Computer Technologies and Engineering – 2022

ObjectivesLearning outcomesIIIIIIIVVVIVIIVIIIElective Courses

Study Programme
Computer Technologies and Engineering

Degree Programme
First cycle degree programme

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

Occupational Profiles of Graduates
This study program provides acquisition of broad computer engineering knowledge and flexible employment opportunities for the prospective students. Computer Engineering professionals are needed in a wide variety of industries that design computer systems based on new technologies in many areas of application. A graduated computer engineer from this profile, can continue his/her career in many industry areas, as well as the public sector, where the following is being designed, developed and implemented: computer communication systems and services; complex digital systems; modern information systems; Internet and network systems; analysis and development of intelligent networks. The acquired knowledge of students is an excellent basis for continuing studies in institutions and/or research centers all around the world.

The Programme Learning Outcomes
This study program enables students to gain extensive fundamental knowledge from all disciplines in computer technologies and engineering, as well as practical skills for analysis, design, implementation, administration and usage of complete hardware-software computer systems for various specific purposes. In particular, throughout their studies, the students can acquire the following competences and skills:

• Analysis, design and implementation of computer architectures and processors for general and special purpose;
• Analysis, design and implementation of algorithms and data structures;
• Design and implementation of databases and information systems;
• Knowledge, design, implementation and administration of wired and wireless computer networks;
• Administration and usage of operating systems, design and implementation of modules and drivers for computer systems, embedded and mobile devices;
• Knowledge and usage of distributed, high performance and cloud systems;
• Design and implementation of software server environments and applications (web and mobile);
• Design and implementation of systems on chip, embedded and Internet of Things systems;
• Knowledge and application of security and secure computer systems;
• Knowledge and application of data science, machine learning and artificial intelligence in intelligent systems.

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.
  • Demonstrate knowledge and understanding of research, development, engineering design in industrial processes and application of computer technology in the design and implementation of various types of computer systems for different purposes, including the areas: design and implementation of processors and general and special purpose processor architectures; design and implementation of general and special purpose computer systems; algorithms, structures and programming; performance analysis and evaluation, modeling, simulation and design of components of computer systems, computer networks and internet; use and administration of operating systems; design and implementation of modules and components of operating systems for different purposes; design and implementation of embedded systems for different purposes; design and implementation of various components of intelligent networks and so on.
  • 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 technologies and engineering.
Ability to assess
  • An ability to collect, to 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 analyze, evaluate and present information, ideas and concepts from relevant data in the field of engineering computer technology, to recognize priorities and identify deviations from the usual paths, as well as to explain the reasons and to select and implement an appropriate solution.
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
4ФЕИТ08З003 Discrete Mathematics 6 3+3+0+0
4ФЕИТ05З033 Signals and Systems 6 3+2+0+0
4ФЕИТ05З017 Electronics 6 2+2+1+0
4ФЕИТ05З022 Logic Design 6 3+1+1+0
Elective course 1 6
Elective course 1
4ФЕИТ04З014 Fundamentals of Energetics 6 3+2+0+0
4ФЕИТ09З015 Power System Basics 6 3+2+0+0
4ФЕИТ03З007 Basic Measurement Technique 6 2+2+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
4ФЕИТ08Л001 Probability and Statistics 6 3+3+0+0
4ФЕИТ07Л005 Computer Architectures 6 2+2+1+0
4ФЕИТ10Л012 Communication Networks 6 3+1+1+0
4ФЕИТ07Л009 Data Modeling and Database Systems 6 2+2+1+0
4ФЕИТ01Л019 Control Systems 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
4ФЕИТ07З006 Computer Networks 6 2+2+1+0
4ФЕИТ07З013 Operating Systems 6 2+2+1+0
4ФЕИТ10З018 Introduction to Digital Communications 6 3+1+1+0
4ФЕИТ07З017 Data Structures and Algorithm Analysis 6 2+2+1+0
Elective course 1 6
Elective course 1
Code Title ECTS No of classes per week
4ФЕИТ12З003 Android Programming 6 2+2+1+0
4ФЕИТ12З009 Fundamentals of WEB Programming 6 2+2+1+0
4ФЕИТ07З020 Computer System Design with HDL 6 2+2+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
4ФЕИТ07Л002 Security and Protection of Computer Communication Systems and Networks 6 2+2+1+0
4ФЕИТ07Л016 Data Science and Data Analysis 6 2+2+1+0
4ФЕИТ07Л007 Microprocessor Systems 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
4ФЕИТ12Л001 WEB Applications 6 2+2+1+0
4ФЕИТ07Л001 Design and Analysis of Information Systems 6 2+2+1+0
4ФЕИТ12Л004 Applications for Mobile Devices 6 2+2+1+0
4ФЕИТ03Л001 Virtual Instrumentation in LabVIEW 6 2+2+1+0
4ФЕИТ12Л007 Mobile Services with Android Programming 6 2+2+1+0
4ФЕИТ07Л014 Operating Systems for Embedded Computer 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
4ФЕИТ07З004 Intelligent Information Systems 6 2+2+1+0
4ФЕИТ07З012 Advanced Computer Architectures 6 2+2+1+0
Elective course 1 6
Elective course 2 6
Elective course 3 6
Elective course 1, 2 & 3
Code Title ECTS No of classes per week
4ФЕИТ12З002 WEB Services 6 2+2+1+0
4ФЕИТ12З005 Virtualization and Container Systems 6 2+2+1+0
4ФЕИТ07З010 Modeling and Simulation Computer Environments 6 2+2+1+0
4ФЕИТ07З011 Network Standards and Devices 6 2+2+1+0
4ФЕИТ12З008 Network Programming 6 2+2+1+0
4ФЕИТ07З015 Optimization and Evolutionary Algorithms 6 2+2+1+0
4ФЕИТ12З010 Development of Server-based WEB Applications 6 2+2+1+0
4ФЕИТ07З021 Software Development and Testing 6 2+2+1+0
4ФЕИТ08З017 Physics of Game Development 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
4ФЕИТ07Л003 Distributed and Cloud Systems 6 2+2+1+0
4ФЕИТ12Л011 Internship 3
Elective course 1 6
Elective course 2 6
Elective course 1
Code Title ECTS No of classes per week
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
4ФЕИТ08Л014 Technological Innovations 6 2+2+1+0
Elective course 2
Code Title ECTS No of classes per week
4ФЕИТ07Л008 Mobile Sensor Systems and Ambient Intelligence 6 2+1+0+0
4ФЕИТ07Л022 High Performance Systems and Computing 6 2+1+0+0
4ФЕИТ07Л023 Systems and Components for Internet of Things 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 4ФЕИТ08З004 Electrooptics V 2 2+1 6 FEIT
4 4ФЕИТ04З005 Energy Efficiency and Environment V 3 2+0 6 FEIT
5 4ФЕИТ09З012 Overhead Lines and Cables V 3 2+0 6 FEIT
6 4ФЕИТ02З018 Fundamentals of Renewable Energy Sources V 3 1+1 6 FEIT
7 4ФЕИТ10Л010 Industrial communication networks VI 3 1+1 6 FEIT
8 4ФЕИТ01Л005 Inteligent Control Systems VI 2 2+1 6 FEIT
9 4ФЕИТ08Л006 Computer-supported Geometric Modeling VI 3 2+1 6 FEIT
10 4ФЕИТ01Л006 Computer Process Control VI 2 2+1 6 FEIT
11 4ФЕИТ04Л025 Photovoltaic Systems VI 3 1+1 6 FEIT
12 4ФЕИТ08Л011 Numerical Methods VI 3 0+2 6 FEIT
13 4ФЕИТ01Л017 Robotics 1 VI 2 2+1 6 FEIT
14 4ФЕИТ09Л009 Smart Grids VI 3 2+0 6 FEIT
15 4ФЕИТ05З001 VLSI Design with PLD and FPGA Components VII 3 1+1 6 FEIT
16 4ФЕИТ03З004 Computerized Measurement Systems VII 2 2+1 6 FEIT
17 4ФЕИТ04З006 Grounding, professional risk and safety in power plants аnd substations VII 3 2+0 6 FEIT
18 4ФЕИТ05З007 Embedded Systems VII 3 1+1 6 FEIT
19 4ФЕИТ093007 Electrical Lighting VII 3 1+1 6 FEIT
20 4ФЕИТ08З002 Introduction to nanomaterials and nanotechnologies VII 2 2+1 6 FEIT
21 4ФЕИТ10З005 Digital Currencies VII 3 1+1 6 FEIT
22 4ФЕИТ05З012 Digital Image Processing VII 3 1+1 6 FEIT
23 4ФЕИТ02З014 Small and Special Electrical Machines VII 3 0+2 6 FEIT
24 4ФЕИТ01З007 Machine Learning VII 2 2+1 6 FEIT
25 4ФЕИТ01З011 Operations Research VII 2 2+1 6 FEIT
26 4ФЕИТ08З012 Fundamentals of Convex Optimization with Applications VII 3 2+0 6 FEIT
27 4ФЕИТ10З030 Network Forensics VII 3 1+1 6 FEIT
28 4ФЕИТ05Л005 Biomedical Electronics VIII 3 1+1 6 FEIT
29 4ФЕИТ05Л023 Machine Vision VIII 3 1+1 6 FEIT