The Bachelor of Science (Applied Mathematics) with Honours is a program formulated as an effort to produce graduates trained in the field of Mathematical Science who are able to apply their knowledge and expertise to meet the nation’s manpower needs. The program curriculum has been fully integrated to meet the eleven domains of program learning outcomes recommended by the MOHE. This program basically trained the students to apply mathematical knowledge as well as related concepts in various areas of focus such as computing, optimization, geometry, physical science, and so on. Students will also be exposed to knowledge and skills in various up-to-date mathematical methods as well as computer programming. Along with the development of current technology and the needs of the industrial revolution (IR) 4.0, several courses in this program have been embedded with SAS modules that enable students to obtain a globally recognized SAS professional certificate. In addition, the program also trains students to think logically, structured and precise manner and thus enables them in finding effective solutions in related fields. At the end of the study, in the seventh semester, students will undergo Industrial Training for 24 weeks in the industry whether public or private, local or international sector. While in the industry, students will be supervised by supervisors from the industry and have the opportunity to practice the theories learned in the lecture room as well as go through real-world work experience in preparation for the next phase. The duration of study for this program is 7 semesters or three and a half years.
This programme is offered for students to achieve the following objectives:
PEO1 : Knowledgeable and have practical skills in the field of Applied Mathematics in line with industry requirements.
PEO2 : Have effective communication and interpersonal skills and demonstrate good leadership qualities in the organization.
PEO3 : Ability to analyze and solve real problems using numeracy skills based on scientific methods and critical thinking without compromising on values and integrity.
PEO4 : Ability to access, manage and deliver information using the latest digital technology as well as demonstrate entrepreneurial skills as added value for career advancement.
This course covers the basic concept of corruption, including the value of integrity, anti-corruption, forms of corruption, abuse of power in daily activities and organizations as well as waysto prevent corruption. Cases related to corruption are discussed. Teaching and learning methods are implemented in the form of ‘experiential learning’ through individual and group activities. At the end of this course, students are able to understand the practice of integrity, the concept of corruption, anti-corruption, abuse of power as well as the prevention of corruption in society and organizations.
This course gives students an exposure to the basic concepts of entrepreneurship. Students will do learning activities that lead to building an entrepreneurial mindset as an initial preparation for a future career. This course provides an exposure to students on knowledge in entrepreneurship. It also gives students the opportunity to apply the knowledge obtained from their respective fields. In addition, the course aims to apply the entrepreneurial mind sets into their life after graduation.
This course discusses the topics of limit and continuity, multivariable functions, partial derivatives, total derivative and multiple integration. In addition, this course also discusses the cylinder coordinate, spherical coordinate and the change of variables in multiple integration.
This course is an introduction to techniques of solutions for differentiation equations that require a basis in calculus as well as algebra. Discussions on applications in real problems are also implemented. This course is necessary as the basis for the relevant advanced courses namely Applied Mathematical Methods and Partial Differential Equations.
The course discusses the concepts of vector space including row space and column space, linear transformation including covering matrix representation and similarity matrices, orthogonality up to the Gram-Schmidt orthogonalization process, eigenvalues, eigenvectors, eigenspace and numerical linear algebra.
This course presents numerical methods for solving mathematical problems. Both theoretical and computer implementation of the methods are discussed in this course. It covers solution of nonlinear equations, interpolation and approximation, numerical integration and differentiation and solution of ordinary differential equations.
This course discusses basic concepts for statistics including probability, random variables, probability distributions of random variables, sampling distribution theory, estimation and hypothesis test.
This course discusses linear models, nonparametric methods, multivariate distribution and some approaches in applied multivariate.
This course discusses the concepts of real number space, bounded set, similar set, finite set and countable set. Point set topology on real line includes the ideas of openness and closeness, compact set and connected set. This course also discusses the properties of convergence sequences of real numbers including the pointwise convergence and uniform convergence of functions. Discussion on several important properties such as limit function, continuity, continuity on compact and connected sets and uniform continuity end this course.
This course discusses an introduction to good programming style through examples, the modification of existing computer programming such as C++ codes to solve similar problems and the implementation of mathematical algorithms in a well-documented computer programming program. This course supports IR 4.0 by means of systematic thinking.
This course discusses the fundamental concepts of linear programming problems and the methods of solution. Topics also include simplex method, duality and its sensitivity analysis, transportation and network problems. The course also supports the industrial revolution through the application of SAS programming to solve optimisation problems.
This course discusses several mathematical techniques which are used in solving for unconstrained and constrained optimization problems. Unconstrained methods include Fibonacci search, Newton method, Secant method, gradient method and conjugate direction method. Meanwhile constrained methods include Lagrange condition and Karush-Kuhn-Tucker condition. Students also will solve optimization problems using software SAS.
This course discusses the topics involves the vector and geometry of space, calculus for vector valued functions and integration of vector valued function in two and three dimensional of space.
This course discusses the concepts of sets, functions and the set of integers. It continues by discussing linear congruence and subsequently equivalence relations. The concepts on groups, rings and fields, which also include several basic theories relating to the topics which cover mappings, and the basic ideas on direct products of groups are also discussed. Discussion on theory of ideals and basic operation involving ideals end this course.
This course discusses mathematical methods and techniques commonly used in solving science, technology and engineering problems. It begins with a series solution for differential equations involving the power series method and the Frobenius method. Applications for the power series and the Frobenius series were also discussed in solving special differential equations such as the Legendre, Hermite, Laguerre and Bessel equations which eventually produced special polynomial functions such as the Legendre, Hermite, Laguerre and Bessel polynomials. Later, Fourier analysis which is one of the methods often used in solving real world problems is also discussed in this course. At the end of the course, these methods and the method of separation of variables are used to solve the partial differential equations involving the Heat, Wave and Laplace equations.
This course discusses the topics involves introductory to mathematical modelling, dimension analysis, model approximation and verification and their applications.
This course presents the basics elements of scientific computing, in particular the methods for solving or approximating the solution of calculus and linear algebra problems associated with real world problems. Using a non-trivial model problem, sophisticated scientific computing and visualisation environments, students are introduced to the basic computational concepts of stability, accuracy and efficiency. New numerical methods and techniques are introduced to solve more challenging problems.
Students who have met the requirements for practical training shall be located at suitable industries for a period of 24 weeks, after 6 semesters of studies. Each student is required to do a comprehensive report equivalent to 12 credits under the supervision of a lecturer decided upon by the coordinator for practical training and the supervisor in charge at the industry concerned
This course exposes the students with the basics in academic research, especially in writing the proposal of a scientific research project.
This course is a direct continuation of the MTK4998A course which allows students to implement scholarly projects that have been systematically recommended. Among the areas of research thrust are pure mathematics, applied mathematics, statistics, optimization, fuzzy set theory, financial mathematics, computer-assisted graphic design, numerical analysis methods and operational research. An appropriate series of talks will be given to the students and further discussions on the topic of the talk will be conducted with their respective supervisors next. All students are required to write, submit and present the final report of their respective academic projects in chronological order as determined by the Program.
This course discusses basic concepts for statistics including probability, random variables, probability distributions of random variables, sampling distribution theory, estimation and hypothesis test.
This course discusses linear models, nonparametric methods, multivariate distribution and some approaches in applied multivariate.
This course discusses the fundamental concepts of linear programming problems and the methods of solution. Topics also include simplex method, duality and its sensitivity analysis, transportation and network problems. The course also supports the industrial revolution through the application of SAS programming to solve optimisation problems.
This course discusses several mathematical techniques which are used in solving for unconstrained and constrained optimization problems. Unconstrained methods include Fibonacci search, Newton method, Secant method, gradient method and conjugate direction method. Meanwhile constrained methods include Lagrange condition and Karush-Kuhn-Tucker condition. Students also will solve optimization problems using software SAS.
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Specific Requirements:
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General Entry Requirements:
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Specific Requirements
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General Entry Requirements
English Language Requirements
Our International Centre office will be happy to advise prospective students on entry requirements. See our International Centre website for further information for international students.
Local | International | Additional Costs |
RM 7,210 | USD 7,150 | Find out more about accommodation and living costs, plus general additional costs that you may pay when studying at UMT. |
Government funding
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 and co-curricular activities, and are awarded on merit. For further information on the range of awards available and to make an application see our scholarships website.
Email: shalela@umt.edu.my
Phone: +609 – 668 3976 (office)
+6011 – 2608 9528 (mobile)