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The new 2-year MSc-ECE degree program represents an upgrade of the previous 1.5-year program, aiming to bring research as a transversal element.
As its predecessor, this is a specialized degree program offered by School of Engineering and Digital Sciences (SEDS) at Nazarbayev University (NU). Students are required to complete 120 ECTS credits, in 4 semesters, which satisfy requirements stipulated by the Bologna Process and the European Credit Transfer and Accumulation System (ECTS) for Master’s Courses. The program is designed to provide advanced skills and a detailed knowledge base at the graduate level for individuals working in academia, industry or research in Kazakhstan, region or throughout the world.
The MSc ECE provides a comprehensive technological and scientific preparation for engineers in 2 (two) key areas of Electrical and Computer Engineering: (a) Electrical Engineering; and (b) Computer Engineering.
MSc ECE program aims:
- To train engineers to analyze data and resources to make effective decisions and to effectively function on or lead multidisciplinary teams within an organization;
- To prepare graduates to effectively organize, plan and develop scientific research oriented to continue their higher-level preparation as scientists or to excel in operating and performing their future engineering duties at mid-managerial level in a modern industrial environment;
- To prepare the engineers to perform costs and fundamental technical assessments, with strictest and highest professional and ethical standards, while implementing principles of sustainability, safety and social responsibility in every application of the discipline; and
- To develop the new generation of Electrical and Computer Engineers to support the economic development of Kazakhstan by enabling the creation of start-ups oriented to the production of modern and highly technological goods and services.
Applicants applying to the Program are expected to have:
1. An undergraduate degree (Bachelor’s degree or equivalent).
During the application period final year students may submit official current transcript for consideration.
2. A minimum CGPA of 2.75 out of 4.0 (or equivalent).
3. High level of English proficiency.
The absolute minimum requirement for English language proficiency test reports for admission to the program is:
1) Overall IELTS test score of 6.5 (with sub-scores no less than 6.0) or the equivalent TOEFL score as posted on the ETS website;
2) Candidates with not sufficient IELTS score may be admitted to the ZERO-year program:
The absolute minimum requirement for English language proficiency test report for conditional admission (NUZYP) is an overall IELTS test score of 5.5, with no more than one sub-score of 5.0, or the equivalent TOEFL scores as posted on the ETS website;
3) Applicants, at the discretion of the Admissions Committee, can be exempted from submitting the language proficiency test report if:
- one of their earlier academic degrees was earned in a country with English as the language of official communication, academic instruction and daily life;
- an undergraduate and/or graduate degree was earned in a program which was officially taught in English.
4. strong reading, analytical and mathematical skills as demonstrated by GRE test (optional). Although an official GRE score is not an essential requirement, an applicant can enhance her/his application with a competitive GRE score;
5. High motivation and strong interest in the program as outlined in a statement of purpose;
6. A curriculum vitae;
7. Two letters of recommendation.
Application package checklist:
1. Complete Application form;
2. National ID (for the citizens of the Republic of Kazakhstan) and passport (for international applicants);
3. Official document confirming name change (if applicable);
4. Bachelor’s (or equivalent) degree diploma with transcript;
During the application period final year students may upload official current transcript for consideration.
5. IELTS or TOEFL certificate valid as of date of online documents submission;
6. Document confirming English as the language of instruction (only for applicants who earned their degree in a program which was taught in English and request an exemption from submitting IELTS or TOEFL).
Applicants should provide a detailed certificate/reference from the university indicating the number and list of subjects completed in English.
7. Curriculum vitae (up to 2 pages);
8. GRE/GMAT certificate valid as of date of online documents submission (if applicable);
9. Statement of purpose (up to 1 page);
10. Two confidential letters of recommendation (at least one academic reference) written within the last 12 months (to be provided by referees electronically or in hard copy after receiving an email request);
11. Consent for Applicant’s personal data processing (according to the template in applicant’s personal account).
All required documents indicated above (excluding letters of recommendation) must be uploaded by candidates to the Personal account before the indicated deadline.
All submitted documents shall be in English or with notarized English translation.
Submission of a complete application package does not guarantee admission to the Program.
Applicants recommended for admission must provide hard copies of all documents as requested by the Admissions Department within established period of time.
Applicants who obtained their degree diplomas/certificates from foreign education institutions must request their official transcripts to be sent directly to the University: 010000, Astana, Kabanbay Batyr Ave., 53, Nazarbayev University, Admissions Department.
Program Learning Outcomes (LOs)
On successful completion of the program the students will be able to demonstrate the ability
- to design, discuss and generate new ideas in a specialization of study chosen from the fields of electrical engineering or computer engineering;
- to identify, evaluate and elaborate advanced electrical and computer engineering problems and apply knowledge of mathematics and science to solve those problems;
- to determine, interpret and test current knowledge, technology, or techniques within their chosen electrical engineering or computer engineering specialization electives;
- to communicate, compose and discuss new ideas in writing through term projects and individual Master's Thesis.
In this course, you will be introduced to the concepts and definitions of charges, currents, voltages, power, and energy. You will learn the voltage- current relationship of basic circuit elements – resistors, inductors, capacitors, dependent and independent voltage and current sources; apply Kirchhoff‟s current and voltage laws to circuits to determine voltage, current and power in branches of any circuits excited by DC voltages and current sources. Apply simplifying techniques to solve DC circuit problems using basic circuit theorems and structured methods like node voltage and mesh current analysis. The goal also includes derivation of the transient responses of RC and RL circuits, steady state response of circuits to sinusoidal excitation in time domain, application of phasors to circuit analysis, introduction to nonlinear electronic devices such as diodes, MOSFETs.
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 transform (derivation, properties, convergence). Laplace transform (properties, convergence), inverse Laplace transform. Introduction to Z transform (time-permitting).
An introductory course to practical aspects of digital system design. The course covers digital logic design, including Boolean Algebra, basic design concepts and implementation technology, number representation, synthesis and design of combinational and sequential logic, and hands on experience in a lab. Pre-requisite: Calculus II
Electromagnetics is the science underlying wave transmission, propagation, interaction, and detection. The aim of the module is to provide the insights and the engineering perspective to electromagnetics and wave propagation. Maxwell‟s equations, and the lumped element model of transmission lines, are the starting point for the analysis that encompasses transmission lines, static and dynamic problems, plane wave propagation, transmission, and reflection. Through the cycle of lecture, the students will become familiar with the electromagnetic concepts and their application, and will gain insight on solving problems that involve waves. The course revolves around 6 pillars: the mathematical description of electromagnetics: phasors and vectors algebra; transmission lines and their analysis, including Smith chart methodology; statics, solution of Maxwell equations in time-invariant fields; time-varying fields and their solutions; plane wave propagation, reflection, transmission, and polarization; waveguides and devices. Through the course, emphasis will be given on practical aspects and applications of the electromagnetic principles to telecommunications, sensors, data transmission, biomedical applications.
In this course, you will be introduced to network theory and circuits analysis. You will learn Voltage & Current source transformations, Wye & Delta transformations, Superposition theorem, Thevenin‟s & Norton‟s theorems, Maximum Power Transfer theorem, Reciprocity theorem, Compensation theorem, Millman‟s theorem, Tellegen‟s theorem- statement & Applications. AC Analysis: Concepts of phasor & complex impedance/Admittance – Analysis of Simple series and parallel circuits – Active power, Reactive power, Apparent power (Volt Amperes), Power Factor and Energy Associated with these circuits – concepts of complex power – phasor diagram, impedance triangle & power triangle associated with these circuits. Resonance: Introduction – series resonance – parallel resonance – Definition: Q factor – half power frequency – resonant frequency – Bandwidth – Mathematical Expression for Different types of Resonant circuit. Coupled circuits: Mutual inductance – Co-efficient of coupling – Dot convention – Energy consideration – Analysis of Coupled circuits 3-phase circuits: Poly phase system – phase sequence – Analysis of 3 phase Balanced/Unbalanced circuits – power and power factor measurement. Source free and forced response of RL, RC and RLC series circuits – Forced response of RL, RC and RLC series circuits with sinusoidal excitation – time constant & Natural frequency of oscillation – Laplace transform application to the solution of RL, RC & RLC transient circuits, MOSFET models
In this course, the objective is to understand the basic concepts in the design of electronic circuits using linear integrated circuits and their applications in the processing of analog signals. MOSFET characteristics, MOSFET models, Inverting & Non-Inverting amplifiers – voltage follower – summing and differential amplifiers – AC amplifiers Differentiator & Integrator – precision rectifiers – clipper and clamper circuits – log and anti-log circuits – Instrumentation amplifier - comparator and its applications. Analog Multiplier using Emitter Coupled Transistor Pair - Gilbert Multiplier cell Variable transconductance technique- analog multiplier ICs and their applications- Operation of the basic PLL- Closed loop analysis Voltage controlled oscillator- Monolithic PLL IC 566-Application of PLL. Analog switches- High speed sample and hold circuits and sample and hold ICs- Types of converter- Performance specifications-D/A conversion circuits:R-2R & inverted R-2R Ladder- D/A converters-A/D conversion circuits :Successive approximation, dual slope and flash A/D converters
This course introduces relevant topics in computer design. This includes computer system interconnection structures, central processing unit, control unit, microprogrammed control, memory organization, cache and virtual memory, computer arithmetic, RISC processors, introduction to parallel processing. The students will practice the concepts using various case studies. Pre-requisite: Digital Logic Design
This course provides the foundations on digital signal processing covering a range of topics including DFT, Z transforms, LTI systems, IIR and FIR filters. Fourier and Z transform would be utilized to system stability and its transfer function. Time and frequency domain techniques for designing, building and testing IIR and FIR filters would be explored in detail.
Pre-requisites: Signals and Systems
The general purpose of the module is to have the students exposed to the fundamentals of magnetics and electromagnetic energy conversion and its applications to basic electrical machines and drives. Topics covered include: Fundamentals of electricity, magnetism and electromagnetic energy conversion, Torque generation principles, DC motors and generators, efficiency and heating of electrical machines, Ideal transformers, practical transformers, three-phase transformers, Armature Windings, polyphase Synchronous motors and generators, permanent magnet motors, polyphase Asynchronous motors, stepper motors, Applications of electrical machines and drives, Controls of DC motors, brushless DC and AC motors, Variable Speed Drives (VSD)
This course covers a wide range of topics in analog and digital communication systems including; Amplitude modulation types and demodulation, angle modulation and demodulation, sampling and quantization, additive white gaussian noise, and baseband and passband digital modulation techniques. Laboratory assignments train students in design aspects and performance analysis of different systems, techniques and methods in modern communication systems.
This unit introduces students to the core knowledge of power systems analysis and modelling. The course 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. This course will cover, introduction to power system analysis, and three phase systems, per unit quantities, change of base, power system modelling, capacitance of transmission lines, bus admittance matrix, types of buses, formation of power flow equations using Ybus matrix, Power flow studies, Gauss-Seidel method, and Newton-Raphson method.
Architecture, structure and programming language of typical microprocessors and micro-controllers. Sample microprocessor families. Memories, UARTS, timer/counters, serial devices and related devices. Interrupt programming. Hardware/software design tradeoffs. This will be run concurrently with a micro process lab.
Pre-requisite: Digital Logic Design and Computer Architecture
Design of data converters using sigma–delta techniques. Operation and design of custom digital filters for decimating and interpolating in analog–to–digital interfaces.
The course deals with crystals, bipolar transistors (BJT, HBT) and eld effect transistors (MOSFET, MESFET, pHEMT), PIN diodes, varactor, Schottky diode, tunnel diode, IMPATT and Gunn diode. Component structure, function and applications. Packaging and assembly.
An introductory course in analog circuit synthesis for microelectronic designers. Topics include: Review of analog design basics; linear and non- linear analog building blocks: harmonic oscillators, (static and dynamic) translinear circuits, wideband amplifiers, filters; physical layout for robust analog circuits; design of voltage sources ranging from simple voltage dividers to high-performance bandgaps, and current source implementations from a single resistor to high-quality references based on negative-feedback structures.
This course covers the analysis and design of digital integrated circuits using CMOS technology. The course emphasizes design, and requires extensive use of MAGIC for circuit layout, and HSPICE and IRSIM for simulations. The main list of topics: CMOS Inverter, Combinational Logic, Arithmetic Structures / Bit Slice Design, Sequential Circuits, Interconnect Clock Distribution, Memory Advanced Voltage Scaling Techniques, and Power Reduction Through Switching Activity Reduction.
This is an introductory course which covers basic theories and techniques of digital VLSI design in CMOS technology. In this course, we will study the fundamental concepts and structures of designing digital VLSI systems include CMOS devices and circuits, standard CMOS fabrication processes, CMOS design rules, static and dynamic logic structures, interconnect analysis, CMOS chip layout, simulation and testing, low power techniques, design tools and methodologies, VLSI architecture.
To familiarize students with the behavior of deep sub-micron (DSM) CMOS devices, including an understanding of how to design the device to obtain the desired characteristics, experimental techniques for characterization, and mathematical models to represent the device in a circuit simulation environment. Characterization of MOS Capacitors: C-V and charge pumping measurements, gate current modeling, MOSFET I-V Model, Short Channel Effects, Drain and Channel Engineering, includes hot carrier effects latch-up and breakdown, Silicon-on-Insulator MOSFET, MOSFET Model for Transient Simulation, New device structures and materials
It is expected that from this course the students will become familiar with basic principles of various computational methods of data processing that are commonly called computational intelligence (CI). This includes mainly bottom-up approaches to solutions of (hard) problems based on various heuristics (soft computing), rather than exact approaches of traditional artificial intelligence based on logic (hard computing). Examples of CI are nature- inspired methods (artificial neural networks, evolutionary algorithms, fuzzy systems), as well as probabilistic methods and reinforcement learning.
"RF and microwave circuit design is used in many electronic systems and components such as radar, wireless communications, GPS, and aerospace systems. The aim of this module is to introduce modern concepts such as computer aided design techniques used in design and implementation of RF circuits and systems and circuit layout considerations including distributed effects, coupling, parasitic effects, and other design issues. The students will become familiar with concepts such as nonlinearity including intermodulation, harmonic distortion, and AM/PM conversion, representation of noise in circuits including noise figure, and dynamic range, transmission lines, Smith charts, and network parameters, RF and microwave active and passive components, microwave amplifier types including low-noise, power, broadband, two-stage, feedback, filters, microwave couplers and power dividers and Wilkinson combiners."
"Radio frequency integrated circuit (RFIC) design has become an essential part Wi-Fi, mobile phone, wireless infrastructure, Bluetooth device, and the emerging Internet of Things (IoT) technologies. This course covers the fundamentals of RFIC design techniques. In this course you will learn RFIC design techniques, tools such as design rule check (DRC) and layout vs. Schematic (LVS), knowledge of the device technologies, circuit topologies and concepts and design and layout. In addition, you will also cover the following topics: RFIC technologies including Bipolar, CMOS, and GaAs, Noise, Noise Figure, and Linearity, amplifier class of operation, Low Noise Amplifier and Power amplifier design, Differential Circuits, Mixer Design, Passive On-Chip Components, Circuit Layout, Thermal Management, Packaging, Current Mirrors and Biasing."
"Big data has found imminent applications in various fields such as medicine, signal processing, education, etc. Extraction of implicit and potentially useful information from data is the ultimate goal in big data mining. Big data can be “big” either in terms of sample size, number of variables (dimension), or both. Machine learning techniques that can be used for “large-sample” data is substantially different from “large-dimension” data. The aim of this course is to first give an introduction to machine learning as the technical basis of data mining and then introduce various machine techniques that can be used for big data mining. We will cover suitable methods for analyzing large-dimension and large-sample data."
"This course covers the fundamental theory of radio frequency (RF) power amplifiers and their applications in wireless communications circuits and transmitter systems. In this course you will learn about the role that power amplifiers play in microwave systems including transmitters in terms of power, efficiency, and linearity. Transmitter design including upconverters and mixers are covered. You will also learn power amplifier topics including load-line impedance, power combining, non-linear device models, bias circuits, classes of operation, and impedance matching.
RF power passive and active devices are also discussed including load-pull measurements for high power and efficiency. High efficiency power amplifiers including class E and F mode amplifiers, linearization and efficiency enhancement techniques including pre-distortion are covered. Power amplifier architectures including multiband, broadband, and high efficiency Doherty, and envelope tracking amplifiers are also covered."
"This course talks about the principle of operation of AC machines in detail along with their modelling and simulation. The course main emphasizes AC machines such as 3-phase transformers, synchronous and asynchronous machines. The course start with the principle of operation of three phase transformers followed by voltage regulation and efficiency in transformers, parallel operation of transformers, open-delta connection, 3-phase auto transformer. This is followed by principle of operation of synchronous generators, equivalent circuit of synchronous machine, power and torque derivations, synchronous machine model parameters, parallel operation of synchronous generators, transient modelling of synchronous machine. This is followed by synchronous motor principle of operation, equivalent circuit, starting methods, and torque equation. This is followed by asynchronous machines (single phase and polyphase) principle of operation, induction generator versus induction motor, torque-speed characteristics, starting methods, speed control, and model parameter estimation. The unit ends with detailed discussion on industrial applications of various machines."
The course examines the application of electronics to energy conversion and control. Topics covered include: types and performance of power semiconductor devices; modelling and analysis of AC-DC (rectifier), DC-DC, and DC-AC (inverter) power converters; selection of power electronics circuit components based on electromagnetic stress; analysis of converter voltage / current steadystate operation waveforms and their frequency spectra using theory and simulations. Prospective applications such as motion control systems, power supplies, and grid-connected for renewable energy shall be discussed.
"This course aims to provide knowledge on power transmission and distribution systems design and implementation, it is also discuss on IEC standards, regulations, demand calculation, equipment selection, loss and performance control in power systems, different levels of power transmission and distribution operation rules as well as HV substation design and performance, power factor improvement, principles, low-voltage fundamental regulations along with neutral wiring system design in distribution network and their calculations, lowvoltage distribution network design and component capacity calculation, distributed generation and renewable energy (solar and wind generation), active and reactive power compensations, substation transformer selection, BAY design and bus-bar calculations, power quality introduction, distribution system de-rating, EHV and HVDC transmission lines, radial and ring dispatch in distribution network and end user voltage drop calculation and heat generation in components."
This course aims to provide fundamental knowledge and practice required for operating high voltage systems, training of students on electrical energy and power system field properties and materials, electrodynamic force calculations, thermal behavior and ratings calculations, electrical contact behavior, a detailed coverage of liquid, gas and solid insulators, bushings, cable insulators, over headline insulators design, selection, and assessment, specific items in High Voltage (HV) field including transformers, switchgear, CTs, PTs, insulation systems, cables, overhead lines, surge arresters, and earthing systems, switching and lightning standard signals, and calculation of their influence on high voltage apparatus.
The course aims to provide the student with the fundamentals of electrical industrial and commercial power systems: design, demand calculation, maintenance, load calculation, international electrical industrial standards, management and operation. In specific, it provides practical and essential knowledge for designing the electrical distribution infrastructure in large commercial buildings and industrial sites. Particular emphasis is on compliance with current practices and regulations within Eurasia. The course also touches on some aspects of utilization. Regulatory aspects, harmonic analysis and mitigation technique in industrial and commercial power system, commercial and industrial low voltage switchboard design, earthing system and safety regulations, underground cabling systems and sizing for large industrial workshops and factories, designing neutral system in industrial and commercial structure, surge protection for buildings, lightning rod system design and calculation, electrical lighting systems, energy efficiency and electricity management, power quality and the effects of voltage and current distortion on feeder and equipment, escalator and lift traffic analysis, feeder loading and overloading in industrial and commercial sites, distributed generation for industrial and commercial buildings and introduction to the smart workshop and smart building and metering systems will be discussed in this course. This is an essential course for electrical engineers which are planning to work in industry or doing research in electrical engineering, specifically those who are working in electrical distribution system
This course introduces students to the fundamentals of power systems protection and relaying. It discusses the types of faults and their calculation using symmetrical components methods; electromechanical relay principles; relaying transducers - voltage and current transformers; transmission line protection overcurrent, directional, distance, out-of-step protection; primary and backup protection zones, discrimination of relay time and current settings. The detailed list of topics to be covered in this course are: Introduction to protective relaying, fundamental units – per unit and per cent values, phasors and polarity, non-symmetrical faults and method of symmetrical components, relaying transducers – voltage and current transformers, protection fundamentals, ground fault protection and reclosers, overcurrent protection, directional protection, distance protection, out-of-step protection.
This course aims at making the students aware of the system level aspects of the power system and electrical energy, standard practices in stable, economic and reliable operation of the power system. To put it in simple words, it encompasses all the electrical power concepts taught in the curriculum so far will be discussed from the application prospective. In this unit, the following topics are included: Detailed modeling of polyphase synchronous machines (PSM), different modes of operation, active and reactive power management in PSM. Following the PSM modelling, the stability problem in power system will be introduced. Under this topic, different types of stability determination criteria, power-angle equation, equal-area criterion for stability, multi-machine stability, solution of swing equation will be discussed. The economic operation of the electrical energy with special emphasis on load frequency control, economic dispatch, automatic generation and unit commitment problems. The course introduces the (N-k) contingency analysis (CA) of power system and various method used in the analysis, power system network reduction techniques will also be taught. Following the CA, the principles of state estimation are introduced at the end.
This course primarily aims at introducing the fundamentals of power generation technologies, systems along with the economic aspects and feasibility study. After going through this course, the students will get a thorough knowledge on thermal, hydro, gas and nuclear power plant operation and management, different substation configurations, economics of power generation systems, and cogeneration trigeneration technologies.
The fundamentals and practice of computer networks, with emphasis on the Internet. The structure and components of computer networks, packet switching, layered architectures, TCP/IP, physical layer, error control, window flow control, local area networks (Ethernet, Token Ring, Token Bus, DQDB and FDDI), network layer, congestion control, and quality of service.
Prerequisites: Computer Architecture
This is an advanced level course in communications. The course aims at giving to the students a deep knowledge of the fundamental principles of digital communications. The material that will be covered is as follows: Signals and Spectra, Analog-to-Digital Conversion, Digital Transmission and Reception, Gram-Schmidt Orthogonalization, AWGN, BER over AWGN, Digital Modulation (Baseband and Passband), Bandwidth Efficient Digital Modulation Techniques and Digital Communication over Channels with Intersymbol Interference.
This course studies fundamental concepts of optimization from two viewpoints: theory and algorithms. It will cover ways to formulate optimization problems (e.g. in the primal and dual domains), study feasibility, assess optimality conditions for unconstrained and constrained optimization, and describe convergence. Moreover, it will cover numerical methods for analyzing and solving linear programs (e.g. simplex), general smooth unconstrained problems (e.g. first-order and second-order methods), quadratic programs (e.g. linear least squares), general smooth constrained problems (e.g. interior-point methods), as well as, a family of non-smooth problems (e.g. ADMM).
This aim of this course is to help students understand the data communications and networking fundamentals, starting from the protocols used in the Internet in particular by using the OSI model protocols layering, and concentrates on the characteristics of the transmission media, applied transmission and coding, and medium access control. The module covers a detailed WANs and LANs networks respectively, describing the wired Ethernet and Internet and concludes by examining security. The students will apply their knowledge in the labs by building increasingly more complex data communication scenarios.
The course provides fundamentals and insights on fiber-optic communications. Topics: Optical fibers: propagation, modes, Schroedinger‟s equations; Devices for communications: LED, lasers, photodiodes (coherent and incoherent detection), electro-optical modulators, amplifiers, passive devices, filters; Single-span non-amplified systems; Single-span amplified systems; multi-span systems; wavelength division multiplexing (WDM); dispersion and its management: modal, chromatic, polarization dispersion; Non-linear effects: self-phase modulation, cross-phase modulation, four-wave mixing, scattering. Multiplexing: polarization division multiplexing, spatial division multiplexing. Modulation formats and coherent detection.
The course provides the fundamentals of optics and photonics, for the use in engineering and systems. The course describes the fundamentals of optics and photonics components and applications and describes both the main devices and the main formulation of light propagation and reflection. The course will be divided into 4 parts: (1) Introduction on electromagnetic and wave optics, plane waves, polarization, scattering matrix formality. (2) Optoelectronics and devices: LED and SLED, laser, photodetector, devices (coupler, splitter, resonator, circulator, polarization filter). (3) Ray optics: ray optic, Gaussian beams, lens and focusing, Fourier optics, fiber optics, guided propagation, modes, graded index optics. (4) Applications: gratings and grating solver, statistical optics and Monte Carlo, imaging and endoscopy, fiber optic communications.
Digital Image Processing (DIP) is referred to use of digital computers to process digital images. This includes any processes where the input and output are both images, or the input is image and the output are attributes, which are extracted image information suitable for processing. The interest in DIP stems from two basic areas: (1) improvement of pictorial information for human interpretation; and (2) processing of image data for storage, transmission, and machine perception. The aim of this course is to introduce fundamental methods in digital image processing.
Stochastic processes and modeling is the foundation of many signal processing algorithms used in radar, sonar, speech and image analysis, and communications. The aim of this module is to introduce fundamental concepts in stochastic processes and modeling. In order to simplify these concepts, we take an approach using which we attempt to develop in students an intuitive feel for these concepts that enables them to “think probabilistically”. Based on this background, we will then cover more advanced concepts such as different families of random processes and their applications in modeling, linear filtering, and prediction. MATLAB will be used during the labs to provide students with motivating exercises and provide a “hands-on” approach to the subject, which essentially promotes a better understating.
This is an advanced level course in digital signal processing covering a range of topics including stochastic signal processing, parametric statistical signal models, and adaptive filtering, application to spectral estimation, optimum FIR filter design and implementation, multirate Signal Processing, Time-Frequency representations, filter banks, adaptive filtering (if time permits).
Pre-requisites: Digital Signal Processing
This course covers fundamentals of wireless sensor networks, architecture, protocols, and performance. After completing this course, you should understand the principles of WSN and be able to design and maintain WSNs. Topics include: Wireless technology for distributed sensor networks, clustering techniques in WSN, routing in WSN, WSNs security, industrial WSN protocols, WSNs design, implementation and management. Performance of WSNs including simulation analysis.
Prerequisites: Wireless Networks
"The course aims to introduce the concepts, development cycle and applications of reconfigurable computing, especially using Field Programmable Gate Arrays (FPGAs). The course will cover the fundamental architecture of commercial FPGAs (such as Xilinx Virtex series and Intel Stratix series), how different digital circuits can be mapped into this architecture and developing FPGA targeted digital circuits through hardware description languages (VHDL, Verilog). The course will cover the different development stages of FPGA based system design such as design specification through HDL, synthesis, mapping, placement and routing and the configuration file generation. There will be sufficient emphasis on digital circuit simulation for functional verification as well as timing verification using industry standard simulators (such as Xilinx iSIM and Mentor Graphic‟s modelSim). For design implementation, students will be introduced to industry standard design tools such as Xilinx Vivado and Intel Quartus Prime software design suites. Students are also expected to complete a project work which encompasses the concepts covered in the course in the implementation of a hardware accelerator and demonstrate it on an FPGA platform. The course will also discuss current challenges faced by the reconfigurable computing community and some of the research directions."
The course focuses to understand the underlying technologies that make contemporary operating systems work efficiently. The course will study and discuss file system, processes, threads, synchronization, I/O, file systems, memory management, transactions, security threats and attacks, and system coordination techniques. In addition, through this course we will discover how these technologies are integrated into the systems we use today and then apply these technologies to practical applications. The course will have projects and programming tasks that need to be presented inclass.
Prerequisites: Data Structures and Algorithms
This course builds upon the computer architecture course and discusses advanced topics in a computer system design. Topics covered include modules and hierarchy, processes, ports and signals, data types and simulation. CPU performance, its factors and evaluating performance. Instruction set principles and Examples, classifying instruction set architectures, memory addressing, type and size of operands, operations in the instruction set, instructions for control flow, encoding an instruction set, role of compilers, MIPS Instruction Set Architecture. Advanced processor concepts such as datapath and Control, building a datapath, single cycle implementation, multi-cycle implementation, exceptions, micro-programming, hard-wired control, enhancing performance with pipelining, pipelined datapath, pipelined control, data hazards and forwarding, data hazards and stalls, control hazards, exception handling. Instruction level parallelism, caches and memory hierarchy design, multiprocessors and clusters, programming multiprocessors, multiprocessors connected by a single bus, multiprocessors connected by a network, clusters, network topologies, chip multiprocessors and multithreading. Vector processors, basic vector architecture, vector length and stride, enhancing vector performance, effectiveness of compiler vectorization. Advanced topics in disk storage, real faults and failures, I/O performance, reliability, measures and benchmarks.
This course is offered to graduates and includes topics such as mathematical models of systems from observations of their behavior; time series, state-space, and input-output models; model structures, parametrization, and identifiability; non-parametric methods; prediction error methods for parameter estimation, convergence, consistency, and asymptotic distribution; relations to maximum likelihood estimation; recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; bounded but unknown noise model; and robustness and practical issues.
Formal models of discrete event systems, computer simulation of models, and analysis of simulation results. Discrete-event simulation is applied to studying the performance of computer and communication system. Prerequisites: Probability and Statistics, Computer Networks
"This course covers the fundamentals of power system optimization, stability and security. The prior emphasis will be given to the system level aspects of power grids and standard practices/analysis required to assess the stability and reliability of the power system. Therefore, the essential tools and analysis used by the system operators will be introduced. Also, detailed modeling of synchronous machines and bulk power systems along with their simulation in state of the art virtual environments such as Power World Simulator, MATLAB-Simulink etc. will be taught. In brief, this module encompasses all the essential concepts required for secure, efficient and optimal operation of electrical power system. "
Provides fundamental knowledge of, and practical experience with, database concepts. Includes study of information concepts and the realization of those concepts using the relational data model. Practical experience gained designing and constructing data models and using SQL to interface to both multi-user DBMS packages and to desktop DBMS packages.
Prerequisites: Operating Systems
Cybersecurity has become crucial for individuals, organizations and nations. This course will introduce students to the basics of cybersecurity and applied cryptography. Students will learn the fundamentals of computer and network systems security including the importance of cybersecurity, authentication, attacks and intrusions, encryption and decryption, networking and wireless security, vulnerability analysis and defense. Students will also learn the underlying scheme for designing and analyzing a secure system
This course primarily focuses on mathematical reasoning and problem solving. As such, it covers the fundamentals of automata and logic, proof techniques, induction/recursion, counting, advanced counting, relations, and graph theory. These mathematical concepts and tools are critical to solve many problems in computer engineering and/or computer science. In particular, the course covers: The Foundations: Automata, Logic, and Proofs; Basic Structures; Algorithms; Number theory; Graphs; Induction and Recursion; Advanced Counting Techniques; Relations.
The course focuses on basic and essential topics in data structures, including array-based lists, linked lists, skip-lists, hash tables, recursion, binary trees, scapegoat trees, red–black trees, heaps, sorting algorithms, graphs, and binary tree. These data structures will be used as tools to algorithmically design efficient computer programs that will cope with the complexity of actual applications.
Antennas and Microwaves is an advanced module intended for those interested in working in the Telecommunication field. Topics covered include transmission lines including coaxial, twin-wire, circular, rectangular waveguides, TE, TM, TEM propagation modes, optical fibres, free-space electromagnetic wave propagation, atmospheric attenuation, diffraction, Fresnel zones, electrically small antennas including monopole, dipole, slot, PIFA, loop, microstrip patch, aperture and reflector antennas, broadband antenna including travelling wave, spiral, antenna feed structures including baluns and power dividers and antenna properties including gain, polarization, radiation patterns. You will be able to explain the principles of antennas and propagation required for wireless communications applications and to develop a thorough understanding of models for various radio frequency (RF) transmission line systems and to explain basic antenna properties such as gain, directivity, efficiency, polarization, antenna patterns, to explain electromagnetic wave propagation issues in urban environments, and to solve basic antenna and propagation design problems such as link budget, line loss, and attenuation.
The course will provide an up to date treatment of the fundamental techniques and algorithms of computer and network systems performance modeling, simulation and measurement. Special emphasis will be given to discrete event simulation. The application of these techniques will be demonstrated by case studies and examples. Prerequisite: Computer Networks
This interdisciplinary course aims to develop an understanding the basic principles in Biomedical Engineering and Biophysics. During the semester will be covered topics for both fields such as history, major state-of-the-art research and development technologies, promising applications for human treatment diagnostics and others; Students will also learn fundamentals of research, and clinical/hospital techniques/methods/technologies applied in Biomedical Engineering and Experimental Biophysics, developing bio-materials for use in medicine and elements of the tissue engineering. It will be focusing on the relevant biological and engineering-related issues including complex cell culture and structure, extracellular matrix biochemistry and tissue organization, muscle and bone regeneration, scaffold fabrication and nanoscopic optical and topographical characterization. Course is open to upper level undergraduate students enrolled in Bachelor programs in Engineering, Physics and Biology.
Course materials are designed for students, who have basic knowledge of semiconductor materials science. The course will introduce students the modern characterization techniques widely applied in the semiconductor industry including electrical, optical, chemical and physical methods. 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 in an actual laboratory.
|Year 1: Fall Semester (Semester 1)|
|TYPE||COURSE CODE & TITLE||ECTS|
|Program Core||MSC 601, Technical Communication||6|
|MSC 602, Advanced Applied Mathematics||6|
|MECE603, Advanced Data Structures And Algorithms||6|
|MECE 724, System Modelling And Control||6|
|MECE605, Probability And Statistics For Electrical and Computer Engineers||6|
|Year 1: Spring Semester (Semester 2)|
|TYPE||COURSE CODE & TITLE||ECTS|
|Program Core||MSC 600, Research Methods and Ethics||6|
|MECE 600, Research Seminar||6|
|MECE606, Embedded Systems And Applications||6|
|Elective||ELECTIVE 1 (Pick on from Electives Pool)||6|
|ELECTIVE 2 (Pick on from Electives Pool)||6|
|Year 2: Fall Semester (Semester 3)|
|TYPE||COURSE CODE & TITLE||ECTS|
|Program Core||MECE601, Master Thesis I||24|
|Elective||ELECTIVE 3 (Pick on from Electives Pool)||6|
|Year 2: Spring Semester (Semester 4)|
|TYPE||COURSE CODE & TITLE||ECTS|
|Program Core||MECE 602, Master Thesis II||24|
|Elective||ELECTIVE 4 (Pick on from Electives Pool)||6|
Program Elective Courses
1) Area: Devices and Circuits:
- Advanced Electromagnetics
- Semiconductor Devices
- Advanced Topics in Mixed Signal Circuit Design
- Advanced Photonics
- RF Circuits
- Pattern Recognition
2) Area: Power and Control Engineering:
- Modern Control Theory
- Industrial and Commercial Power Systems
- Advanced Power System Protection
- Advanced Power Electronics
- Renewable Energy
- Pattern Recognition
3) Area: Signal Processing and Communication Systems:
- Adaptive Signal Processing
- Wireless Communications
- Optical Communication
- Wireless Sensor Networks
- Communication Systems
- Internet of Things
- Pattern Recognition
4) Area: Computer Engineering:
- Computer Communication Networks
- Parallel and Advanced Computer Architecture
- Computer and Network Security
- Advanced Microprocessor Systems
- Security of E-Systems and Networks
- Internet of Things
- Pattern Recognition
|Block||Room||Laboratory Name||Courses Taught|
|3||132||Power and Machines Laboratory||Electrical Machines and Drives, Power Systems Protection, Power Transmission and Distribution Plants|
|6||120||Semiconductor Characterisation Laboratory||Integrated Circuit design (2017-16); Microelectronics (2016); Mixed Signal design (2016,19)|
|3e||121||Power Systems Laboratory||Power System Analysis 1, Power System Generation, Power System Analysis 2|
|3e||123||High Voltage Engineering Laboratory||High Voltage Engineering, Industrial and Commercial Power Systems, Power System Analysis 1|
|3e||318||Installations and Measurement Laboratory||Capstone Design, Computer Lab|
|3e||320||Electronics Laboratory||Electronic Engineering Design Principles; Digital Electronic System Design; Microelectronics (2018)|
|3e||321||Electronics Laboratory||Antennas and Propagation; Analog Circuits Design|
|3e||322||Telecommunications Laboratory||Computer System Architecture; Communication systems; Embedded Microcontrollers, Introduction to Engineering|
|3e||333||ECE Innovation and Power Electronics Laboratory||Capstone Design (2017-2018);Power Electronics|
|3e||336||RF Laboratory||Electronic Engineering Design Principles, RF Circuit Design|
|3e||Computer Labs (Common)||6.522 Software engineering; Data Communications; 6.522 Electric Power Generation, Power System Operation and Control, Numerical Optimization Techniques and Computer Applications; 3.323 Power Systems Analysis; 3E.217 Pattern Recognition and Machine Learning; Signals and Systems|