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 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 |
