose up to 4 courses from the faculty list of electives

No. Code Title Semester No of classes per week ECTS Faculty
L E
1 4ФЕИТ06З004 Energy and Sustainable Dеvelopment III 3 2+0 6 FEIT
2 4ФЕИТ05З011 Digital Signal Processing V 3 1+1 6 FEIT
3 4ФЕИТ08З003 Discrete Mathematics V 3 3+0 6 FEIT
4 4ФЕИТ08З004 Electrooptics V 2 2+1 6 FEIT
5 4ФЕИТ04З005 Energy Efficiency and Environment V 3 2+0 6 FEIT
6 4ФЕИТ02З018 Fundamentals of Renewable Energy Sources V 3 1+1 6 FEIT
7 4ФЕИТ07З013 Operating Systems V 2 2+1 6 FEIT
8 4ФЕИТ12З009 Introduction to WEB programming V 2 2+1 6 FEIT
9 4ФЕИТ09З012 Overhead Lines and Cables V 3 2+0 6 FEIT
10 4ФЕИТ08З013 Statistical Data Analysis V 3 1+1 6 FEIT
11 4ФЕИТ12Л001 WEB Applications VI 2 2+1 6 FEIT
12 4ФЕИТ09Л009 Smart Grids VI 3 2+0 6 FEIT
13 4ФЕИТ08Л006 Computer-supported Geometric Modeling VI 3 2+1 6 FEIT
14 4ФЕИТ04Л025 Photovoltaic Systems VI 3 1+1 6 FEIT
15 4ФЕИТ08Л011 Numerical Methods VI 3 0+2 6 FEIT
16 4ФЕИТ07Л016 Data Science and Data Analysis VI 2 2+1 6 FEIT
17 4ФЕИТ03Л001 Virtual Instrumentation in LabVIEW VI 2 2+1 6 FEIT
18 4ФЕИТ05З001 VLSI Design with PLD and FPGA Components VII 3 1+1 6 FEIT
19 4ФЕИТ093007 Electrical Lighting VII 3 1+1 6 FEIT
20 4ФЕИТ05З007 Embedded Systems VII 3 1+1 6 FEIT
21 4ФЕИТ08З002 Introduction to nanomaterials and nanotechnologies VII 2 2+1 6 FEIT
22 4ФЕИТ10З005 Digital Currencies VII 3 1+1 6 FEIT
23 4ФЕИТ05З012 Digital Image Processing VII 3 1+1 6 FEIT
24 4ФЕИТ04З006 Grounding, professional risk and safety in power plants аnd substations VII 3 2+0 6 FEIT
25 4ФЕИТ02З014 Small and Special Electrical Machines VII 3 0+2 6 FEIT
26 4ФЕИТ12З010 Development of Server-based WEB Applications VII  2  2+1  6 FEIT
27 4ФЕИТ08З012 Fundamentals of Convex Optimization with Applications VII 3 2+0 6 FEIT
28 4ФЕИТ10З030 Network Forensics VII 3 1+1 6 FEIT
29 4ФЕИТ05Л005 Biomedical Electronics VIII 3 1+1 6 FEIT