fbe.txt

COMP2119. Introduction to data structures and algorithms (6 credits)
Arrays, linked lists, trees and graphs; stacks and queues; symbol tables; priority queues,
balanced trees; sorting algorithms; complexity analysis.
Prerequisite: ENGG1340 or COMP2113 or COMP2123
Assessment: 40% continuous assessment, 60% examination
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COMP2121. Discrete mathematics (6 credits)
This course provides students a solid background on discrete mathematics and structures
pertinent to computer science. Topics include logic; set theory; mathematical reasoning;
counting techniques; discrete probability; trees, graphs, and related algorithms; modeling
computation.
Mutually exclusive with: MATH3600
Assessment: 50% continuous assessment, 50% examination
COMP3230. Principles of operating systems (6 credits)
Operating system structures, process and thread, CPU scheduling, process synchronization,
deadlocks, memory management, file systems, I/O systems and device driver, mass-storage
structure and disk scheduling, case studies.
Prerequisites: ENGG1340 or COMP2113 or COMP2123; and COMP2120 or ELEC2441
Mutually exclusive with: ELEC3541
Assessment: 50% continuous assessment, 50% examination
ELEC2147. Electrical energy technology (6 credits)
This is an introductory course that provides students with a solid foundation of knowledge on
alternating current (A.C.) systems. The emphasis is on FOUR key topics of single phase A.C.
system - fundamental characteristics, phasor algebra, circuit analysis and magnetic components.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. identify the fundamental characteristics of A.C. systems
2. use circuit diagrams, phasor diagrams and mathematical equations to describe A.C.
systems and to analyse performances
3. describe the working principle, analyse and design inductors and transformers
4. use electrical measuring instruments, measurement of resistance, inductance,
capacitance, frequency, phase, current, voltage and power
Mutually exclusive with: MECH2406
Assessment: 20% practical work, 30% continuous assessment, 50% examination
ELEC2243. Introduction to electricity and Magnetism (6 credits)
This is the first course introducing basic mathematical and physical concepts of
electromagnetism. It aims at providing fundamental understanding about key electromagnetic
principles and scope of their applications. It covers the fundamentals of electrostatics,
magnetostatics, time-varying fields, dielectric materials, ferromagnetism, magnetic circuits and
wave propagation. The close relationship between electromagnetism and circuit models will be
introduced together with basic circuit elements, concepts, laws, and circuit theorems. The
extended applications of theories are introduced after each part of theoretical studies.
Specifically, the course covers the following topics in contemporary electromagnetics: 1)
Electrostatics: Coulomb's law, Gauss’ Law, electrostatic field, potential, capacitance and
energy storage, 2) Magnetostatics: Biot-Savart law, magnetic fields, Ampere's circuital law,
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force on a current-carrying conductor, Lorentz force. 3) Time-varying fields: Faraday’s Law,
Lenz's Law, self-inductance, mutual inductance and stored energy. 4) Dielectric material:
dipole, polarisation, permittivity and capacitors. 5) Ferromagnetism: magnetisation curve,
permeability, hysteresis and saturation. 6) Magnetic circuits: magnetomotive force, reluctance.
5) Wave propagations, material properties, and transmission lines (optional). It serves as the
entry class of engineering electromagnetism.
Assessment: 50% continuous assessment, 50% examination
ELEC2245. Control systems I (6 credits)
Control systems is fundamental to many engineering disciplines. In this course, a general
approach will be taken to study of control systems, so that the theory and methods are applicable
to other disciplines at the system level.
The course is aimed at providing a general understanding of the fundamental principles of
control systems. The following topics will be covered in the course: system modeling, transient
response, principles of feedback, root locus, frequency response methods, state-space models,
introduction to digital control.
At the end of the course, students should have gained an understanding of the concepts and
methodologies for the complete process of modeling, analysis and design of a feedback control
system
Mutually exclusive with: ELEC3245
Assessment: 15% practical work, 25% continuous assessment, 60% examination
ELEC2346. Electric circuit theory (6 credits)
This is an introductory course that provides students with a solid foundation of knowledge on
analog and digital electric circuits and concepts, to prepare them for subsequent circuit-related
courses. At the end of the course, the student will be able to identify, analyse, design and
optimize basic circuits based on fundamental circuit laws and theorems, using passive and
active circuit components as well as the op-amp.
The topics to be covered include basic circuit concepts and laws, methods of analysis, circuit
theorems, op-amps, first and second order circuits, diode and diode circuits and introductory
digital electronics.
Assessment: 10% practical work, 30% continuous assessment, 60% examination
ELEC2347. Fundamentals of optics (6 credits)
This is an introductory course that provides students with a solid foundation of knowledge on
optics, to prepare them for subsequent photonics-related courses. At the end of the course, the
student will be able to identify, analyse, design and optimize optical systems such as
microscopy based on fundamental laws and theorems.
The topics to be covered include ray optics, wave optics, beam optics, polarization optics,
guided-wave optics and quantum optics.
Assessment: 20% practical work, 20% continuous assessment, 60% examination
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ELEC2441. Computer organization and microprocessors (6 credits)
This course aims at providing fundamental knowledge on the principles of computer
organization and microprocessors, and serves as the first course to other more advanced
computer courses. In order to bring out the essential principles, a simple processor is used for
illustration and is studied in detail, and on top of it, more general systems are also introduced.
Specifically, the course covers the following topics: integer and floating point number
representations; basic computer building blocks; register transfers and phases of instruction
execution; micro-computer system organization - bus signals, timing, and address decoding;
study of a simple model microprocessor and the latest processor development: signals,
instruction set and addressing modes; binary arithmetic; subroutines; I/O programming;
interrupt I/O and DMA; memory and storage systems; exception handling; system software.
Mutually exclusive with: COMP2120
Assessment: 10% practical work, 30% continuous assessment, 60% examination
ELEC2543. Object-oriented programming and data structures (6 credits)
This course aims to provide a hands-on and in depth survey of object oriented programming
paradigm, and the basic concepts of data structures through the Java programming language. It
serves to provide a solid foundation of essential concepts on object oriented programming and
data structures that will be required in its sequels —including the Systems and Network
Programming, Distributed Computing Systems or Embedded Systems.
Specifically, the course covers the following topics: basics of the Java development
environment; Java applications and applets; Java syntaxes; control structures; methods in Java;
iteration; recursion; objects; classes; interfaces; inheritance; polymorphism; overloading;
overriding; wrapper classes; type conversions; strings; string manipulations in Java; Java
exceptions; try blocks; throwing and catching exceptions in Java; byte and character streams;
stream classes; file classes; file manipulation in Java; arrays; dynamic memory allocation;
dynamic data structures including the dynamically linked lists, stacks, queues, trees, graphs,
hash tables; sorting; searching; examples of Java applications.
Pre-requisite: ENGG1111 Computer programming and applications or ENGG1112 or
ENGG1330
Mutually exclusive with: COMP2119
Assessment: 60% continuous assessment, 40% examination
ELEC2544. Introduction to electronic commerce and financial technology (6 credits)
This course aims at introducing basic technical knowledge on electronic commerce and financial
technology. The course will introduce different e-commerce models: B2C and B2B model and overview
different enabling technologies e-Commerce and FinTech such as the location base technology, RFID,
GPS, e-payment, server-side and channel security, Near Field Communication, QR Code, augmented
reality and other latest technologies deploying in the industry. By the end of the course, the latest trend
and the way forward of e-commerce and Fintech in Hong Kong and overseas will be discussed.
Assessment: 30% continuous assessment, 70% examination
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ELEC2840. Engineering training (6 credits)
The aims of ELEC2840 Engineering Training are to provide practical trainings for students to
acquire essential practical skills related to Electrical and Electronic Engineering. There are 6
modules namely Electronic Practice, Practical Networking, CAD/CAE tools practice, Virtual
Instrumentation, Main Circuit Board and Microcontroller.
For the Computer Engineering (CE) and Electronic Engineering (ElecE), they are required to
take the following modules to fulfill the workshop training requirement.
1) Electronic practice (EP)
2) Practical Networking (NET)
3) CAD/CAE tools practice (CAD)
4) Virtual Instrumentation (VI)
For the Electrical Engineering (EE), they are required to take the following modules to fulfill
the workshop training requirement.
1) CAD/CAE tools practice (CAD)
2) Virtual Instrumentation (VI)
3) Microcontroller (MIC)
4) MCB installation (MCB)
The aims of each module are:
• CAD/CAE tools practice – To learn how to use CAD software application to design
circuit
• Electronics Practice – To learn how to produce a PCB circuit broad and soldering
technique
• Practical Networking – To learn how to design and configure a data network
• Microcontroller – To learn how to design and program a microcontroller
• Virtual instrumentation – To learn how to write codes and build hardware on virtual
instrumentation circuits
• Main Circuit Board – to learn how to design and install a main circuit board for electric
power distribution
Assessment: 30% practical work, 70% continuous assessment
ELEC2843. Multivariable calculus and elementary partial differential equations (6
credits)
This course aims to further develop the foundation of mathematics used in engineering
discipline.
Students will be introduced and explored to
1. The concepts of multivariable functions in multivariable spaces.
2. The concepts of differentiation and integration of multivariable functions
3. Basic extensions of multivariable calculus to vector analysis
4. The ideas of periodic functions and their Fourier series representations
5. The methods for solving elementary partial differential equations.
Through the development of solution methods, students will enrich their experience in critical
analysis and problem solving
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Pre-requisite: MATH1851 Calculus and ordinary differential equations and MATH1853 Linear
algebra, probability & statistics
Mutually exclusive: MECH2407 Multivariable calculus and partial differential equations
Assessment: 20% continuous assessment, 80% examination
ELEC2844. Probabilistic systems analysis (6 credits)
This course aims to introduce students to the modelling and analysis of real world phenomena
with the tools of probability and statistics. It involves both theoretical and computational
components, where probabilistic concepts are taught through many engineering examples
ranging from pattern analysis and image processing to forecasting and finance. Topics include
random variables, independence and conditional probability, mathematical expectation,
functions of random variables, classical estimation, Bayesian estimation, hypothesis testing,
and linear regression.
Pre-requisite: MATH1853 Linear algebra, probability & statistics
Mutually exclusive: STAT2601 Probability and statistics I
Assessment: 40% continuous assessment, 60% examination
ELEC2845. Applied optimization and applications (6 credits)
This course aims to further develop the foundation of mathematics used in electrical
engineering discipline.
Students will be introduced and explored to
1. The concepts of multivariable calculus and its application to optimization.
2. Different types of optimization problems and techniques for formulation.
3. Optimality conditions and basic solution methods in optimization.
4. System state equations and estimation/control via optimization.
5. The concept of Fourier series representations and frequency estimation by nonlinear
least squares method.
Through the development of solution methods, students will enrich their experience in critical
analysis and problem solving.
Pre-requisite: MATH1853 Linear algebra, probability & statistics
Mutually exclusive: COMP3407
Assessment: 35% continuous assessment, 65% examination
ELEC3141. Power transmission and distribution (6 credits)
The course aims at providing detailed understanding about power transmission and distribution
systems. The emphasis is on the mathematical models and equivalent circuits of power
transmission lines and the basic structure of distribution systems. The model for high voltage
transmission system is the basis for power system analysis and operation. The introduction of
distribution systems provides the basic understanding of how power is distributed to customers
and the technologies applied in power distribution.
Specifically, the course covers the following topics:
• Power transmission systems
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• Transmission line model
• Power distribution systems
• Distribution overhead lines and underground cables
• Various issues in distribution systems
Co-requisite: ELEC2147 Electrical energy technology
Mutually exclusive with: MECH2406
Assessment: 10% practical work, 20% continuous assessment, 70% examination
ELEC3142. Electrical energy conversion (6 credits)
This course aims at providing sound understanding of various electrical energy conversion
devices and systems. The emphasis is on four kinds of electrical energy conversion –
electromechanical motion, electric heating, electric lighting and electrochemistry.
Specifically, the course covers the following topics: electric machines including DC machines,
synchronous machines, induction machines and special machines; electric heating including
resistive heating, induction heating and dielectric heating; electric lighting including
incandescent lighting, discharge lighting and LED lighting; electrochemical sources including
batteries and ultracapacitors.
Pre-requisite: ELEC2147 Electrical energy technology
Assessment: 20% practical work, 20% continuous assessment, 60% examination
ELEC3143. Power electronics (6 credits)
Electrical energy is essential today. In order to effectively utilize electrical energy it must be
converted and processed to the right forms for different types of loads. A modern
microprocessor might need low voltage high current DC for its power supply whereas a
rotational machine might need high voltage high frequency AC for its operation. Power
electronics is a power conversion technology. It enables conversion of electrical energy to the
right form. It also enables the conversion process to be carried out with high efficiency. High
efficiency power conversion plays a crucial role in energy saving, reducing carbon emission
and global warming. Power electronics is based on the application of electronics technology to
control the electrical conversion process. It is a field that spreads across various disciplines such
as electrical, electronics and control.
The course starts with an introduction to various power semiconductors. Power semiconductors
are the basic components for power converters. Power converters for AC to DC, AC to AC, DC
to DC and DC to AC conversions are studied. Students are expected to learn the operation and
design of these converters. Students should also know where and how these converters are
applied in various electrical and electronic engineering systems.
Co-requisite: ELEC2147 Electrical Energy Technology, ELEC2346 Electric Circuit Theory
Assessment: 10% practical work, 20% continuous assessment, 70% examination
ELEC3241. Signals and linear systems (6 credits)
Signals and linear system theory is fundamental to all engineering discipline, especially in the
field of electrical, computer and medical engineering. This is a first course in signals and linear
systems for engineering students without any pre-requisite knowledge in signal theory or signal
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processing other than some knowledge in fundamental calculus and use of complex numbers.
The course uses simple real life examples of signals and systems to illustrate how signal theory
can be used in practical application, and will including an introduction to MATLAB as a tool
for signal analysis and system modelling.
This course aims to help students gain a firm understanding of the fundamentals of signal and
linear systems concepts and theory using adequate mathematical and computing techniques to
tackle simple signal processing problems. It serves as a pre-requisite course for many other
courses including Digital Signal Processing, Control and Instrumentation, Communication
Systems, and Digital Image Processing.
Specifically, the course covers the following topics: time-domain signal representation,
periodic and aperiodic signals; spectral representation of signals, Fourier series and Fourier
transform; system responses and linear system modelling; sampling, aliasing and analog-todigital conversion; z-transform and concepts of poles and zeros; convolution; FIR filters and
digital filtering; IIR filters and frequency response of digital filters; continuous-time systems
and Fourier transform properties; application examples of signal analysis and processing.
At the end of the course, students should have a clear understanding of the fundamentals of
signals and system theory to enable them to perform simple signal analysis and processing using
both analytical method as well as using computing tools, link the mathematical representation
of signals to some very simple real life signals and vice versa, and appreciate the applications
of linear systems theory in solving some simple real life problems. In addition, students should
be aware of the complexity of real life problems and the need to continue investigation in
practice after graduation.
Assessment: 40% continuous assessment, 60% examination
ELEC3243. Fundamentals of next-generation communications (6 credits)
The current mobile communication system is in its fifth generation (5G). The last decade has
witnessed the invention of many new wireless technologies, including massive MIMO,
OFDMA, SDMA, cross-layer design, network slicing, non-orthogonal access, interference
management, and cloud/fog networking. This course is aimed at explaining some fundamental
ideas and principles for 5G communications in a simple and intuitive way. The list of topics
discussed introduced in this course include
• Overview of 5G
• Baseband models
• Communication channels and coding
• Sharing of wireless medium
• Time and frequency in communication
• Space in communication
• Multi-antenna communication
• Layering and slicing
• Cells, clouds, and fogs
Through this course, students will gain useful insights and intuitions how practical
communication systems and networks are designed and operated.
Mutually exclusive: ELEC3242 Communications engineering
Assessment: 40% continuous assessment, 60% examination
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ELEC3244. Digital signal processing (6 credits)
This course aims to introduce students to the various applications of digital signal processing
(DSP) and focuses on the classical frequency domain theory and tools for the design and
realization of frequency selective digital filters, sampling-rate converters and adaptive filters.
It first starts with a brief general introduction to various DSP applications including digital
communications, multimedia signals processing, estimation theory, machine learning and
biomedical signal processing, etc. The classical frequency domain modelling of digital-time
signals and linear systems, and their relationship to continuous time counterparts will be
reviewed, where topics such as z-transform, stability, and spectrum will be reviewed. The
short-time Fourier transform (STFT) will be introduced as a tool for spectral analysis of signals.
The frequency domain specification of digital filters, various types of linear-phase finite
impulse response (FIR) filters and their optimal design techniques will be studied in details.
Realization techniques such as the cascade form for infinite impulse response (IIR) filters and
the application of fast Fourier transform (FFT) algorithm for realizing FIR filters will also be
discussed. Finally, the theory and design of sampling rate conversion and the concept of
adaptive filters will be briefly introduced.
Specifically, the course covers the following topics: DSP applications; review of linear system
theory and frequency domain representation; Spectral Analysis – STFT, time-frequency
resolution; structure of DSP systems and AD/DA converters – sampling theorem, filter
specification, four types of linear-phase filters; Design of FIR (linear-phase and low-delay) and
IIR filters – Windowing method, Park McClellan algorithm, second order cone programming,
bilinear transform and model order reduction; Realization of digital filters – cascade form,
overlap add/save methods using FFT; Discrete Fourier transform (DFT) - properties and fast
algorithms; Sampling conversion – upsampler, downsampler, specification, design and
realization methods; adaptive filters – Wiener-Hopf equation, least mean squares algorithm,
applications.
Pre-requisite: MATH1853 Linear algebra, probability & statistics and ELEC2346
Electric circuit theory
Assessment: 20% practical work, 20% continuous assessment, 60% examination
ELEC3248. Engineering electromagnetism and antenna designs (6 credits)
The objective of this course is to offer comprehensive understanding in electromagnetics and
its applications toward antenna engineering. It includes topics of Maxwell’s Equations,
property of matters, wave propagation, reflection and transmission, wave radiation,
transmission line basics, as well as important electromagnetic theorems. The course focuses
more on the dynamic electromagnetic field analysis. Based on these taught knowledge, antenna
theories and designs are introduced. The discussed topics will provide theoretical foundations
and application benchmarks for mobile communications, IoT, satellites, energy harvest, etc.
This course prepares students for understanding the physics and details of other courses and
technologies such as microwave engineering, optoelectronics, photonics, communication
systems, etc.
Pre-requisite: ELEC2242 Introduction to electromagnetic waves and fields or ELEC2243
Introduction to electricity and magnetism
Assessment: 50% continuous assessment; 50% examination
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ELEC3249. Pattern recognition and machine intelligence (6 credits)
This module aims at providing fundamental knowledge on the principles and techniques of
pattern recognition and machine learning.
Specifically, the module covers the following topics: Estimation theory and Bayes decision
theory; parametric and non-parametric methods; linear discriminant functions; design of
classifiers, unsupervised learning and clustering; feature extraction; neural networks and deep
learning; case studies.
After finish the course, students will be able to
1. Master the basic concept of pattern recognition and techniques for preprocessing and
feature extraction.
2. Master the application of statistical techniques to the estimation of probability
densities from samples.
3. Master the techniques of designing classifiers for pattern classification.
Pre-requisite: MATH1853 or MATH2101
Assessment: 50% continuous assessment; 50% examination
ELEC3255. Control systems II (6 credits)
This course provides the students with a good understanding of feedback control systems. The
fundamental concepts, mathematics and techniques for the analysis of control systems will be
given. Both continuous-time and discrete-time systems will be covered. The course will also
provide many examples of feedback control systems in different domains of engineering.
This course will cover many important topics in the field of line control systems from a statespace point of view. By the end of this course, students should possess a firm grounding in the
concepts and techniques of linear feedback control systems. The student should be able to
apply the acquired knowledge for the analysis of control systems, as well as to carry out the
design of feedback systems.
Pre-requisite: ELEC3245 Control and instrumentation or ELEC2245 Control systems I
Mutually exclusive with: ELEC4250
Assessment: 10% practical work, 30% continuous assessment, 60% examination
ELEC3342. Digital system design (6 credits)
This course aims at providing students the fundamental understanding of digital system
structures and system design techniques using discrete and programmable devices.
Digital system design as a synthesis process using building block components, and
characteristics of various block components are discussed. The analysis and synthesis of digital
system structure, especially those related to timing, pipeling, and debugging are discussed.
Typically, digital systems have lots of electronic modules interfaced with each other. Thus,
designers have to use various tools to design and analyze an entire digital system. In the course,
students are guided to acquire skills in using hardware and software development tools through
lectures, laboratory sessions and projects.
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Pre-requisite: ELEC2346 Electric circuit theory or ELEC2441 Computer organization and
microprocessors
Assessment: 70% continuous assessment; 30% examination
ELEC3347. Electronic materials and quantum physics (6 credits)
This course deals with the fundamental aspects of electronic materials, including solid-state
physics, material growth and processing, material properties and material properties at the
nano-scale: quantum physics.
It begins with coverage of crystal structures and a study crystallography, followed by the
physics and methods of crystal growth and ways of processing crystals for the formation of
functional devices. In the next section, the properties of materials will be studied in detail. The
optical properties of materials, including absorption and luminescence, will be covered. The
dielectric properties of insulating materials, including the different mechanisms of polarization,
will be taught. This is followed by understanding the electrical properties of semiconductors
in terms of carrier transport. Towards the end of the course, an introduction to quantum
mechanics will be given.
Assessment: 10% practical work, 20% continuous assessment, 70% examination
ELEC3349. Optical devices (6 credits)
The course aims at providing detailed understanding about active and passive optical devices
and optical systems. Students will learn optical components such as optical waveguides, fibers,
variety of light sources (e.g. laser and light emitting diodes), passive and active components,
wavelength division multiplexer, transmitters, receivers, photovoltaic devices and systems.
Students will gain the knowledge in the physics, operation principles and the applications of
optical components.
Pre-requisite: ELEC2346 Electric circuit theory or ELEC2347 Fundamentals of optics
Assessment: 20% continuous assessment, 80% examination
ELEC3350. Electronic circuits and devices I (6 credits)
The aim of this course is to provide students with a basic understanding of (i) the principles
underlying the operation of some common semiconductor devices, and (ii) some simple analog
and digital circuits based on these semiconductor devices.
Pre-requisite: ELEC2346 Electric circuit theory
Assessment: 10% practical work, 40% continuous assessment, 50% examination
ELEC3351. Electronic circuits and devices II (6 credits)
The aim of this course is to provide students with an in-depth understanding of (i) the principles
underlying the operation of some common semiconductor devices, and (ii) some simple analog
and digital circuits based on these semiconductor devices.
Pre-requisite: ELEC3350 Electronic circuits and devices I
Assessment: 10% practical work, 40% continuous assessment, 50% examination
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ELEC3441. Computer architecture (6 credits)
This course aims at providing detailed understanding about how modern high performance
microprocessors are designed and the rationales behind their different design principles. The
emphasis is on the relationship between the microarchitecture and the system software (e.g.,
operating system and compiler). Contemporary processors such as MIPS and Pentium are used
as practical cases to illustrate the different design principles. Pipelining microarchitecture and
some elementary concepts on instruction level parallelism (ILP) are discussed. Compiler
support and optimizations for exploiting the parallel processing capability provided by the
microarchitecture are discussed.
Specifically, the course covers the following topics in contemporary computer architecture
design: Design and performance issues of a computer system; RISC vs CISC; design of control
unit; design of ALU; instruction pipeline; memory system; input/output system; and parallel
processors.
Pre-requisite: ELEC2441 Computer organization and microprocessors
Mutually exclusive with: COMP3231 Computer architecture, ELEC2401
Assessment: 70% continuous assessment, 30% examination
ELEC3442. Embedded systems (6 credits)
This course introduces the design concepts of modern embedded systems, with an emphasis on
the integration of hardware and software. Topics include: hardware/software interface design
and implementation, the role of operating system in embedded systems, embedded application
development and the tradeoffs involving the use of hardware accelerators. A key component of
the course is to design and implement a real-world embedded system using field-programmable
gate array (FPGA) as a platform.
Upon completing this course, the student should be able to:
• Develop basic understanding of the role of embedded systems in contemporary
electronic systems.
• Evaluate embedded systems in terms of performance, power and energy consumptions.
• Understand the fundamentals of hardware-software codesign in embedded system.
• Develop practical techniques in constructing embedded systems with hardware and
software components addressing real-world challenges.
Pre-requisite: ELEC3342 Digital system design
Assessment: 55% practical work, 45% continuous assessment
ELEC3443. Computer networks (6 credits)
This course aims at providing detailed understanding of the basic principles of computer and
data communications, and the essential functions and protocols for co-ordinated exchange of
data through computer networks. It covers data communication networks and facilities;
network structures; protocols; local area networks; wide area networks; network trends; data
security.
Mutually exclusive with: COMP3234
Pre-requisite: (ENGG1340 or COMP2113 or ELEC2543) and (COMP2120 or ELEC2441)
Assessment: 50% continuous assessment, 50% examination
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ELEC3541. Software engineering & operating systems (6 credits)
This course aims at providing students the fundamental knowledge of software engineering
practices and system software for development and execution of computer software. The first
part of this course presents software engineering methodologies for the development of quality,
cost-effective, and maintainable software. Software is dealt with as an engineered product that
requires planning, analysis, design, implementation, testing and maintenance. The object is to
provide a concise presentation of each step in the engineering process. The second part of the
course aims at providing fundamental concepts and ideas of operating systems, and the
underlying principles of computer resource management by system software.
Specifically this course covers the following topics in Software Engineering and Operating
Systems: software engineering process; principles that guide practice; requirements and
modeling; software design concepts; software architectural and detail design methodologies;
software testing strategies; software maintenance; software quality; software documentation.
Software development systems: assembler, linker and loader, compiler; basic operating system
and process concepts; concurrent processes; processor management; primary and secondary
memory management; file and database systems.
Mutually exclusive with: COMP3230 & COMP3297
Assessment: 15% practical work, 85% examination
ELEC3542. Advanced programming and application development (6 credits)
This course aims at introducing the principles of software development in portable and wearable
devices. We will cover the issues and solutions when we want to develop a portable version of
a desktop software. We will also study the new opportunities offered by portable/wearable
devices, such as Internet of Things, location-aware services, push notification, and remote
control, etc.
Specifically, the course covers the following topics: features and limitations of
portable/wearable devices, event-driven programming paradigm, complexity and memory
usage analysis, concepts of Internet of Things, network programming basics, database basics,
cloud computing basics, security issues and concerns, application design and development, etc.
Co-requisite: ELEC2543 Object-oriented programming and data structures, or COMP2119 or
COMP2396
Assessment: 60% continuous assessment, 40% examination
ELEC3543. Advanced systems programming (6 credits)
This course aims to provide students with solid background on concepts and programming skills
for advanced systems programming, in particular, system architectures, programming
paradigms, advanced UNIX system facilities and programming, graphics processing unit
(GPU) programming, and working level software systems and development for cloud
computing and other sophisticated applications. It covers both advanced UNIX
multiprogramming software development, concurrency control, and GPU programming for
modern applications.
After finishing the course, students will be able to
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1. Master the basic concepts and programming skills for advanced systems
programming.
2. Master the working principles of advanced systems programming, GPU programming
and cloud computing.
3. Apply advanced UNIX system programming and/or GPU programming in modern
applications.
Pre-requisite: ELEC2543 Object-oriented programming and data structures or (COMP2119
Introduction to data structures and algorithms and COMP2396 Object-oriented programming
and Java)
Assessment: 50% continuous assessment, 50% examination
ELEC3544. Introduction to data analytics (6 credits)
Data analytics is about discovering and extracting meaningful knowledge from large amounts
of data, which is highly demanded in academia and industry. This course will lay out the
foundation of full-stack data analytics and focus more on the implementation aspects. It covers
the following basic topics: 1) introduction to Python for data analytics; 2) data collection,
presentation, and visualization; 3) mathematic tools for data analytics; 4) basic data analysis
tools upon statistical and machine learning approaches; 5) advanced deep learning tools for
analyzing high-dimensional data (e.g., images). We will focus on using the tools and
implementing the techniques, which will also help further studies in AI and machine learning.
Pre-requisite: COMP2119 or ELEC2543; and MATH1853 or MATH2014
Assessment: 30% continuous assessment, 70% examination
ELEC3641. Human computer interaction (6 credits)
This course aims at providing fundamental knowledge on the principles of Human Computer
Interaction (HCI): Design and Programming. It is targeted to provide core concepts in
designing, developing and evaluating HCI for other more advanced computer or HCI related
courses. In order to bring out the essential design principles and methodologies for HCI,
various development models and evaluation strategies for HCI are thoroughly discussed with
illustrative examples, and are studied in detail. On top of it, group projects on interesting topics
are also introduced for students to apply the valuable design principles and knowledge gained
in this course for designing, building and evaluating working prototypes of practical
applications throughout the semester.
Specifically, the course covers the following topics: human factors of interactive systems,
design principles of user-interface, user conceptual models and interface metaphors,
information and interactivity structures, interaction devices, presentation styles, information
visualization; general features and components of window programming toolkits, event
handling and layout management; strategies for effective human-computer interaction,
managing design process, evaluation of human-computer interaction.
Pre-requisite: ENGG1111 or ENGG1112 or ENGG1330
Assessment: 40% continuous assessment, 60% examination
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ELEC3643. Systems and network programming (6 credits)
This course aims to provide students with solid background on systems programming, in
particular, UNIX system programming, and working level network software development using
Java or Unix system facilities. It covers both classical UNIX multiprogramming software
development and object oriented system implementations for networked applications.
Specifically, the course covers the following topics: Unix system calls, file I/O, Unix system
data; process control, signals; daemon processes; threading approaches; concurrency control;
socket programming; I/O multiplexing; IPv4 and IPv6 interoperability; broadcasting;
multicasting; concurrent network servers; the 3-tier model; middlewares and their classification;
distributed objects; Java sockets; multicasting in Java; the Java distributed computing platform
including the Remote Method Invocation (RMI), the Java Servlets; the JavaServer Pages (JSP);
the Extensible Markup Language (XML); the Java peer-to-peer (P2P) technologies.
Pre-requisite: ELEC2543 Object-oriented programming and data structures or (COMP2119
Introduction to data structures and algorithms and COMP2396 Object-oriented programming
and Java)
Assessment: 40% continuous assessment, 60% examination
ELEC3644. Advanced mobile apps development (6 credits)
This course is designed for senior engineering students who have basic computer
programming knowledge to learn how to create innovative and advanced mobile apps
on iOS platform. Students will acquire essential Swift programing skills including
optionals, functions, closures, structures, classes, properties and protocols. The course
will also cover latest technologies for developing mobile apps to meet emerging needs
of the society including SwiftUI, List and Navigation, GitHub, JSON, Databases,
Camera and Photo, Location-based services, Machine Learning and Augment Reality.
On successful completion of the course, students should be able to
• Evaluate and compare the strength and weakness of contemporary mobile apps
• Master the essential concepts and skills in iOS development
• Demonstrate the working knowledge of design patterns and frameworks in iOS
development
• Design mobile apps to solve real life problem using latest technologies
Pre-requisite: ENGG1330 Computer Programming I or ENGG1111 Computer programming
and applications
Assessment: 100% continuous assessment
ELEC3841. Internship (0 credit)
Students are trained with hands-on practice under the supervision of either a company, a
research and development unit, or an experiential learning organizer. At the end of the training,
every student is required to submit a training report to the Department for assessment.
Mutually exclusive with: ELEC3840
Assessment: 100% continuous assessment
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ELEC3844. Engineering management and society (6 credits)
The aims of this course are to develop basic understanding of organization and management
skills, professional ethics and legal foundation for the engineering discipline. Topics on
engineering organization, project management and managerial skills, decision making
processes, contingency and crisis management, leadership, corporate culture and philanthropy
will be discussed. In order to provide a clear and right insight for engineering students to interact
and contribute to the society, topics related to professional conduct, social responsibility,
sustainability and safety issues, technology and environment, professional ethics, and
professional societies are included. For the legal foundation, topics such as contract, intellectual
property, tort, professional negligence and related law issues are discussed.
Assessment: 30% continuous assessment, 70% examination
ELEC3845. Economics, finance and marketing for engineers (6 credits)
The aims of this course are to develop basic understanding of economics, finance and marketing
for the engineering discipline. The syllabus includes macroeconomics, microeconomics, value
chain, financial management, cost and profit, shares and bonds, accounting concepts and
financial statements, cash flow, rate of return; risk management, investment portfolio, technical
analysis; marketing management, marketing mix, marketing media, marketing plan, and
business ethics.
Assessment: 30% continuous assessment, 70% examination
ELEC3846. Numerical methods and optimization (6 credits)
This course aims at introducing numerical methods and optimization used for the solution of
engineering problems. Specifically:
1. In the first part of the course, numerical algorithms to solve various mathematical
problems are provided. Development of algorithms, their mathematical analysis, and
an analysis of their errors and performance are discussed. The applications of numerical
methods in solving equations, differentiation and integration, ordinary differential
equations, and linear algebra, are illustrated.
2. In the second part of the course, essential concepts of optimization theory are
introduced, and fundamental classes of optimization problems are analyzed.
Theoretical results and practical algorithms for solving optimization problems are
introduced and explained. Applications in engineering fields and other areas are
illustrated.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. demonstrate knowledge and understanding of the basic concepts of numerical
methods and optimization;
2. apply theoretical results and practical algorithms for solving equations and
optimization problems.
Mutually exclusive with: COMP3407
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Assessment: 40% continuous assessment, 60% examination
ELEC3848. Integrated design project (6 credits)
This course aims at providing senior undergraduate students in small teams an opportunity to
apply and integrate their knowledge and skills in electrical and electronic engineering courses,
as well as project management, to implement a practical system that requires knowledge and
skills from different EEE disciplines (i.e., Computer Engineering, Electronic Engineering, and
Electrical Engineering). Typically, the system to be built has electrical components for
interfacing with the real world (e.g., a smart plug that can measure and regulate power
consumption as well as display measured data to user through an external user interface),
electronic components that integrated the external interfaces with the processing and
networking cores, and computing components that handle the data manipulations. Thus, by
design, each project team should consist of students from electrical engineering, electronic
engineering and computer engineering.
At the beginning of the course, students are guided to acquire skills in using hardware and
software development tools through introductory lectures and laboratory exercises. Students
then begin working on the project. Technical consultation sessions are conducted as
supplementary to help students throughout the process.
Assessment and grading will be made according to the quality of design product, demonstration
and documentations. Besides implementing the system to the required project specification,
students are encouraged to extend the project with their own inputs.
Assessment: 100% continuous assessment
ELEC4141. Electric railway systems (6 credits)
The aim of this course is to provide fundamental knowledge of electric power in railways, on
system and component levels. It elaborates on the power supply systems, rolling-stocks,
traction systems, supporting systems, automatic train operation, control, and protection systems.
Magnetic levitation systems are discussed. Topics on high-speed rail networks, railway
engineering management, health and safety are included.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. describe and understand the construction and functions of electrical installations and the
prerequisites that apply in the operation of installations;
2. explain different electrical installations that are parts of the operation of electric railway
traffic with respect to both function and the essential connections with the parts of the
installation;
3. understand the basic concepts of power supply systems for railways;
4. understand the rolling-stocks, traction systems and supporting systems of electric railway
systems;
5. understand the automatic train operation, control, and protection systems;
6. have a general grasp on the basic concepts of magnetic levitation systems;
7. demonstrate knowledge, understanding of high-speed rail networks and railway
engineering management, health and safety.
Pre-requisite: ELEC2147 Electrical energy technology
Assessment: 25% continuous assessment, 75% examination
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ELEC4142. Power system protection and switchgear (6 credits)
The aim of this course is to provide fundamental knowledge of electric power in power system
protection and switchgear. It elaborates on protective relays, protection transformer,
transmission line protection, rotating machine protection, substation protection. Principles of
over-voltages and electrical breakdown are discussed. Circuit breaker technologies,
switchgears and their protection schemes, and auto-recloser and sectionalizer are included.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. grasp and understand the basic principles and functions of protection relays and switchgears;
2. have a general grasp on the basic concepts of protection transformer;
3. understand the basic concepts of over-current protection, distance protection, pilot
protection of transmission lines;
4. understand the basic concepts of rotating machinery protection;
5. understand the basic concepts of substation protection;
6. have a general grasp on the basic concepts of electric arc and switching overvoltage;
7. understand the general principles of circuit breaker technologies;
8. have a general grasp on the switchgear technologies;
9. understand the basic concepts of auto-recloser and sectionalizer for power systems.
Pre-requisite: ELEC3141 Power transmission and distribution
Assessment: 10% practical work, 30% continuous assessment, 60% examination
ELEC4144. Electric vehicle technology (6 credits)
This course aims at providing sound understanding of various electric vehicle (EV)
technologies. The emphasis is on fiver key areas of EVs – System integration, propulsion
systems, energy sources, auxiliaries and impacts.
Specifically, the course covers the following topics: system integration including battery EVs,
hybrid EVs and fuel cell EVs; propulsion systems including single-motor and multiple-motor
drives, geared and gearless in-wheel motors and hybrid powertrains; energy sources including
batteries, fuel cells, ultracapacitors and ultrahigh-speed flywheels; auxiliaries including battery
chargers and indicators, temperature control units, power steering units, auxiliary power
supplies and regenerative braking units; impacts including power system, environment and
economy.
Pre-requisite: ELEC3142 Electrical energy conversion
Assessment: 40% continuous assessment, 60% examination
ELEC4145. Building services- electrical services (6 credits)
The aim of this course is to provide knowledge on electrical principles applied in building
services design and installation, on system and component levels. It elaborates on those
electrical subsystems within the Heating, Ventilation and Air-conditioning System, Plumbing
& Drainage System, Fire & Security Services System. Various building services systems are
discussed covering engineering fundamentals, system components, electrical design and
statutory requirements, system integration as well as practical familiarization of systems.
At the end of this course, students who fulfill the requirements of this course will be able to:
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1. describe and understand the construction and functions of building services installation
for building to operate; and their forming part of a building and its connection between
each other;
2. understand the basic electric drives and control for motors in building systems, plumbing
and drainage systems;
3. understand the security systems for buildings, including electronic alarm and detection
systems, and latest surveillance systems;
4. understand the principles of variable speed drives, highly efficient motors and its modern
control, as well as its applications in HVAC (heating, ventilation and air-conditioning)
systems;
5. understand the issues and strategies in power quality, its impacts from and to other
building services systems, in terms of performance and energy efficiency, relating to
HVAC systems.
Pre-requisite: ELEC2346 Electric circuit theory
Assessment: 20% continuous assessment, 80% examination
ELEC4146. Building services- electrical installations (6 credits)
To develop classmates’ potential in selecting electrical equipment, designing electrical
installation, and making them professional in achieving optimal benefits in building services
without compromising safety.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. describe and understand the electrical installation as a system; and the major components
that build up the installations;
2. be aware of the potential hazards of electrical installations, yet be able to prevent those
hazards;
3. select proper equipment and protective devices to facilitate expected functions of the
electrical installations;
4. be competent in electrical safety and codes of practice;
Pre-requisite: ELEC2147 Electrical energy technology OR ELEC2346 Electric circuit theory
Assessment: 30% continuous assessment, 70% examination
ELEC4147. Power system analysis and control (6 credits)
The aim of this course is to provide fundamental knowledge of electric power in power system
analysis and control. It elaborates on the power flow analysis, fault analysis, economic dispatch
algorithms, and small/large disturbance stability. Power system component models and network
matrices are included.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. describe and understand the structure and functions of electrical power systems;
2. understand electrical power network modeling and algorithms for network matrices
construction;
3. understand the basic concepts of steady-state analysis for power systems and some
algorithms for power flow analysis;
4. have a general grasp on the basic concepts of power system operation and understand some
algorithms for power system economic dispatch;
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5. understand the basic concepts and methods of fault analysis for power systems;
6. understand the basic concepts and methods of stability analysis for power systems.
Pre-requisite: ELEC3141 Power transmission and distribution
Assessment: 10% practical work, 20% continuous assessment, 70% examination
ELEC4148. Smart grid and renewable energy systems (6 credits)
The aim of this course is to introduce the disciplinary knowledge of smart grid. It is an in-depth
study of the ways in which the renewable energy sources, microgrids, and information and
communication technologies are being employed to modernize the electrical energy
infrastructure. It elaborates on definitions and functions of smart grids, types of renewable
energy resources, wind power and photovoltaic systems, micro-grids and distribution systems.
Wide-area monitoring systems are discussed. Information and communication technologies for
smart grids are introduced.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. understand definitions, requirements and basic applications of smart grid;
2. have a general concept on the types of renewable energy resources;
3. grasp the basic principles of wind power and photovoltaic systems;
4. understand the basic architectures and operation strategies of micro-grids;
5. grasp the steady-state analysis methods of a distribution system based micro-grid;
6. understand the basic concepts of information and communication technologies applied in
smart grids.
Pre-requisite: ELEC3141 Power transmission and distribution
Assessment: 20% continuous assessment, 80% examination
ELEC4149. Basic Lighting Engineering (6 credits)
The aim of this course is to provide basic knowledge on electrical principles applied in lighting
systems design and installation, on system and component levels. It elaborates on the lighting
physics, operating principles, mathematical models, and design criteria in Lighting Installation.
It is suitable to potential lighting specialists as well as to general building services engineers.
Various lighting systems are discussed covering engineering fundamentals, system components,
electrical design and statutory requirements, system integration as well as practical
familiarization of systems.
At the end of this course, students who fulfill the requirements of this course will be able to:
1. Describe and understand the construction and functions of building services installation for
building to operate; and their forming part of a building.
2. Understand the physics and mathematics behind lighting engineering, and carry out
fundamental calculations related to “how much light”.
3. Logically choose different types of lighting schemes for different applications.
4. Gain a solid fundamental for carrying out lighting design in future.
5. Acquire lighting design skills.
6. Understand the issues of light pollution, and design for proper outdoor lighting systems.
Pre-requisite: ELEC2346 Electric circuit theory
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Assessment: 20% continuous assessment, 80% examination
ELEC4151. Hybrid electric propulsion technology (6 credits)
This course aims at providing sound understanding of hybrid electric propulsion systems. The
emphasis is on five key areas of hybrid electric propulsion technologies of electric vehicles
(EVs) – motor drive systems, hybrid electric propulsion systems, hybrid electric drive train,
regenerative braking and challenges.
Specifically, the course covers the following topics: 1) Motor drive systems including DC
motor drives, induction motor drives, switched reluctance motor drives, brushless DC motor
drives and permanent magnet synchronous motor drives; 2) Hybrid electric propulsion systems
including multiple-energy management systems, power converters, hybrid propulsion systems
and propulsion control modes; 3) Hybrid electric drive train systems including series (electrical
coupling)/parallel (mechanical coupling) hybrid electric drive train, series-parallel (torque and
speed coupling) hybrid electric drive train, mild hybrid electric drive train, and design of hybrid
EVs; 4) Regenerative braking including braking energy, braking power and braking systems;
5) Challenges in hybrid EVs, hybrid electric propulsion and hybrid electric drive train
Assessment: 50% continuous assessment, 50% examination
ELEC4241. Communication systems (6 credits)
This course aims at providing detailed understanding of the basic principles of analogue and
digital communication systems in the presence of noise with focus on basic issues relating to
system design. It covers spectral analysis; random signal theory; information theory; noise in
analogue systems; digital transmission through AWGN channels; digital carrier-modulation
schemes; DM and PCM, error control coding.
Pre-requisite: ELEC3242 Communications engineering or ELEC3243 Introduction to nextgeneration communications
Assessment: 10% practical work, 90% examination
ELEC4244. Multimedia signals and applications (6 credits)
This course provides an introduction to the basic concept of multimedia applications with
particular emphasis on media compression standards/formats for speech, audio, image and
videos. Specifically, the course will cover basic concept and terminology in multimedia
applications. Furthermore, the course will also discuss in detail about digital representations of
important media such as speech, audio, images and videos. Finally, the course will include indepth coverage of digital media formats, compression methods and standards.
The course is designed to achieve the following:
1. Enable the students to acquire fundamental knowledge/terminologies on essential
multimedia components including image, video, audio and speech and their compression
techniques/standards for supporting multimedia applications. It will also allow them to keep
abreast with more recent development in multimedia compression standards and system
development.
2. Enable the students to understand the following basic technical concept on multimedia:
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a) multimedia, example systems, and common media components such as hypertext,
image, videos, and audio,
b) some popular authoring tools,
c) common color systems used in images and videos and simple image/graphic data type
and file formats,
d) videos, digital videos and HDTV,
e) digital audios such as sampling rate, and quantization techniques (e.g. companding, and
prediction)
f) lossless compression principle and algorithms such as Huffman codes, dictionarybased codes (e.g. LZW), JPEG lossless image compression, and runlength code.
g) the principle/merits/demerits of image compression standards such as JPEG Baseline
and related algorithms,
h) the principle of video compression using motion estimation/hybrid DCT/DPCM codec
and simple motion estimation algorithm such as the logarithmic search,
i) the principle of MPEG-1/2 video compression algorithm,
j) speech production/speech analysis techniques using STFT and all-pole
modeling/Principle of Multiband Excitation codec and Analysis/Synthesis codec and
example coding standards.
3. Enable the students to appreciate the design and implementation issues in a selected
multimedia application through the completion of an individual miniproject. The project
should have sufficient coverage for the students to apply and integrate the knowledge they have
learnt from lectures to develop practical multimedia applications and learn to use relevant state
of the art engineering tools.
4. Enable the student to analyze the arithmetic complexity requirements, relative merits, design
considerations and other relevant parameters etc for these essential multimedia components
through the tutorial questions and assessment by examination.
Pre-requisite: ELEC3241 Signal and linear systems
Assessment: 30% continuous assessment, 70% examination
ELEC4245. Digital image processing (6 credits)
This course aims to help students gain a firm understanding in digital image processing
and master its methods and techniques. The course in general begins with the basics in
2D signals and systems, visual perception, image sensing and acquisition. It then
proceeds to study various problems including image enhancement, image
reconstruction and restoration, image segmentation, and image analysis and recognition.
The course concludes with modern image processing applications using convolutional
neural networks and deep learning such as image classification, face detection, and
biomedical image analysis.
Specifically, it covers the following topics:
Image acquisition and image representations: imaging systems and examples of images
such as natural image, biomedical images and depth images, and color image
processing.
Image enhancement: intensity transformations, histogram processing, image filtering in
spatial and frequency domains with case studies.
Image restoration: deconvolution, wiener filter and image quality measure.
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Image analysis (feature extraction): image features – corner detection, Sobel and Canny
edge detectors, Line detection, Scale-invariant feature transforms with case studies.
Image segmentation: mean-shift and graph-cut algorithms.
Image processing and recognition with deep learning: convolutional neural networks,
feedforward and backpropagation, example architectures for image processing and
recognition: AlexNet, VGG, ResNet and UNet with applications to image segmentation
and object detection, etc.
Pre-requisite: MATH1853 or MATH2101
Assessment: 50% continuous assessment, 50% examination
ELEC4248. Photonic systems technologies (6 credits)
The course aims at providing detailed understanding about the key technologies of photonic
systems, especially in the application for communications. Students will learn optical
components such as fibers, transmitters and receivers, passive and active components,
wavelength-division multiplexer, optical amplifiers. Students will gain the knowledge in the
operation principles and the applications of optical components and systems. With the
knowledge, the requirement and knowhow to build an optical communication system from
optical components are discussed. Some experiments will be conducted for gaining the practical
knowledge.
Pre-requisite: ELEC2346 Electric circuit theory or ELEC3349 Optical devices
Assessment: 30% continuous assessment, 10% practical work, 60% examination
ELEC4251. Microscopy (6 credits)
This is an advanced course that provides students with an in-depth knowledge of various optical
and electronic microscopy technologies. The course will cover the essential theories of optical
image formation, image analysis, experimental designs of microscopes. Discussion of their
practical applications in biomedicine and basic science research will be covered. Selected
technologies include phase-contrast microscopy, fluorescence microscopy, super-resolution
(far-field) microscopy, scanning electron microscopy (SEM), transmission electron microscopy
(TEM), scanning probe microscopy, e.g. atomic force microscopy (AFM).
Assessment: 20% practical work, 40% continuous assessment, 40% examination
ELEC4252. Robotic control and vision (6 credits)
The development of robotics has evolved from early programmable industrial arms or
manipulators (consisting of a driven mechanical structure) to a diverse range of objects that
may generally be referred to as robots. As a result, robotics has become a highly
interdisciplinary subject involving different kinds of technologies.
The first part of the course is aimed at providing a general understanding of the fundamental
principles of robot manipulators covering robot kinematics, robot dynamics and robot control.
The second part of the course will venture into selected topics in robotics (such as robot vision,
AI in robotics etc.) and then consider robot applications to different areas (such as humanoid
robot, medical and surgical robots, etc.).
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At the end of the course, students should have gained an understanding in the principles and
mathematical techniques that underlie the traditional manipulator as a basic building block of
different kinds of robots, and also an appreciation of how other technologies can be applied to
enhance the capabilities and scope of applications of robots.
Pre-requisite: ELEC3241 Signals and linear systems
Assessment: 20% continuous assessment, 80% examination
ELEC4253. Wireless communications (6 credits)
This course is an introduction to cellular radio communications systems taught at a level
appropriate for third-year undergraduates in electrical and electronic engineering. It is aimed at
providing a general understanding of the basic theory and design of wireless communications.
The following topics will be covered in the course: cellular-systems concepts, advanced digital
modulations, digital cellular technologies, code-division-multiple access, GSM system, IS-95
CDMA system, 3G mobile systems, TD-SCDMA system, and safety issues on non-ionizing
radiation from wireless systems.
At the end of the course, students should have gained an understanding of the concepts of
cellular radio communications systems and analyses the advantages and disadvantages of
different mobile systems.
Pre-requisite: ELEC3242 Communications engineering or ELEC3243 Introduction to nextgeneration communications
Assessment: 30% practical work, 70% examination
ELEC4254. Microwave and RF engineering (6 credits)
This course introduces fundamental concepts and design technologies for real world
Microwave and RF circuits for modern communication systems. It aims to establish necessary
design methodologies and essential skills for engineering development in practical designs,
from circuit to system levels. Starting from Electromagnetic fundamentals, this course will
introduce the transmission line theory, waveguides, network parameters, impedance matching
methods, filter designs, active circuit designs, and wireless communication systems. Many
concepts are extendable to Acoustics and Optics. At the end of the class, the students are
expected to understand modern wireless transceiver designs in RF, microwave, and millimetre
wave regimes with great details that could produce realistic prototypes. Also students shall
have much more complete understanding about how electronic circuits and system works based
on first principles.
Pre-requisite: ELEC3248 Engineering electromagnetism and antenna design
Assessment: 30% practical work, 30% continuous assessment, 40% examination
ELEC4256. Wireless networking in the era of machine learning (6 credits)
Artificial intelligence (AI) lies at the heart of next-generation wireless networks (e.g., 5G/6G).
On the one hand, machine learning enables the design and optimization of increasingly dynamic
and heterogeneous wireless networks. On the other hand, wireless networks are envisioned to
serve as an integrated communication and computing platform to empower pervasive AI
services at the edge.
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To keep pace with this significant development trend, this course aims to provide a systematic
and comprehensive guide to machine learning, wireless networks, and their vital interplay. It
introduces students to the fundamentals of machine learning and wireless networks, followed
by advanced machine learning algorithms for wireless networks and the design of wireless
networks to support machine learning services.
Upon completing this course, students will be able to
1) Understand the fundamentals of machine learning
2) Gain in-depth knowledge of next-generation wireless networks
3) Appreciate the design principles of machine learning for wireless networks and
wireless networks for machine learning
4) Master problem-solving skills in engineering optimization problems
Pre-requisite: ELEC3243 or ELEC3443
Assessment: 40% continuous assessment, 60% examination
ELEC4342. Embedded machine learning: A software-hardware design flow (6 credits)
Machine learning (ML) and artificial intelligence (AI) have revolutionized various engineering
fields and continued to evolve and penetrate into our daily life. This course rides on the latest
developments in ML (software, algorithms, etc.) and microelectronics (microcontroller, FPGA,
etc.) to introduce a software-hardware embedded AI design flow. The course contains
dynamically changing components across various AI applications and their system integration,
with an emphasis on edge AI implementation.
Holistically, this course aims to present a broad overview of how machine learning works, how
to train neural networks, and how to deploy these networks onto microcontrollers and/or FPGAs,
through embedded machine learning and/or the TinyML framework. No prior machine learning
knowledge is assumed for this course. Familiarity with Arduino/microcontrollers/Vivado will
be a plus though we will cover them from scratch. Group or individual project presentation and
demonstration are expected toward the end of the course.
Upon completing this course, students will be able to
1) Understand the fundamentals of machine learning and AI programming language(s).
2) Gain in-depth knowledge of a machine learning workflow, such as model training,
inference, and software and/or hardware deployment.
3) Familiarize with running machine learning algorithms on resource-constrained devices,
e.g., FPGAs.
4) Master problem-solving skills in engineering optimization problems.
Assessment: 100% continuous assessment
ELEC4343. Design of digital integrated circuits (6 credits)
The aim of this course is to design logic and memory circuits on silicon micro-chips
fabricated by various IC technologies.
Specifically, the course covers the following topics: MOS processing : polysilicon gate,
LOCOS isolation; MOSFET, as a switch in an inverter; NMOS logic : R-load, E-load, D-load,
and their comparisons; Layout design of NMOS circuits; Design rules, extraction of device
parameters, isolation concerns; Design of memory circuits : ROM, EPROM, EEPROM, DRAM,
SRAM; CMOS processing : different types of well, threshold control; Problems in CMOS
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circuits : field inversion, latchup, SOI; CMOS circuits : analysis, layout design; Effects of
scaling on the performance of MOS circuits; Bipolar junction transistor, BiCMOS circuits.
Pre-requisite: ELEC3346 Electronic circuits or ELEC3350 Electronic circuits and devices I
Assessment: 50% continuous assessment, 50% examination
ELEC4344. Advanced electronic circuits (6 credits)
The aim of this course is to provide students with more advanced knowledge on analogue
electronic circuits like amplifiers, filters, diode circuits, oscillators, AD converters and DA
converters.
Specifically, the course covers the following topics: s-domain analysis; low-frequency and high
frequency response of single-stage BJT and MOSFET amplifiers, cascode configurations,
cascade configurations; The BJT differential pair; small-signal operation: input differential
resistance, differential voltage gain common-mode input resistance and gain, biasing in BJT
integrated circuits :current source circuits, cascode configurations, MOS differential amplifiers,
BiCMOS amplifiers, multistage amplifiers; Class A output stage; Class B output stage; Class
AB output stage; biasing techniques of the class AB circuit; Basic feedback concepts; feedback
amplifier configurations: shunt-shunt, shunt-series, series-shunt, series-series; loop-gain;
stability problem; Op-amp realization of Butterworth and Chebyshev filter types; switchedcapacitor filters; tuned amplifiers; Series voltage regulators; overcurrent protections; shunt
voltage regulators; Sinusoidal oscillators; op amp-RC oscillator circuits; the Wien-Bridge
oscillator, the phase-shift oscillator, the quadrature oscillator, the active-filter tuned oscillator;
LC oscillators: Colpitts and Hartley oscillators; crystal oscillators; bistable and astable
multivibrators; the 555 as an oscillator and as a monostable circuit; D/A converters: inverted
ladder converter, current switching converter; A/D converters: the voltage-to-frequency
converter, ramp-comparison technique, the counter-binary ramp converter, the dual ramp
integrator converter, successive-comparison method.
Pre-requisite: ELEC3346 Electronic circuits or ELEC3350 Electronic circuits and devices I
Assessment: 20% practical work, 20% continuous assessment, 60% examination
ELEC4442. Advanced networking technologies (6 credits)
This course takes a systematic approach to study the various components that form the
infrastructure of the next generation Internet. Topics include optical switching technologies,
survivable optical networks, IEEE 802.11, wireless mesh networks, mobile ad hoc networks,
wireless sensor networks, high performance switches and routers, advanced topics on
congestion and flow control, traffic management.
- To provide a comprehensive coverage of key technologies in optical and wireless
networking;
- To study fundamental problems and approach in providing QoS in the next generation
Internet.
Pre-requisite: ELEC3443 Computer networks or COMP3234 Computer and communication
networks
Assessment: 40% continuous assessment, 60% examination
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ELEC4542. Introduction to deep learning for computer vision (6 credits)
Computer vision deals with how computers can gain high-level understanding from digital
images or videos. Recent developments in deep learning approaches have greatly advanced the
development of computer vision, leading to wide applications in search, image understanding,
smartphones, social media, self-driving cars, etc. This course will introduce the basic theories,
model architectures, algorithms, and implementation of deep learning for computer vision.
Students will also obtain hands-on experience on implementing and training deep neural
networks for computer vision tasks. The course will cover the following topics: (1) neural
network optimization algorithms; (2) backbone network architectures for computer vision,
including convolutional neural networks and transformers; (3) network structure design for
visual recognition tasks (image classification, object detection, image segmentation) and visual
content generation tasks; (4) implementation and training of neural networks for computer
vision tasks; (5) advanced topics in computer vision and deep learning.
Mutually exclusive with: COMP3340
Assessment: 50% continuous assessment, 50% examination
ELEC4543. Fuzzy systems and neural networks (6 credits)
This course provides a general introduction to fuzzy logic and neural network. The fundamental
concepts and techniques in the general field of fuzzy systems and neural networks will be given.
The course will also provide examples on the application of fuzzy logic and neural network to
a variety of engineering problems.
This course will cover two important topics in the field of Artificial Intelligence. By the end
of this course, student should possess a firm grounding in the concepts and techniques of fuzzy
logic and neural network. The student should be able to apply the acquired knowledge to the
development of intelligent systems or to the exploration of research problems.
Assessment: 30% continuous assessment, 70% examination
ELEC4544. Artificial intelligence and deep learning (6 credits)
This course aims at providing students with a basic understanding on deep learning
technology. The topics to be covered are neural network, backpropagation, deep auto-encoder,
Restricted Boltzmann Machines (RBM), Convolutional Neural Network (CNN), Multi-Layer
Perceptron (MLP), strategies for training deep architectures, handling overfitting, crossvalidation, meta-heuristic searching for parameter tuning. This is followed by hands-on
implementation of deep learning algorithms using Python, with applications ranging from
image classification, speech processing, and financial data analysis.
After finish the course, students will be able to
1. Master the basic concept of deep learning in artificial intelligence.
2. Master the Python programing language for implementing deep learning model.
3. Apply deep learning in novel applications.
Pre-requisite: ELEC3241 Signals and linear systems
Assessment: 55% continuous assessment, 45% practical work
45
ELEC4545. Time series analysis with financial applications (6 credits)
This module aims at providing fundamental knowledge on the principles and techniques of time
series analysis with applications to finance.
Specifically, the module covers the following topics:
Linear time series and applications: stochastic processes, stationarity, correlation,
autocorrelation, AR, MA, ARMA models, forecasting, engineering applications;
Financial Time Series and Their Characteristics;
Conditional Heteroscedastic Models: The GARCH models, Stochastic Volatility Model, The
Long-Memory Stochastic Volatility Model;
Nonlinear models: Functional Coefficient AR Model, Nonlinear Additive AR Model,
Nonlinear State-Space Model, Neural Network Models;
High-Frequency Data Analysis: Nonsynchronous Trading, Bid–Ask Spread, Empirical
Characteristics of Transactions Data, Models for Price Changes; Duration Models, Bivariate
Models for Price Change and Duration; Multivariate Time Series Analysis: Vector AR and
ARMA Models;
Principal Component Analysis and Factor Models: Macroeconometric Factor Models and other
engineering applications;
Continuous-Time Models: The Wiener Process, Generalized Wiener Processes, Ito Processes,
Ito’s Lemma, Distributions of Stock Prices and Log Returns;
Pricing and Risk: Derivation of Black–Scholes Differential Equation, Black–Scholes Pricing
Formulas, Concept of Value at Risk and Risk Metrics.
After finish the course, students will be able to
1. Master the basic concept and common models of time series analysis.
2. Master the applications of time series analysis and common estimation techniques.
3. Appreciate the applications of time series analysis to financial time series and related
concepts.
Pre-requisite: ELEC3241 Signals and linear systems
Assessment: 40% continuous assessment, 60% examination
ELEC4546. Investment and trading for engineering students (6 credits)
This course is designed for engineering students who wish to start a career in the financial
industry. The depth of this course will be at senior undergraduate students with good technical
skills are welcome to take. This course helps the students to integrate the technical skills, for
example, programming and statistical analysis, they have learned in other engineering courses
and to develop the basic knowledge, skill sets, and vocabulary that can communicate with the
practitioners in the financial industry. The most important is that students are expected to learn
how to develop market view by analyzing the driving factors of the financial markets to forecast
the movement of financial assets like equities and foreign exchange, which is extremely
important when interviewing for a job in the financial industry.
Then, students are expected to build up the basic knowledge on various financial instruments,
such as, options and futures, as well as quantitative models for investment management and
development of trading strategies. The financial products or instruments include: equities,
46
bonds, options, futures and other derivatives. Also, we will discuss various investment/trading
strategies, such as, VWAP, TWAP, Bollinger Band, RSI, etc.
Pre-requisite: ELEC3241 Signals and linear systems
Assessment: 50% continuous assessment, 50% examination
ELEC4547. Emerging technology for VR/AR (6 credits)
There are many emerging yet interesting parts assisting how human beings visualize and
interact with the digital world, including display systems, optics & electronics, IMUs and
sensors, real-time rendering, tracking, haptics, multimodal human perception and depth
perception, stereo rendering, presence. This course’s emphasis on VR/AR/MR technology.
Course Goals: This is a technical class. Students will learn about all hardware (optics,
electronics, display, microcontroller, ...) and software (JavaScript, WebGL, Python) aspects of
Virtual and Augmented Reality (VR/AR). The goal for this class is to learn all of these aspects
in a hands-on manner. Each assignment is a small piece of a bigger project. The goal for each
student or small team of students is to build a fully functional head mounted display, including
optics, display, IMU, rendering, lens distortion shader, model loader etc., from off-the-shelf
parts. The HMD we will build is inspired by the Oculus DK1. We will NOT learn game
development, but study the fundamental building blocks of VR/AR systems and implement all
of them.
Assessment: 50% continuous assessment, 50% examination
ELEC4640. Distributed computing systems (6 credits)
This course aims at providing detailed understanding about the concept and design of
distributed computing systems. The emphasis is on distributed protocol design and analysis.
Various existing distributed systems, such as the Internet, are discussed. Network programming
is introduced for students to develop their own distributed applications.
Pre-requisite: (ELEC3541 Software engineering and operating systems or COMP3230
Principles of operating systems) and (ELEC3443 Computer networks or COMP3234 Computer
and communication networks)
Assessment: 40% continuous assessment, 60% examination
ELEC4641. Computer network security (6 credits)
This course focuses on state-of-the-art computer network security technologies, which are
crucial to the success of any electronic commerce systems. The course covers fundamental
techniques of cryptography, security threats and their possible countermeasures, secure
protocols, and other network security schemes (authentication, key management, firewalls,
intrusion detection, etc.).
Pre-requisite: ELEC3443 Computer networks or COMP3234 Computer and communication
networks
Mutually exclusive with COMP3355
Assessment: 40% continuous assessment, 60% examination
_____________________________________________________________________
47
ELEC4642. VLSI design principles (6 credits)
To give a detailed treatment on the principles and methods for designing large-scale digital
integrated circuits.
The course content ranges from low level fabrics like MOSFET (metal-oxide-semiconductor
field-effect transistor) basics, logic gate families, layout and fabrication practices, to higher
level system knowledge like timing, memory, design optimization and tests; and eventually
extends into basic analog circuit blocks like CMOS (complementary metal-oxidesemiconductor) transistor amplifiers and opamps etc.
The course also includes a Verilog design project that covers the typical VLSI design flow
using the most popular electronic design automation (EDA) tools.
Assessment: 40% continuous assessment, 60% examination
_____________________________________________________________________
ELEC4745. Queueing theory (6 credits)
The objective of the course is to introduce the basic principles of queueing theory. The concepts
of random processes, birth-death queueing systems, Markovian queues in equilibrium, and
simulation techniques are discussed. Applications of these concepts are also illustrated.
At the end of this course, students will be able to:
1. Gain understanding of concepts in queueing theory;
2. Illustrate the applications of concepts to engineering;
3. Explore the foundations of analytical and critical thinking, academic research, and
preparing students some mathematical techniques for conducting academic research;
4. Acquire learning strategies that will enhance their learning experience;
5. Explore some practical examples as a showcase over the course of the Engineering
degree.
Pre-requisite: ELEC3847 Probability and statistics in engineering or ELEC2844 Probabilistic
systems analysis
Assessment: 30% continuous assessment, 70% examination
ELEC4848. Senior design project (12 credits)
This course aims at providing the very fundamental training in conducting an individual design
project prior to leaving the University.
The essence of the project is for student to re-enforce and consolidate all the learned engineering
skill and theory in the school into a real-life practical technical project. The aims of the project
are not limited to technical achievement, but also reflected on self-awareness, self-management
and probing the limitation of oneself.
Depending on each project offered by teaching staff, students are usually required to
individually carry out the Project Requirement and Design, Implementation and Evaluation,
Report and Presentation on the selected project. Students are encouraged to explore and lean
his/her own direction of the Project over the year during which project supervisor shall provide
assistance and aids along each Project phase with the students.
Students are required to have meeting and discussion with his/her supervisors on a regular basis,
usually every week or every fortnight. Mid-term Review will be held with both the supervisors
48
and the 2nd examiner in order review the student progress. The final assessment will be based
Project Report, Presentation and Demonstration.
Assessment: 100% continuous assessment
List of Courses by Subject Groups
Note:
Each course shall be classified as either introductory level course or advanced level course, and
be assigned a Level – One, Two, Three or Four, in which Level One and Level Two courses
are introductory courses whereas advanced courses include Level Three and Four courses.
Courses with similar contents are flagged as "mutually exclusive". For each set of mutually
exclusive courses, students are not allowed to take more than one course. Subject to approval,
some MSc courses may also be taken as Disciplinary Elective Courses in their respective
subject groups. Each MSc course is equivalent to a 6-credit course by undertaking additional
workload than an MSc student in the course concerned.
Group A: Electrical Engineering
Level Code Course Title Credit Prerequisite Co-requisite
2 ELEC2147 Electrical energy
technology (core: EE)
(mutually exclusive with
MECH2406)
6 - -
3 ELEC3141 Power transmission and
distribution (core: EE)
6 - ELEC2147
3 ELEC3142 Electrical energy
conversion (core: EE)
6 ELEC2147 -
3 ELEC3143 Power electronics (core:
EE)
6 - ELEC2147,
ELEC2346
4 ELEC4141 Electric railway systems 6 ELEC2147 -
4 ELEC4142 Power system protection
and switchgear
6 ELEC3141 -
4 ELEC4144 Electric vehicle
technology
6 ELEC3142 -
4 ELEC4145 Building services -
electrical services
6 ELEC2346 -
4 ELEC4146 Building services -
electrical installations
6 ELEC2147
or ELEC2346
-
4 ELEC4147 Power system analysis and
control
6 ELEC3141 -
4 ELEC4148 Smart grid and renewable
energy systems
6 ELEC3141 -
4 ELEC4149 Basic Lighting
Engineering
6 ELEC2346 -
4 ELEC4151 Hybrid electric propulsion
technology
6 - -
Group B: Electronics and Optics
Level Code Course Title Credit Prerequisite Co-
49
requisite
2 ELEC2346 Electric circuit
theory (core: CE,
EE, ElecE)
6 - -
2 ELEC2347 Fundamentals of
optics
6 - -
3 ELEC3342 Digital system
design (core: CE)
6 ELEC2346
or
ELEC2441
-
3 ELEC3347 Electronic materials
and quantum
physics
6 - -
3 ELEC3349 Optical devices 6 ELEC2346
or
ELEC2347
-
3 ELEC3350 Electronic circuits
and devices I (core:
ElecE)
6 ELEC2346 -
3 ELEC3351 Electronic circuits
and devices II
6 ELEC3350 -
4 ELEC4248 Photonic systems
technologies
6 ELEC2346
or
ELEC3349
-
4 ELEC4251 Microscopy 6 - -
4 ELEC4342 Embedded machine
learning: A
software-hardware
design flow
6 -
4 ELEC4343 Design of digital
integrated Circuits
6 ELEC3346
or
ELEC3350
-
4 ELEC4344 Advanced electronic
circuits
6 ELEC3346
or
ELEC3350
-
4 ELEC4642 VLSI design
principles
6 - -
Group C: Signal Processing, Control and Intelligent Systems
Level Code Course Title Credit Prerequisite Co-requisite
2 ELEC2245 Control systems I 6 - -
3 ELEC3241 Signals and linear
systems (core: ElecE,
EE)
6 - -
3 ELEC3244 Digital signal
processing
6 MATH1853
and
ELEC2346
-
3 ELEC3249 Pattern recognition and
machine intelligence
6 MATH1853
or
MATH2101
3 ELEC3255 Control systems II 6 ELEC2245
or
ELEC3245
-
50
4 ELEC4244 Multimedia signals
and applications
(mutually exclusive
with COMP3315)
6 ELEC3241 -
4 ELEC4245 Digital image
processing
6 MATH1853
or
MATH2101
-
4 ELEC4252 Robotic control and
vision
6 ELEC3241 -
Group D: Communications and Networking
Level Code Course Title Credit Prerequisite Co-requisite
2 ELEC2243 Introduction to electricity
and magnetism (core: EE,
ElecE)
6 - -
3 ELEC3243 Fundamentals of nextgeneration communications
(core: ElecE)
6 - -
3 ELEC3248 Engineering
electromagnetism and
antenna design
6 ELEC2242
or
ELEC2243
-
3 ELEC3443 Computer networks
(mutually exclusive with
COMP3234)
6 (ENGG134
0 or
COMP211
3 or
ELEC2543
) and
(COMP212
0 or
ELEC2441
)
-
4 ELEC4241 Communication systems 6 ELEC3242
or
ELEC3243
-
4 ELEC4253 Wireless Communications 6 ELEC3242
or
ELEC3243
-
4 ELEC4254 Microwave and RF
engineering
6 ELEC3248 -
4 ELEC4256 Wireless networking in the
era of machine learning
6 - -
4 ELEC4442 Advanced networking
technologies
6 ELEC3443
or
COMP323
4
-
Group E: Computer Systems and Data Engineering
Level Code Course Title Credit Prerequisite Corequisite
2 ELEC2441 Computer organization and
microprocessors (core: CE,
ElecE, EE)
6 - -
51
(mutually exclusive with
COMP2120)
2 ELEC2543 Object-Oriented
programming and data
structures (mutually
exclusive with COMP2119)
(core: ElecE)
6 ENGG1111
or
ENGG1112
or
ENGG1330
-
2 ELEC2544 Introduction to electronic
commerce and financial
technology
6 -
3 ELEC3441 Computer architecture
(core: CE)
(mutually exclusive with
COMP3231)
6 ELEC2441 -
3 ELEC3442 Embedded systems (core:
CE)
6 - -
3 ELEC3541 Software engineering and
operating systems (mutually
exclusive with COMP3230
and COMP3297)
6 - -
3 ELEC3542 Advanced programming
and application
development
6 - ELEC2543
or
COMP211
9 or
COMP239
6
3 ELEC3543 Advanced systems
programming
(core: ElecE)
6 ELEC2543
or
(COMP2119
&
COMP2396)
-
3 ELEC3544 Introduction to data
analytics
(core: CE)
6 - -
3 ELEC3641 Human computer
interaction
6 ENGG1111
or
ENGG1112
or
ENGG1330
-
3 ELEC3643 Systems and network
programming (mutually
exclusive with COMP3402)
6 ELEC2543
or
(COMP2119
&
COMP2396)
-
3 ELEC3644 Advanced mobile apps
development
6 ELEC2543
or
ELEC2840
-
4 ELEC4542 Introduction to deep
learning for computer vision
(Mutually exclusive with
COMP3340)
6 - -
4 ELEC4543 Fuzzy systems and neural
networks
6 - -
52
4 ELEC4544 Artificial intelligence and
deep learning
6 ELEC3241 -
4 ELEC4545 Time series analysis with
financial applications
6 ELEC3241 -
4 ELEC4546 Investment and trading for
engineering students
6 ELEC3241 -
4 ELEC4547 Emerging technology for
VR/AR
6 - -
4 ELEC4640 Distributed computing
systems
6 (ELEC3541
or
COMP3230)
&
(ELEC3443
or
COMP3234)
-
4 ELEC4641 Computer network security
(mutually exclusive with
COMP3355)
6 ELEC3443
or
COMP3234
-
Group F: Complementary Studies
Level Code Course Title Credit Prerequisite Co-requisite
2 ELEC2840 Engineering training 6 - -
2 ELEC3841 Internship 0 - -
3 ELEC3844 Engineering management
and society
6 - -
3 ELEC3845 Economics, finance and
marketing for engineers
6 - -
Group G: Projects
Level Code Course Title Credit Prerequisite Co-requisite
3 ELEC3848 Integrated design project 6 - -
4 ELEC4848 Senior design project 12 - -
Group H: Engineering Core courses
Level Code Course Title Credit Prerequisite Co-requisite
1 MATH1851 Calculus and ordinary
differential equations
6 - -
1 MATH1853 Linear algebra,
probability & statistics
6 - -
1 ENGG1300 Fundamental Mechanics 6 - -
1 ENGG1310 Electricity and
Electronics
6 - -
1 ENGG1320 Engineers in the Modern
World
6 - -
1 ENGG1330 Computer programming I
(mutually exclusive with
COMP1117 or
ENGG1111 or
IIMT2602)
6 - -
1 ENGG1340 Computer programming 6 ENGG1330 -
53
II
(mutually exclusive with
COMP2113 or
COMP2123)
or
COMP2117
1 ENGG1350 Thermofluid mechanics 6 - -
Group I: Mathematics
Level Code Course Title Credit Prerequisite Corequisite
1 MATH1851 Calculus and ordinary
differential equation
6 - -
1 MATH1853 Linear algebra, probability &
statistics
6 - -
2
COMP2121
Discrete mathematics
(mutually exclusive with
MATH3600)
6 - -
2 ELEC2843 Multivariable calculus and
elementary partial differential
equations
6 MATH1851
&
MATH1853
-
2 ELEC2844 Probabilistic systems analysis
(mutually exclusive with
STAT2601)
(core: CE)
6 MATH1853 -
2 ELEC2845 Applied optimization and
applications
(mutually exclusive with
ELEC3846 and COMP3407)
6 MATH1853 -
3 MECH3407 Advanced partial differential
equations & complex
variables
6 - -
3 ELEC3846 Numerical methods and
optimization (mutually
exclusive with COMP3407)
6 - -
4 ELEC4745 Queueing theory 6 ELEC3847/
ELEC2844
-
Group J: Software and IT Applications
Level Code Course Title Credit Prerequisite Co-requisite
2 COMP2113 Programming
technologies (mutually
exclusive with
ENGG1340 or
COMP2123)
6 COMP1117 or
ENGG1330
-
2 COMP2119 Introduction to data
structures and
algorithms (core: CE)
6 ENGG1340 or
COMP2113 or
COMP2123
-
2 COMP2396 Object-oriented
programming and Java
(mutually exclusive
with ELEC2543 or
FITE2000)
6 ENGG1340 or
COMP2113 or
COMP2123
-
54
3 COMP3230 Principles of operating
systems (mutually
exclusive with
ELEC3541) (core: CE)
6 ENGG1340 or
COMP2113 or
COMP2123; and
COMP2120 or
ELEC2441
-
3 COMP3234 Computer and
communication
networks (mutually
exclusive with
ELEC3443)
6 COMP2113 or
COMP2123 or
ELEC2543 or
ENGG1340; and
COMP2120 or
ELEC2441
-
3 COMP3235 Compiling techniques 6 COMP2119 or
FITE2000
-
3 COMP3278 Introduction to
database management
systems (mutually
exclusive with
IIMT3601)
6 COMP2119 or
COMP2502 or
ELEC2543 or
FITE2000
-
3 COMP3297 Software engineering
(mutually exclusive
with IIMT3602) (core:
CE)
6 ENGG1340 or
COMP2113 or
COMP2123
-
3 COMP3322 Modern technologies
on World Wide Web
(mutually exclusive
with IIMT3663)
6 COMP1117 or
ENGG1330
-
3 COMP3323 Advanced database
systems
(mutually exclusive
with: FITE3010)
6 COMP3278 -
3 COMP3329 Computer game design
and programming
6 ENGG1340 or
COMP2113 or
COMP2123
-
3 COMP3352 Algorithmic game
theory
6 MATH1853 or
MATH2014 or
MATH2101; and
COMP2119
-
3 COMP3354 Statistical learning 6 MATH1853 or
MATH2101 or
STAT1602 or
STAT1603
-
3 COMP3355 Cyber security
(mutually exclusive
with ELEC4641)
6 COMP2119 or
ELEC2543 or
FITE2000
-
3 COMP3407 Scientific computing 6 COMP1117 or
ENGG1330 or; and
COMP2121
-