Master (by Coursework)
Understanding complex phenomena in real world problems requires knowledge and skills at an advanced level. Modelling the complex dynamical system and dealing with unpredictable processes must be based on the combination of pure and applied mathematics. To certain extent, some problems may need solution with the aid of Machine Learning in parallel with industrial revolution nowadays. This programme has been designed to equip you with the knowledge and skills that you really need for your career. Our experts are waiting to serve you!
- Bachelor’s Degree in Science (Computational Mathematics) or Bachelor’s Degree in Science (Financial Mathematics) with a minimum CGPA of 2.75 from UMT; OR minimum CGPA 2.50 with minimum five (5) years’ work experiences.
- Bachelor’s Degree in Science with Honours and equivalent to part (i), with a minimum CGPA of 2.75, from higher institutions recognized by the Senate; or minimum CGPA 2.50 with minimum five (5) years’ work experiences.
English Language Requirements
- English requirement for international candidates: TOEFL with minimum score 550; or IELTS with minimum band 6.0.
Duration: Full-time: 1 year (minimum) / Part-time: 2 years (minimum)
Credit hours: 44 credits
Program Core modules include
This course discusses nonlinear ordinary differential equations from an analytical point of view and involves significant use of a number of concepts, including equilibrium points, orbits, phase portraits and limit cycles. Several methods such as linearization are discussed to determine existence and stability of equilibrium points and analyze nonlinear differential equations such as. An introduction to chaos theory is also presented. The techniques will be applied to nonlinear differential equations from physics, engineering, biology, ecology.
The numerical method is an important tool to solve problems in various fields. In this course, students will be exposed to a number of numerical methods appropriately. They also will be guided to develop and to improve the numerical methods based on the given problems. This course is embedded with programming element thus the developed solution can be implemented by using a computer. Throughout this course, the students are expected to perform numerical computation in a few projects in order to get real experience in solving mathematical modeling.
In this course, students are applied with knowledge of the process that need to be taken for mathematical modeling of the various considered issues. In addition, students are exposure to methodology and mathematical skills in modeling. The topics include the problems in industrial and physical sciences especially in the field of maritime and maritime decision-making. The discussion of the modeling approach based on analitical or numerical solutions and the suitability of the model from research papers will be highlighted. Also, Students will use their knowledge and skills to simulate or visualize the results. The detailed syllabus could be changed from year to year with the different talk of research from lecturers and visitors (if applicable).
Machine learning is concerned with the question on how to make computers learn from experience. The ability to learn is not only central to most aspects of intelligent behaviour, but machine learning techniques have become key components of many software systems. This course covers both well-established and advanced machine learning techniques such as Neural Network, Support Vector Machines etc.
This course discusses the general methods used in conducting research. The style and method of writing a research proposal paper is also discussed. In addition, issues related to the attitude and value of professionalism as researchers and ethics in writing and publishing are also being highlighted in this course.
This course aims to provide a space for students to demonstrate social skills, teamwork and responsibility in organizing postgraduate colloqium ethically, morally and professionally. In addition, effective oral communication is also emphasized through the individual presentation of the organized colloquium.
Programme Elective modules may include
In this course, basic introduction for physical oceanography such as ocean and athmospheric characterictic, temperature, salinity, density of the oceans will be introduced. Then, the derivation of fluid and geophysical fluid dynamics that is commonly used in solving ocean waves problem is also included. This is followed by the formulation of basic mathematical models that are often used in solving physical oceanographic problems such as shallow water equations, rotating shallow water equations and wind-driven circulation. Next, this course will also critically discuss the solutions and results obtained in solving related models either analytically or numerically.
This course focuses on the knowledge needed to solve wave problems using computational wave dynamics. The development of history, philosophy and the importance of computational fluid dynamics are generaly discussed. Turbulance models, governing equations and basic principles of wave dynamics are introduced such as the equations of viscous fluid, multiphase flow equations and wave equations. Fundamentals in computational method such as discritisation of finite difference is discussed along with its boundary conditions. Several numerical techniques will be considered to be discussed in this course according to the suitability of the problems to be solved, for example fluid volume method, constrained interpolation profile method, particle method and so on.
The course describes the stochastic method for ocean wave analysis which provides a route to predicting the characteristics of random ocean waves which give vital information for the design and safe operation of ships and sea structures. Begin with a discussion on fundamental knowledge on probability theory, stochastic process and transformation, the course is then describes the essential elements of wind-generated random seas from the stochastic point of view. Next, spectral analysis technique for ocean waves is introduced, probabilistic prediction of wave amplitude and height under various condition is done. Consideration on the wave height, period and travel direction of wind-generated random wave completes the course.
This course explains whats knowing from ocean circulation exploration integrated with latest approximation about transport quantitiy and basic background for dynamical systems. Also discussed about fixed point, stability and bifurcations and numerical techniques to solve the model from dynamical systems point of view.
This course enables students obtain the knowledge in solving problems related to maritime management.
This course discusses algorithm concepts such as mapping and comparison between algorithms. It focuses on a few Quasi-Newton methods and constrained optimization. Optimization method in maritime is also covered.
This course will introduce the fuzzy set decision theory in maritime activities. Firstly, this course discussses the fundamental topics in fuzzy set decision making, namely interval value fuzzy set, some properties of fuzzy sets theory, the development of membership function and decision making with uncertainties. Finally, this course will discuss the applications of fuzzy sets decision making in maritime studies such as Fuzzy AHP, Fuzzy TOPSIS and Fuzzy DEMATEL.
This course allows student gain knowledge in decision making for solving optimization problem in maritime using quantitative methods using heuristic methods. This will improve the student’s ability to make more systematic decision.
Project module include
This course enables students to expand their Mathematical knowledge, understading and skills that are required to solve a problem in related field using scientific methodology. These include planning, implementation and presenting significant research project outcomes.
Fees and funding
The 2021/22 annual tuition fees for this programme are:
Home RM 11, 140.00
International full-time MYR 17, 810.00
General additional costs
Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at UMT.
You may be eligible for government finance to help pay for the costs of studying. See the Government’s student finance website.
Scholarships are available for excellence in academic performance, sport and music and are awarded on merit. For further information on the range of awards available and to make an application see our scholarships website.
Find out More
Semester II Session 2020/2021
- Briefing on the commencement of study
- Buku Panduan Program Ijazah Sarjana Matematik dan Sarjana Statistik Sains Marin (pdf-in Malay)
- Jadual Kuliah (pdf-in Malay)
- Academic Calendar Session 2020/2021 (pdf)
Dr. Che Mohd Imran Che Taib
Phone: +609-668 3759 (office)