Бакалавр в области электротехники и компьютерной инженерии

This course introduces students to the foundation and fundamental principles required to become analytical, detail-oriented, and productive engineers. The students will also gain an overview of what engineers do and of the various areas of specialization. Important topics for the engineering profession such as research in engineering, communications, and safety are also introduced. Additionally, students will work together in interdisciplinary groups to research, design, fabricate, test, and deploy a complete engineering project.

Through lectures, laboratory practicum and project work, the students will become familiar with the following topics:

• Overview of the Engineering Discipline
• Engineering Communications
• Research Skills
• Occupational Health & Safety
• Drafting and 3D Modelling
• Fundamental Dimensions and Units
• Manufacturing (3D Printing and/or others)
• Material & Chemical Properties
• Hydraulics and Fluids management
• Programming * AC/DC circuits

Programming for Engineers is a comprehensive introductory course designed specifically for students with little or no prior programming experience. The course aims to equip students with fundamental programming skills and a solid understanding of the role computation can play in problem-solving. By the end of the course, students will develop the confidence and ability to write small programs to accomplish practical goals, regardless of their field of study.

This course will introduce students to the field of Materials Science and Engineering. Some of the fundamental physical and chemical features of materials will be addressed, including bonding between metal atoms, covalent bonding between non-metallic atoms, ionic bonding, and soft bonding (van der Waals interaction and hydrogen bonding). Many construction materials, as encountered in our daily lives, will be examined from the atomic level all the way up to their (often surprising) macroscopic features. For instance, attention will be devoted to electrical properties of materials (conductivity, isolators), as well as to magnetic and optical properties. Furthermore, the effect of processing methods on the ultimate properties of materials will be discussed. The course will address metals (including shape-memory metals), ceramic materials and various types of polymers (e.g. poly olefins, poly esters, polyurethanes, natural polymers such as cellulose, silk and wood, and synthetic hydrogels). Some pertinent applications, e.g., (i), in the field of electronic engineering (semiconductors); (ii), in micro- and nano-mechanical systems) and (iii), in biomedical engineering (biomaterials) will be highlighted.

1. Differential equations of first- and second-order
2. Series solution of differential equations
3. Laplace transforms and its application to the solution of initial value problems
4. Some of the important special functions.
5. Linear algebra applications
6. Incorporation of the software package Mathematica for both calculus & linear algebra applications.

This course provides an introduction to basic probability theory and statistics. Topics include sample spaces, events, classical and axiomatic definition of probability, conditional probability, independence, expectation and conditional expectation, variance, distributions of discrete and continuous random variables, joint distributions, central limit theorem, descriptive statistics, confidence interval estimation, and hypothesis testing.

In this course students work in interdisciplinary teams toward a holistic approach to design projects; including problem definition, design proposal, implementation, and critical evaluation. The course explores design research and practice within social and economic contexts; including the ethical, cultural, and environmental impacts of design decisions, intellectual property considerations, and aspects of appropriate professional conduct. The course will focus on tools and skill sets that are particularly important for succeeding in a design project, including planning, teamwork, project management, and design reporting. Where possible, it is expected that the projects will include an industrial partner, who will provide realistic industrial problems and support them with necessary guidance and resources. This course requires students form and work in groups of 5 or more in size.

The capstone project is the culminating experience of the student's engineering program and provides students with the opportunity to apply and integrate their knowledge and skills gained from earlier years. This course spans two semesters (one academic year), during which students work in teams to apply their knowledge and skills to solve design and operational problems with real world constraints. At the completion of the unit, students will hand over their project deliverables and present project outcomes in a report as well as end-of-semester oral presentation and defense.

This is the first course on electrical circuit theme and covers three distinct circuit aspects. The first part of the course deals with the circuit analysis techniques, circuit theorems, various combination on RLC circuits and their responses, and phase relationship for R, L, and C, Impedance and Admittance. The second part of the course deals with Semiconductor diode, Zener diode, Rectifier Circuits, Clipper and Clamper Circuits, and other wave shaping circuits. The third and final component of this course covers Magnetic circuits, mutually coupled circuits, Transformers, and equivalent circuits and their performance.

The objective of this course is to build on the tools and techniques learnt in ELCE 200 Circuit Theory I course. A tentative list of topics includes: Review of Basic Circuit Analysis, Operational Amplifiers-based circuit analysis, Second-Order Circuits and Three-Phase Circuits, Frequency Response of Active Filters, Application of Laplace Transform for Circuit Analysis, Circuit Application using Fourier Analysis, Two-port Networks.

The objective of this course is to provide hands-on laboratory training in circuit theory, design and analysis methods to students taking the accompanying core ELCE 200 Circuit Theory I and ELCE 201 Circuit Theory II courses. A tentative list of topics includes: Review of Basic Circuit Analysis, Operational Amplifiers-based circuit analysis, Second-Order Circuits and Three-Phase Circuits, Frequency Response of Active Filters, Application of Laplace Transform for Circuit Analysis, Circuit Application using Fourier Analysis, Two-Port Networks.

This course presents the introductory concepts that are needed in order to design digital systems including combinational and sequential digital logic, and state machines. Concepts of Boolean algebra, Karnaugh maps, flip-flops, registers, and counters along with various logic families and comparison of their behavior and characteristics are covered. Additionally this course presents an introduction of the Hardware description language (VHDL) and introduce students to design combinational and sequential circuits using VHDL and simulators.

A co-requisite laboratory course (accompanying ELCE 206 Digital Logic Design), covering practical aspects of digital system design. This course introduces basic wiring and hardware interfacing techniques, exposes students to state-of-the-art design applications and techniques using Field Programmable Gate Arrays (FPGA), and covers design using hardware description languages (HDL). Concepts, such as Boolean algebra, number representations, synthesis and design of combinational and sequential logic circuits, and other topics from the co-requisite lecture course, are reinforced with hands-on experiences in the laboratory.

The objective of this course is to introduce fundamental properties of linear systems and transform techniques to analyze the behavior of linear systems. Students are also expected to gain an appreciation for the importance of linear system theory in electrical engineering.

A tentative list of topics includes:

• Introduction to signals: classifications, transformations, and basic building-block signals. *Introduction to systems: properties (linearity, time-invariance, causality, etc.) and system interconnections.
• Time-domain analysis: convolution sum and convolution integral, linear constant-coefficient difference and differential equations.
• Frequency domain analysis: Fourier series (derivation, properties, and convergence), Continuous-time Fourier transform (derivation, properties, convergence), Discrete-time Fourier transforms (derivation, properties, convergence). Laplace transform (properties, convergence), inverse Laplace transform.
• Introduction to Z transform (time-permitting)

The objective of this course is to train students by providing comprehensive practical (laboratory) works on the fundamental properties of linear systems and transform techniques to analyze the behavior of linear systems. Students are also expected to gain an appreciation for the importance of linear system theory in electrical engineering.

A tentative list of topics includes:

• Introduction to signals: classifications, transformations, and basic building-block signals.
• Introduction to systems: properties (linearity, time-invariance, causality, etc.) and system interconnections.
• Introduction to sampling.
• Time-domain analysis: convolution sum and convolution integral, linear constant-coefficient difference and differential equations.
• Frequency domain analysis: Fourier series (derivation, properties, and convergence), Continuous-time Fourier transform (derivation, properties, convergence), Discrete-time Fourier transform (derivation, properties, convergence). Laplace transform (properties, convergence), inverse Laplace transform. Finite impulse response (FIR) filtering.

Solid state devices play an important role on modern life, causing revolutionary development in new technologies. This course focus on fundamental knowledge in semiconductor material properties and solid-state devices such as diodes, MOSFETs and BJT. The course will start with introducing physical models, energy band models, carrier actions and then go into the topics of p-n junctions and its applications. Modern devices such as photodetectors, solar cells and LEDs will be discussed. This course will also cover the fundamentals of MOS capacitors, BJTs and MOSFETs, equipping students with consolidation of physical knowledge for their subsequent courses in electronics and circuits. In the lab sessions, students can consolidate their knowledge by doing the designed experiments in electronics and computer labs and have chance to learn the basic fabrication techniques of semiconductor devices.

This course covers processes that consist of a sequence of countable and separable structures. This is in contrast with calculus, which studies processes in a continuous fashion. While the calculus is fundamental to many scientific disciplines including physics, engineering, and economics, the ideas in discrete mathematics contribute to the computer science and engineering. The main themes of this first course in discrete mathematics are logic and proof, induction and recursion, discrete structures, combinatorics and discrete probability, algorithms and their analysis, and applications and modeling.

• Logic and Proof: is the main goal of this first course in discrete mathematics which is to help students to think abstractly. Students will learn to use logically valid forms of arguments and avoid logical errors. They will gain knowledge to reason from definitions and to derive new results from those already known to be true.
• Induction and recursion: Students will be familiarized with the concept of recursion which is the process of solving large problems by breaking them down into simpler problems that have identical forms. Such approach is widely used in the analysis of algorithms.
• Discrete structures: Those will be covered are sets of integers and rational numbers, general sets, Boolean algebra, functions, relations, graphs and trees, formal languages and regular expressions, and finite-state automata.
• Combinatorics and Discrete Probability: Basic probability theory will be studied including subjects such as permutations, combinations, expectation, probability axioms and binomial theorem.
• Algorithms and their analysis: Designing an algorithm and determining whether or not it is correct requires the use of mathematical induction. In order to compare the algorithms in terms of their memory requirements and their execution speeds, combinatorics, recurrence relations, functions, and O-, V-, and Q-notations will be studied.

This course provides an overview of microcontrollers, as well as select topics in computer architecture and embedded systems. Students will develop an appreciation for the role of hardware in computer operations; an understanding of microcontrollers, microprocessors, and embedded systems; and will be able to design, write, and debug assembly language and C-language programs for microcontrollers using a state-of-the-art integrated development environment. Additional concepts will include interfacing with external hardware, interrupts and timers, as well as principles of good software/hardware co-development. This course will place a heavy emphasis on laboratory practicums and all theory aspects will be covered in the corresponding labs.

This course equips students with the practical skills to program and develop applications for microprocessor based systems. Laboratory experiments in this course supplement the subjects covered in ELCE 300 Microprocessor Systems course. Microprocessor kits and experiment boards, as well as emulator tools, are used to explore the architecture and behavior of such systems. A tentative list of topics includes:

• Methods used to store data in microprocessor based systems
• Programming model of the microprocessors and assembly language
• Instruction set and its classification , e.g. for Intel family microprocessors
• Developing applications using assembly program
• Basic I/O interfacing that includes timers, keyboard/display controllers, ADC/DAC
• Advanced I/O techniques such as printer interface and disk memory

The course focuses on building the ability to analyze and design electronic circuits. This course starts with an overview of semiconductor technology. Subsequently it covers Bipolar Junction Transistor (BJT), Small Signal BJT models, BJT based amplifiers, Metal Oxide Field Effect Transistors (MOSFET), Small Signal MOS models, MOSFET based amplifiers, applications of BJT and MOSFET in the design of differential amplifiers, power amplifiers, and their characterization techniques. The assignments and labs complement the theoretical postulations and will consist of theoretical analysis, simulation exercises, and laboratory experiments.

The objective of this course is to provide hands-on laboratory training in analysis and electronic circuits design. This course starts with an overview of semiconductor technology. Subsequently it covers Bipolar Junction Transistor (BJT), Small Signal BJT models, BJT based amplifiers, Metal Oxide Field Effect Transistors (MOSFET), Small Signal MOS models, MOSFET based amplifiers; and analog and digital circuits and applications.

This course aims to teach the theory and principles of electromagnetism and electromechanical energy conversion devices and systems. Topics covered include: Electromagnetism and magnetic circuits, magnetic losses, self and mutual inductances, permanent magnet, and production of voltage and force. DC machines – construction, operation, classification, characteristics, losses, efficiency, starting, speed control, and dynamic model and characteristics. Transformers – construction, equivalent circuits, voltage regulation and efficiency, determination of parameters, autotransformers, and 3-phase transformers. Three-phase induction machines – construction, classification, operation, development of equivalent circuit, performance calculations, characteristics, starting, and speed control of induction motors; modelling, operation, and characteristics of induction generators. Synchronous machines – construction, operation, equivalent circuit, phasor diagram, and characteristics for both generator and motor operations. Overview, operation, and characteristics of some special purpose machines.

Power system analysis is the core knowledge required for understanding, planning, and operating a power system. This unit introduces students to the core knowledge of power systems analysis and modelling. The unit will begin by introducing concepts related to the operation of plant equipment and the deregulation of the energy industry. This is followed by a detailed study into current, voltage, capacitance and impedance relations on a short, medium and long distance transmission line. Power-flow calculations for various symmetrical and unsymmetrical fault conditions will be investigated using the methods of Gauss-Seidel, Newton-Raphson and Fast Decoupled. Other aspects covered include power system stability, control, contingency analysis and economic operation.

This course introduces fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: overview of network architectures, applications (HTTP, FTP), network programming interfaces (e.g., sockets), transport (TCP, UDP), flow control, congestion control, IP, routing, multicast, data link protocols, error-detection/correction, multiple access, LAN, Ethernet, wireless networks, and network security. Examples will be drawn primarily from the Internet (e.g., TCP, UDP, and IP) protocol suite. The main topics that will be covered are computer networks and the Internet, application layer, transport layer, network layer: data plane and control plane, datalink layer: links, access networks and LANs, wireless and mobile networks, network security, multimedia and social networking.

Data structures and algorithms covers analysis and design of fundamental data structures and engages students to use data structures as tools to algorithmically design efficient computer programs that will cope with the complexity of actual applications. The course focuses on basic and essential topics in data structures, including array-based lists, linked lists, queues, hash tables, recursion, binary trees, heaps, sorting algorithms, graphs, and finite automata. This course will also cover the advanced programming concepts, equipping students with consolidation of physical knowledge for their subsequent courses in computer engineering. The lab sessions have been designed to give students sufficient practical exposure and make them capable to design efficient application-specific algorithms.

This course is an introductory course in control theory which introduces analysis of feedback closed loop systems and controller design. The course includes description of linear, time-invariant, continuous time systems, system dynamic properties in time and frequency domains, and performance specifications. Then the course covers basic properties of feedback including stability analysis: Routh-Hurwitz criterion, Root Locus method, Bode gain and phase margins, and Nyquist criterion. Then classical controller design in time and frequency domain: lead, lag, lead-lag compensation, rate feedback, and PID controller are introduced. Laboratory work consists of MATLAB and Simulink assignments, reinforcing analytical concepts and design procedures.

This course is designed to familiarize students with the fundamental concepts in digital signal processing (DSP). A list of topics includes:

• Introduction to DSP
• Review of signals and systems (convolution vs Correlation).
• Fourier domain analysis, and Discrete Fourier Transform (DFT), Properties of DFT, Circular Convolution, linear vs circular convolution.
• Z-Transform and its applications in signal processing.
• Sampling & digital processing of continuous time signals.
• Transform-domain analysis of linear time-invariant (LTI) systems.
• Structures for implementation of digital filters.
• IIR Digital filter design & FIR filter design.
• Overview of Signal Processing Applications

ELCE 308 is the first course in communication engineering that convers the concepts both in analog and digital communication systems including amplitude (AM) and frequency modulation (FM), pulse code modulation (PCM), phase shift keying (PSK)and quadrature amplitude modulation (QAM). Analog to digital conversion methods, sampling and quantization, are briefly revisited. The effects of noise and the transmission medium on the system performance through signal-to-noise ratio (SNR), intersymbol interference (ISI) and bit-error-rate (BER) analysis are discussed. For digital communication, optimal receivers with matched filtering for both baseband and passband transmission are discussed In detail. Fourier transform techniques, linear systems, filtering, power and energy spectral density of random signals are reviewed for conceptual purposes. Laboratory and software assignments are given to exercise the concepts and techniques covered in class.

This course is designed to be a lead-in to the Year 4 capstone project of student studies, during which students will develop necessary skills that would make their capstone project successful. The course covers literature review, independent research, and methods of applying existing knowledge and skills to solving an engineering problem. This course would be led by the student, with faculty members providing the necessary expertise to steer the research in the correct direction. Students will learn and develop research methods, which they will apply throughout their capstone project course sequence in Year 4 of bachelor studies. A proposal that will provide the scope for the capstone project and a comprehensive literature review will be presented at the end of the course, in addition to an end-of-semester presentation.

This course prepares students for the Year 4 capstone project by honing skills in report writing, research, and LaTeX typesetting. It offers hands-on labs covering electrical circuits and PCB design. Students present findings and submit a final report, showcasing growth and insights. Graduates emerge as skilled electronics enthusiasts, researchers, and adept report writers, well-prepared for their Year 4 capstone projects.

This course prepares students for the Year 4 capstone project by honing skills in report writing, research, and LaTeX typesetting. It offers hands-on labs covering electrical circuits and PCB design. Students present findings and submit a final report, showcasing growth and insights. Graduates emerge as skilled electronics enthusiasts, researchers, and adept report writers, well-prepared for their Year 4 capstone projects.

This course offers a comprehensive exploration of MATLAB/SIMULINK for modeling, simulating, and analyzing electrical systems. From circuits to control systems, students gain practical skills through lab sessions and theoretical explanations, ensuring a thorough understanding of the subject matter.

The course materials are designed for year 3 bachelor students, to obtain basic knowledge of electronic instrumentation and measurements. In this course, students can get essential hands-on experience and understanding of end-to-end measurement of circuits and systems such as Amplifiers, resonant circuits, analog-to-digital/digital to analog converters and filters. The course exposes students to understand measurement principles; how circuits are built and connected; and how to operate basic measurement instruments such as power supplies, function generators, oscilloscopes, multimeters, network analyzers and spectrum analyzers.

This course covers the fundamentals and applications of power electronics, focusing on AC-DC, DC-DC, and DC-AC converters. Students will learn to analyze and simulate converter performance, understand semiconductor devices, and develop hands-on skills through labs and simulation tools. The course prepares students for advanced study and careers in energy systems, electric vehicles, and industrial automation.

Students in the Electrical and Computer Engineering department have an opportunity to complete a credit-bearing internship from the third year onwards. The internship provides a practical problem-solving experience as a bridge between coursework and professional life. A student can take the internship at a company, located either in Kazakhstan or in a foreign country, for a total number of working hours equal to 200 or more. As an alternative, the internship can be taken either in a research laboratory of a foreign university, for total number of hours of research conducted equal to 200 or more.

This course introduces students to the use of MATLAB/SIMULINK for modeling, simulating and analyzing various electrical systems, including electric circuits, operational amplifiers, power electronics, electrical machines, communication systems, and control systems. The laboratory sessions will be supplemented with theoretical explanations to ensure a comprehensive understanding of the topics .

This course provides the mathematical framework for an understanding of adaptive statistical signal processing. The basic tools of vector spaces, optimization theory, and discrete-time stochastic processes are reviewed and applied to the methods of Wiener filtering and least-squares filtering. Various types of adaptive filters will be introduced and their properties will be studied, specifically convergence, tracking, robustness and computational complexity.

The course materials are designed for year 4 bachelor students, who have basic knowledge of semiconductor material science. In this course, students can learn the fundamentals of semiconductor material properties with understanding the material as well as device characterizations. The modern characterization techniques widely applied in the semiconductor industry are including electrical, optical, chemical and physical methods. The fundamental principles, mechanisms, instrumentation and applications of instruments will be covered. Experimental sessions will be prepared for students, who can perform characterizations on materials and devices with modern instruments.

The aim of this course is to equip students with knowledge of variable-speed drives and motion control systems which are used in many industrial processes such as in conveyors, machine tools, pumps, compressors, mining drives, electric vehicles, ship propulsion, wind energy systems, air-craft actuators, servo drives and automation systems, to name a few. The course stresses the basic understanding of characteristic of machines driven from appropriate power electronic converters and controllers. The steady-state behavior of such drives will be primarily covered, and some dynamic issues of drive representation and control system design will also be introduced. The course covers elements of electric drive systems and requirements of industrial drives. Drive representation, quadrant operation, dynamic and regenerative braking, performance analysis and other topics are then discussed. Application of Electric Drives in industrial motion control systems such as wind turbines and tractions systems in electric/hybrid vehicles will also be covered.

The course aims to provide the students with the fundamentals of energy conversion and renewable energy generation along with resources, and renewable energy sites and potential recognition. Solar, wind, photovoltaic, geothermal, wave, tidal, micro-hydro generation are discussed and analyzed in this course. In particular, it provides essential fundamental knowledge for designing the wind and solar/photovoltaic energy systems. Sustainable energies and suitability of renewable resources as a replacement for conventional energy resources in future energy demand are explained, discussed and analyzed in this course. This course will also provide knowledge on DC/AC conversion systems and equipment, design, fabrication, calculation and its operation principles. It will also deliver fundamental knowledge on thermal energy systems and discuss on battery energy storage systems’ design, size selection and circuit connection considerations. Grid-connected and stand-alone systems will be introduced in this course, and, DC and AC dispatch will be introduced. This course will also provide design and operation of Electric Vehicles (EVs) and the EV propulsion system along with motors, drivers and converters would be explained. The course will also practice different industrial renewable energy systems and explain their implementation factors for students. Particular emphasis is on compliance with current practices and regulations within Eurasia.

This course is designed to provide knowledge and understanding along with design proficiency for electrical and high voltage apparatus. It will cover large power systems in interconnected physical networks, different types of equipment and apparatus, synchronous generators, power transformers, overhead transmission lines design and structure and insulation coordination, underground cables, metering and control equipment, switchgear for connection or disconnection, high-voltage insulators, AC/DC devices, flexible alternating current transmission system (FACTS) as static equipment used for the AC transmission of electrical energy, and high voltage direct current transmission (HVDC) systems as well as high voltage power electronics-based devices. This course also provides knowledge on different high voltage equipment design constraints to support different electrical operating conditions (voltage, current and power levels) and ambient constraints. This is a progressive course on high-voltage technology and electrical insulating materials, providing different aspects (calculations, assessment, and measurement) and testing techniques for high voltage power system apparatus. Electrical breakdown strength of gaseous, liquid and solid insulators and dielectric modeling and properties of electrical insulation systems are also delivered in this course. In addition, switching, lightning, and other high voltage incidents in industry along with their standards are discussed in detail in this course. Modern high voltage AC/DC and FACTS devices will be also discussed in this course.

The course is designed to provide the fundamental and key knowledge on generation, transmission and distribution in power systems as well as electrical industrial power systems: design, construction, maintenance, load calculation, management and operation. It will also provide essential knowledge on renewable energy and its calculations along with microgrid and distributed generation concept. In particular, it provides crucial fundamental understanding for designing the wind and solar energy systems along with energy conversion basics. Furthermore, transmission lines in power system as well as distribution network demand calculation is discussed in this course. Particular emphasis is on compliance with current practices and regulations within Eurasia. The course also touches on some aspects of utilization. Regulatory aspects; underground power systems; earthig system design; DC and AC dispatch in distribution network; power factor correction in distribution network, calculating touch voltages and electric shock risk in transmission and distribution systems, active and reactive power, power factor improvement and voltage control, equipment selection, and performance calculation are some of the important topics that will be discussed in this course.

Machine learning provides the technical basis of data mining and has become an integral part of various research projects and high-tech applications. Although understating the detailed working principles of many machine learning techniques needs a good level of mathematical proficiency, in this course, we keep the math minimal and take a hands-on approach to focus primarily on practical aspects of machine learning. In this regard, we focus on using Python, which has become the most popular language in data science. We assume students have no knowledge of Python programming but are familiar with programming in another language. As a result, and in order to make the course self-contained, we provide a quick introduction to essential components of Python programming and move to machine learning applications. Then in order to efficiently implement all the introduced machine learning methods and techniques, we will use efficient Python libraries for machine learning including Scikit-Learn and Keras with a TensorFlow backend.

This course provides a core grounding in how science and technology have developed to enable the Internet of Things (IoT) – in a way appropriate for any learner. For those interested in developing further hands-on expertise in designing and developing for the Internet of Things, this course will provide a context to the discoveries and converging technologies that will springboard the next round of innovations. Topics covered in this module include:

• Automation systems: Introduction, networks for automation applications: HART, CAN, PROFIBUS, Industrial Ethernet
• Capillary networking: Challenges for wireless capillary networking. Systems addressing these challenges: IEEE 802.15.4, Wireless HART, Low Power Bluetooth, Lower Power WiFi

Internet of Things (IoT): Introduction of IoT, Integration of constrained node networks into the IPv6 world, 6LoWPAN, ROLL RPL: Routing protocol for heterogeneous low-power and lossy networks, CoRE CoAP: HTTP-like application layer protocol over UDP

This course introduces the basic methodologies and theories of digital image processing and computer vision. Computer vision is presented as a process of extracting useful data from noisy images and video sequences. Lightweight algorithms will be covered, as well as their application to embedded smart cameras and other low-power vision platforms. Algorithm design will be emphasized over specific libraries or products, allowing students to implement their own computer vision algorithms from scratch using any programming language of their choice. At the conclusion of the course, deep learning techniques for computer vision algorithms and their applications will be explored.

This is an introductory course on optimization techniques for solving engineering problems. The main aim of this course is to (i) Model engineering problems as optimization problems, (ii) Recognize and solve convex sets, functions and optimization problems, and (iii) Apply constrained and unconstrained optimization methodology in engineering applications. Accompanied by several implementation assignments, the following outcome and learning attributes are expected to have been gained by the students:

1. Identify, formulate and solve optimization problems that arise in engineering.
2. Hands-on experience with tools to solve unconstrained and constrained convex optimization problems.
3. Understand the role of numerical linear algebra in solving these problems.
4. Understand the heuristics for solving non-convex problems.

The main outline of the course is:
1. Introduction: classification of problems, optimality conditions
2. Univariate optimization (bracketing methods): Bisection method, Fibonacci search, Golden section search
3. Univariate optimization (interpolation methods): Newton’s method, Secant method, Regular Falsi method, quadratic interpolation, cubic interpolation
4. Multivariate optimization: Non-smooth functions, Gradient based methods, second derivative methods, least squares
5. Constrained optimization: Lagrange multipliers, KKT, linear programming, quadratic programming, interior point method, convex programming
6. Global optimization: genetic algorithm, simulated annealing
7. Game theory strategies (cooperative, non-cooperative resource allocation)

The course consists of three different facets of circuits and systems technology. The first part focuses on the analog circuits and systems. It aims to equip the students with the concepts of operational amplifier design (from transistor to block level), instrumentation amplifier, OTAs etc. This will entail theory, simulation, and design of circuit blocks for achieving certain functionality such as waveform generator, triangulation etc. In the second part, the students get equipped with the RF/Microwave and Antenna techniques. The students will be introduced to the RF and Antenna concepts for advanced wireless, biomedical, and consumer electronics applications. The students will also get introduced to Machine Learning for RF circuits design and optimization. The particular emphasis will be on the design and realization of blocks such as power divider, resonators etc. The third part entails successful realization of a group project. The aim of this project will be to equip the students with some of the tools and technique used in the industry for the design of electronic circuits and systems.

The class provides an introduction to the design of digital circuits and computer architecture. It covers technical foundations of how a computing platform is designed from the bottom up. It introduces various execution paradigms, hardware description languages, and principles in digital design and computer architecture. The focus is on fundamental techniques employed in the design of modern microprocessors and their hardware/software interface.

This class provides a first approach to Computer Architecture. The students learn the design of digital circuits to understand the basics, understand the principles (of design), understand the concepts (in computer architecture).

Based on such understanding, the students are expected to: learn how a modern computer works underneath, from the bottom up, evaluate tradeoffs of different designs and ideas, implement a principled design (a simple microprocessor), learn to systematically debug increasingly complex systems, be prepared to develop novel, out-of-the-box designs.

This course provides material about controlling industrial processes and automating the production lines of the factories. Topics include the definition of industrial automation, an overview of the Factory Automation, programmable logic controllers (PLCs), PLC hardware components, PLC programming using Ladder logic, programming timers and counters, PLC installation, networking, Human machine interface (HMI), industrial sensors and actuators, function block diagram programming, structured text programming, sequential function chart programming, continuous function chart programming. CODESYS software will be used for simulating the PLC and HMI to practice programming. Siemens s7-1212C AC/DC/RLY together with Siemens totally integrated automation (TIA) platform will be used to practice PLC programming in the lab to get hands-on experience. Programming with LabView to have the supervisory control (SCADA) and some advanced topics in industrial automation will be considered as additional possible topics to be covered.

The main course aims are as follow:

1) The students will gain proper knowledge about the concept of the industrial automation
2) The students will become familiar with the state-of-the-art tools and techniques used in the field
3) The students will be able to compare several available tools and techniques with each other and pick the one which suits better the given problem
4) Students will practice working in a team for their course projects
5) The students will apply the gained knowledge in the course to design, simulate and implement a typical industrial automation system

This course offers comprehensive material on controlling industrial processes and automating production lines in factories. It covers the fundamentals of industrial automation, an overview of factory automation, and in-depth topics such as programmable logic controllers (PLCs), PLC hardware components, and programming techniques using Ladder logic, timers, and counters. Students will also learn about PLC installation, networking, human-machine interfaces (HMIs), industrial sensors and actuators, as well as various programming languages including function block diagrams, structured text, sequential function charts, and continuous function charts.

In the lab, students will work with the Siemens PLC S7-1200 and the C-IID/EV board, gaining hands-on experience with programming using the Siemens Totally Integrated Automation (TIA) platform. CODESYS software will be utilized for simulating PLC and HMI programming.

This course covers fundamental technologies of mobile information systems and wireless communication networks. Topics of study include characteristics of the mobile radio environment, propagation phenomena, cellular concept and channel allocation, dynamic channel allocation and power control, multiple access techniques: FDMA, TDMA, CDMA – system capacity comparisons. Several standard protocols for wireless networks (DAB, DVB, LTE, GSM, 802.11, 802.15 etc.) are covered. The is focus on qualitative descriptions and realistic explanations of relationships between wireless systems and performance parameters. Mobility support in network and transport layers is also included.

The main course aims are as follow:

• Introduces wave propagation characteristics and models.
• Provides students with up-to-date knowledge of the techniques and the principles underlying cellular network design.
• Introduces different wireless communication techniques and standards.
• Provides students skills in traffic engineering

This is an undergraduate introductory course in a relatively new discipline that investigates the topology and dynamics of complex networks, aiming to better understand the behavior, function, and properties of the underlying systems. The applications of network science cover physical, informational, biological, cognitive, and social systems. In this course, the students will study algorithmic, computational, and statistical methods of network science, as well as applications in communications, biology, and societal networks. The course will go beyond the strictly structural concepts of small-world and scale-free networks, focusing on dynamic network processes such as epidemics, synchronization, or adaptive network formation.

In order to let students truly learn through this course useful knowledge and techniques in the long term, this course emphasizes student involvement by focusing on experiments and data-driven projects thus, providing them the opportunity to enhance their career prospects by acquiring a key modeling tool in networks. The main topics that will be covered are:

1. Introduction to networks and their classifications
2. Network properties: small-world, power-law, and scale-free networks
3. Measures of centrality and assortativity
4. Network visualization and analysis
5. Community detection
6. Spreading phenomenon: epidemic models and information diffusion models
7. Percolation and robustness
8. Multiplex and temporal networks
9. Representation of learning on graphs and their limitations

This course is designed to train students in printed circuit board (PCB) design and manufacturing. PCB design is an integral part of each electronics products and this is a basic course to help students to design their own PCB projects. This course is designed to teach students how to design and layout PCBs for various electronics applications by giving students a comprehensive understanding of the design and fabrication of PCBs. The course includes theoretical and practical training, covering topics such as digital electronics, analog circuits, schematic capture, PCB layout, and design for manufacturability. The course also includes hands-on design projects, where students can design and fabricate their own PCBs using industry-standard design software and fabrication tools. They are also trained in using 3D design tools to visualize electronic components and circuits. The course not only touches on the technical aspects but also teaches students about the aesthetics of PCB design, including printed circuit board layout, various routing techniques, and proper placement of components. At the end of the course, students will have a good understanding of PCB design principles and practical experience designing and prototyping their own PCBs.

In recent years, the efficient use of RF and Microwave spectrum has become extremely critical considering the need of high data rate applications such as 5G and beyond services, satellite and military segments, and variety of consumer electronics services. It is imperative to note that these applications are heavily dependent on the RF and Microwave Circuits and Systems for the eventual reliability and robustness. This, therefore, necessitates the design of innovative RF and Microwave circuits, building blocks, and systems to facilitate the date hungry applications. This course aims to equip the students with the tools and techniques to design circuits and systems operating at RF and Microwave frequencies. The course, at first, introduces the students to the fundamental theory and analytical formulations which are required for understanding of RF and Microwave circuits and systems. The students will then learn extensively about the transmission lines and Smith chart. These concepts will then be utilized for learning impedance matching techniques, power dividers and power splitters, directional coupler, coupled line coupler, and filter. The course also covers some aspects of active design and aims to discuss some generic design techniques. During this course, the students will learn to analyze, design and develop some circuit components which utilize the theoretical concepts and commercial CAD simulators. The idea is to achieve agreement between the theoretical results and CAD simulated results.

The course provides the students with an introductory exposure and fundamental understanding of robotics and rehabilitation. In particular, it provides the theoretical knowledge of robot design, robot automatic control systems (position control, impedance control) and insight into selection of appropriate control systems based on different robots targeting different disability conditions. The course introduces students to fundamentals of human biomechanics and experimental techniques used in gait analysis to enable understanding of how such knowledge is necessary to evaluate human movement performance, a key aspect of characterizing the efficacy of rehabilitation robots. Through selected state-of-art literature, selected research and commercial grade rehabilitation robots are introduced, to provide students with a basic knowledge of the field. The course takes students through a “virtual” design and development process in the pretext of a term project whereby students design at least one example robot to illustrate the engineering principles of robot subsystems (sensors, actuators, motors, and controller). In addition, the course will introduce students to social and cognitive robotics. The course will also introduce students to the methodology for clinical study design, while introducing some seminal clinical studies/trials utilizing rehabilitation robots, highlighting their study rationale, experimental design, and key findings, as well as ethical and regulatory guidelines in the field of rehabilitation robotics.

The aim of this course is to introduce the principles of photonics, and its applications. At the same time, this course strives for providing students with a necessary knowledge of photonics components, which is fundamental for advanced course like Optical Communication, and Optical Sensors. The course can be structurally divided into four parts: 1) Introduction to optics and photonics, including: ray and wave optics formalism, their range of use, their applications and their connection with electromagnetic theory; laws of reflection and refraction, theory of diffraction, scattering and polarization; scattering matrix formalism; introduction to Fourier optics. 2) Guided optics, including: introduction to dielectric waveguide; mode theory in guided structures; slab waveguide and propagation conditions; integrated optical waveguides; propagation in optical fiber; practical description of optical fibers, their types, their properties and their applications. 3) Passive photonic component, including: power dividers, directional couplers and multiplexers; Fabry-Perot interferometers; transmission and reflection diffraction gratings; multimode interferometers; Mach-Zehnder interferometers; non-reciprocal components including polarization converters, isolators and circulators; gratings description and coupled mode theory; Bragg and Fiber Bragg gratings; long period gratings; non-uniform gratings; Fiber Bragg Gratings (FBG) applications. 4) Active photonic component, including: introduction to optical modulators; electro-optic modulator including phase, Mach-Zehnder, travelling wave and Lithium-Niobate modulators; acusto-optic modulators; saturable absorbers; theory of optical amplification; doped fiber amplifiers; Erbium Doped Fiber Amplifier (EDFA), properties and applications; semiconductor optical amplification; Raman amplification; LED and Super-luminescent LED; optical resonators and principles of lasers; semiconductor lasers; fiber lasers; characterization of emit

The objective of this course is to introduce students to fundamentals and applications of microfluidics. The course will provide knowledge on physics and theory of microfluidic principles, micro-/nano-fabrication of polymer microfluidic devices, materials and microfluidic components, and a wide range of applications of microfluidics through lectures and research case studies. Topics include but not limited to physics and principles of microfluidics; micro-/nano-fabrication technology; polymer microfabrication and components of microfluidic devices; mixers, integrated heaters; lab-on-a-chip devices, sensors and wearable microfluidics; microfluidics for cell culture, and a range of emerging applications of microfluidics.

Optical Communications course provides an in-depth overview of fiber-optic communications for high bit-rate/high-throughput. The course provides a description of fiber-optic communication networks. Starting from an in-depth analysis of the devices that are fundamental part of the optical communication network, such as single mode optical fibers, fiber amplifiers, optical switches, filters, multiplexers, and photodetectors, the course aims to set the basis for assessment of network performance and for the consequent network design. The effect of attenuation, dispersion, and non-linearities will be quantified and standard methods of compensation of those effects will be discussed. Protocols for 10-100 Gbit/s data communication over long-haul links are discussed.

Finally new trends on signal modulations, applied to optical communication, will be exposed as an overview of future optical fibers network.

Modern wireless communications course offers a comprehensive exploration of wireless technology, equipping students with knowledge and skills to understand, design, and optimize wireless communication systems. The course covers wireless principles, spectrum regulations, and core transmission fundamentals like modulation and error correction. The curriculum includes multiple access schemes enabling efficient spectrum sharing and an examination of diverse wireless network architectures, from cellular to ad-hoc setups, addressing challenges like noise, fading, and dynamic channels. Communication quality parameters are scrutinized, along with techniques for system optimization, encompassing link budget analysis, antenna design, and interference control. Advanced topics like multiple antenna technologies (e.g., MIMO) and emerging trends like massive MIMO, millimeter-wave communication, and IoT are explored. Students gain insights into real-world protocols like IEEE 802.11 (Wi-Fi), Bluetooth, Zigbee, LTE, and 5G NR. The course concludes by envisioning the future of wireless, covering 6G and beyond, wireless security, edge and cloud computing integration, and privacy concerns. Graduates will navigate the dynamic world of wireless, contribute to innovations, and tackle intricate challenges in this ever-evolving field.