Pre-requisite(s): None 

Course Description:
This course provides students with basic knowledge of computer-oriented problem solving methodologies, algorithm development, structured programming concepts and design techniques, and implementation tools that facilitate debugging and testing. In particular, structured programming skills will be illustrated with a contemporary programming language.

Pre-requisite(s): 
COMP1013 STRUCTURED PROGRAMMING, or
GCIT1013 FOUNDATIONS OF C PROGRAMMING, or
COMP1023 FOUNDATIONS OF C PROGRAMMING, or
COMP2013 OBJECT-ORIENTED PROGRAMMING, or
STAT2043 STRUCTURED PROGRAMMING (FOR STAT STUDENTS), or
COMP3153 C++ PROGRAMMING LANGUAGE

Course Description: 
This course develops students’ knowledge of data structures and their associated algorithms. It introduces the concepts and techniques of structuring and operating on Abstract Data Types in problem solving. Common sorting, searching and graph algorithms will be discussed, and their complexity studied.

Pre-requisite(s): None 

Course Description: 
This course introduces the basic techniques in matrix algebra, which is the foundation for more advanced mathematics and statistics subjects. Major emphasis will be on the system of linear equations, linearly independence in finite dimensional vector spaces..

Pre-requisite(s): 
MATH1053 LINEAR ALGEBRA I, or
MATH1003 LINEAR ALGEBRA, or
MATH1173 LINEAR ALGEBRA

Course Description: 
This course introduces the basic techniques in matrix algebra, which is the foundation for more advanced mathematics and statistics subjects. Major emphasis will be on the system of linear equations, linearly independence, and eigenvalue problems in finite dimensional vector spaces. Basic ideas and techniques on calculus will be introduced.

Pre-requisite(s): None 

Course Description:
This course introduces the basic ideas and techniques in single variable calculus with mathematical rigour to prepare students for more advanced mathematical and statistical subjects.

Pre-requisite(s):
MATH1073 CALCULUS I, or
MATH1123 CALCULUS FOR SCIENCE AND ENGINEERING, or
MATH1103 CALCULUS

Course Description:
This course is a continuation of Calculus I. It provides a solid foundation in multivariable calculus to prepare students for more advanced mathematics and statistical subjects.

Pre-requisite(s):
MATH1063 LINEAR ALGEBRA II, and
MATH1083 CALCULUS II

Course Description:
This course introduces various forms of ordinary differential equations and their solution methods using analytical techniques. Topics include first order, second order and higher order scalar ODE, serious solution to second order linear ODE, systems of first order ODE, Laplace transform for initial value problems. .

Pre-requisite(s):
MATH1083 CALCULUS II

Course Description:
This course is a rigorous sequence in analysis on the line and higher dimensional Euclidean spaces. Limit, continuity, least upper bound axiom, open and closed sets, compactness, connectedness, differentiation, uniform convergence, and generalization to higher dimensions.

Pre-requisite(s):
MATH2043  ORDINARY DIFFERENTIAL EQUATIONS

Course Description:
This course introduces the theory of multi-dimensional scalar and system of parabolic, elliptic and hyperbolic partial differential equations (PDEs) that model physical processes in areas such as physics, biology, chemistry and social science. Solution techniques such as the separation of variables, eigenfunction expansions, Green functions, Fourier and Laplace transforms for solving the equations in a bounded and unbounded domain, with homogeneous and inhomogeneous source term will be studied in detail.

Pre-requisite(s):
MATH1083 CALCULUS II 

Course Description:
This course provides an introduction to measure theory, Lebesgue integration, LP space, and Fourier analysis. Equipped with this knowledge, students are prepared for further studies in numerical analysis, functional analysis and advanced probability theory.

Pre-requisite(s):
MATH1063 LINEAR ALGEBRA II, and
MATH1083 CALCULUS II, and
COMP3153 C++ PROGRAMMING LANGUAGE or COMP1023 FOUNDATIONS OF C PROGRAMMING

Course Description:
This course introduces numerical methods on various problems, such as equation solutions, interpolations, differentiations and integrations, initial value problems, linear systems, and error analysis on these numerical methods. Students would learn the theory of numerical analysis, as well as its rich applications in science and economics. After studying this course students will have a better mastery of techniques in numerical analysis.

Pre-requisite(s):
MATH1083 CALCULUS II 

Course Description:
This course introduces introduce the basic theory of analytic functions of one complex variable. The topics include some important theorems, like Cauchy’s theorem, Residues theorem and series representation of analytical functions and conformal mappings and their applications.

Pre-requisite(s):
MATH1073 CALCULUS I 

Course Description:
This course aims to let students apply mathematical and statistical skills to real world problems according to the basic principles of mathematical and statistical modelling and investigate meaningful and practical problems chosen from common experiences encompassing many academic disciplines, including mathematical sciences, engineering, operations research, management sciences, and life sciences. It can also enable students to use related computing software in mathematical modelling and problem solving and to formulate real world problems as mathematical models.

Pre-requisite(s): None 

Other Condition(s):
Year 4 standing in Applied Mathematics Programme 

Course Description:
To enable students to go through an independent learning experience. (2) To provide students with opportunities in developing skills, including the use of on-line and off-line materials, the logical development of scientific arguments, thesis writing skills, presentation techniques and time management. (3)To enable students to demonstrate an integrated understanding of mathematics through solving real-life problems.

Pre-requisite(s):
MATH1053 LINEAR ALGEBRA I or MATH1003 LINEAR ALGEBRA,
and MATH1073 CALCULUS I or MATH1123 CALCULUS FOR SCIENCE AND ENGINEERING

Course Description:
This course introduces the fundamental theory and techniques for both unconstrained and constrained optimization. There will be an overview of the existing numerical software packages. Finally some interdisciplinary techniques and applications related to optimization will be discussed.

Course Description: 1. To provide an introduction to some important concepts in probability theory. 2. To familiarize students with random variables and various probability distributions. 3. To familiarize students with random vectors and their distributions.

Course Description: The aim of this course is to emphasize the application of various statistical methods in real data analysis and expand students’ statistical toolbox through numerical and simulation methods. Additionally, the course will teach students how to approach statistical problems from a computational perspective. They will learn how to set up and run stochastic simulations, how to fit basic statistical models and assess the results, and how to work with and filter large data sets.

Pre-requisite(s): None 

Course Description:
This course provides the student with a solid foundation in the principles of biology, from molecular biology to cells to the diversity of life. Topics include the structure and function of representative organisms, and their diversity. Latest advances in biology are incorporated into the course. There is also an overview of the scientific process/method, and examples are reviewed to show how the process works.

Pre-requisite(s):
COMP1013 STRUCTURED PROGRAMMING, or
GCIT1013 FOUNDATIONS OF C PROGRAMMING, or
COMP1023 FOUNDATIONS OF C PROGRAMMING, or
STAT2043 STRUCTURED PROGRAMMING (FOR STAT STUDENTS), or
COMP2013 OBJECT ORIENTED PROGRAMMING, or
COMP3153 C++ PROGRAMMING LANGUAGE

Course Description:
The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. .

Pre-requisite(s): MATH1083 CALCULUS II  

Course Description: This course introduces how to use python programming language to do data collection, storage, analysis and visualization. After studying this course, students will learn how to crawl data from the web, store data into database, perform statistical analysis, and visualize the result. Equipped with these skills, students can further analyse finance data, make predictions and do back testing. To take this course, students are required to have some basic background in computer programming.

Course Description: This course aims to give students a basic understanding of econometrics and regression analysis. Numerous examples will be examined in order to achieve this goal. Emphasis will be placed on the classical linear regression model, least squares estimation, hypothesis testing, and model building, and application to practical economic problems on forecasting and analysis. In addition, this course will train students to use computer statistical software.

Pre-requisite(s): 

MATH1083 CALCULUS II, and  

MATH1063 LINEAR ALGEBRA II

Course Description: This course aims to provide students with recent developments in Black-Scholes-Merton Model and its applications to finance, such as option pricing in Binomial Tree Method. In particular, the course addresses a large spectrum of problems and techniques. The objective is to enable student to understand how Black-Scholes-Merton Model provides a large set of theoretical and computational tools with applications in option pricing.

Pre-requisite(s): 
MATH1063 LINEAR ALGEBRA II, and
MATH1083 CALCULUS II

Course Description:
This course aims to introduce basic ideas of discrete mathematics such as formal mathematical reasoning techniques, basic counting techniques and their applications for computer science students. The emphasis is on understanding the concepts and the ability to solve problems. The objective is for students to understand the basic theory and some applications of discrete mathematics. The course gives students training in the ability to think quantitatively and analyse problems critically.

Pre-requisite(s):
MATH1063 LINEAR ALGEBRA II, and
MATH1083 CALCULUS II

Course Description:
This course provides students with the mathematical tools of classical differential geometry, fundamental topological invariances of curves and surfaces and the theory of intrinsic geometry of surfaces. Also trains them to apply techniques in shell theory and cartography.

Pre-requisite(s):
STAT2023 ADVANCED PROBABILITY or STAT2063 PROBABILITY THEORY or MATH2063 PROBABILITY AND STATISTICS, and
MATH1063 LINEAR ALGEBRA II,and
MATH1083 CALCULUS II

Course Description:
This course reviews basic probability theory and deals with major stochastic processes including Poisson processes, renewal theory, Markov Chains and continuous-time Markov Chains. Applications to inventory problems, equipment replacement policy and queuing theory are also dealt with through some examples.

Pre-requisite(s): None 

Course Description:
This course covers some fundamental concepts and principles of graph theory. Practical topics include the Chinese postman problem, the travelling salesman problem and the map colouring problems. Applications of the theory and some related algorithms are also discussed.

Pre-requisite(s):
STAT2003 ADVANCED STATISTICS, or
MATH2063 PROBABILITY AND STATISTICS

Course Description:
To introduce computational methods for problems in finance, including the computation of market indicators and option prices. The market indicators include stock and option indices. The option prices are based on the Black-Scholes model. Finite difference methods, Monte Carlo Methods and Binomial Tree Methods will be introduced.

Pre-requisite(s):
MATH1063 LINEAR ALGEBRA II, and
MATH1083 CALCULUS II

Course Description:
This course aims to give students a broad training on various analytical techniques in modern applied mathematics. It intends to equip learners, through various teaching and learning activities and assessment methods, with skills and knowledge to solve more sophisticated mathematical problems in various areas.

Pre-requisite(s):
MATH1063 LINEAR ALGEBRA II, and
MATH3043 REAL ANALYSIS (FOR MATH STUDENTS) or MATH3163 REAL ANALYSIS 

Course Description:
This course aims at familiarizing the student with the basic concepts, principles and methods of functional analysis and its applications. The notions of metric spaces, fixed point theorems, Banach spaces, Hilbert spaces, continuous linear operator, the Hahn-Banach extension theorem, the uniform boundedness principle and the open mapping theorem, and applications of the above topics will be introduced.

Pre-requisite(s):
MATH3053 NUMERICAL METHODS I, or MATH4083 NUMERICAL ANALYSIS

Course Description:
This course aims to apply numerical methods and scientific computing techniques for ordinary and partial differential equations. This course introduces the major numerical techniques for solving ordinary and partial differential equations. Emphasis is placed on finite difference methods. Methods for different classes of first and second order linear PDEs are described and analysed. It trains students to design computer programmes and apply them to solve differential equations.

Pre-requisite(s): None 

Other Condition(s):
Year 4 standing in Applied Mathematics Programme 

Course Description:
(1) To enable students to go through an independent learning experience. (2) To provide students with opportunities in developing skills, including the use of on-line and off-line materials, the logical development of scientific arguments, thesis writing skills, presentation techniques and time management. (3) To enable students to demonstrate an integrated understanding of mathematics through solving real-life problems.

Pre-requisite(s):
MATH1053 LINEAR ALGEBRA I

Course Description:
To introduce fundamental theory, techniques and algorithms for linear programming and integer programming problems. It addresses both the basic as well as advanced topics in linear programming and integer programming. Several software packages will be also introduced.

Pre-requisite(s): 

STAT2003 ADVANCED STATISTICS or

Course Description: To introduce the basic computer simulation in various discrete systems. The aim is to model and simulate various practical systems in financial, transportation, and commercial applications. This course covers the basic concepts, models and computer software in simulating practical discrete systems.

Pre-requisite(s): None 

Course Description:
This course teaches the basic principles of physics to explain the properties of heat, light, electricity, magnetism, and quantum mechanics of atoms and then apply the principles to study the functions of electronics, analytical instruments, environmental monitoring instruments, solar panel, etc. In addition, the impacts of important physical phenomena such as air movement, light scattering by particulate matter, global warming, solar radiation, radioactivity, etc. on the formation of environmental risks and pollutions will be analysed. The basic principles of physics taught in this course can be applied not only to Environmental Science, but also to other sciences and everyday life.

Pre-requisite(s):
MATH1053 LINEAR ALGEBRA I, and
MATH1063 LINEAR ALGEBRA II, or MATH1003 LINEAR ALGEBRA

Course Description:
This course provides an understanding of classical multivariate analysis and modern techniques in data mining which are useful for analysing both designed experiments and observational studies. Real data in social, life, and natural sciences are analysed using statistical packages such as R or MATLAB.

Pre-requisite(s):
MATH1083 CALCULUS II and MATH1063 LINEAR ALGEBRA II, or
COMP1023 FOUNDATIONS OF C PROGRAMMING, or
COMP2013 OBJECT-ORIENTED PROGRAMMING

Course Description:
In this information age much data are collected, but less often analysed. This course covers methods for gleaning useful information for large data sets. These methods may be used to help improve product marketing, increase operational efficiency and discover new knowledge.