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Mathematical Modeling

M.Sc. Mathematical Modelling Pure and Applied Mathematics Department African University of Science and Technology (AUST), Abuja

M.Sc. Mathematical Modelling

Pure and Applied Mathematics Department

African University of Science and Technology (AUST), Abuja


Most things in the real world are really complex systems which cannot be fully understood by using linear representations. Consider, for example, the complex biological systems that make up our lives and our environment, the increasingly complex financial markets and myriad industrial processes, managing traffic flows, spread of diseases, etc, all of which can only be understood, mimicked and predicted if we use dynamic mathematical models. Mathematical modelling, an essential part of contemporary applied mathematics, is a fundamental tool for understanding these systems and can be a powerful tool for planning purposes in modern economies. This program will both draw from existing capacity in the Mathematics Institute and add capacity to it.

This program course has three main aims: to provide an understanding of the processes involved in creating a viable mathematical model; to teach the fundamental analytical techniques and computational methods used in understand the behaviour of systems and to expose students to a range of typical applications (e.g. industrial, biological and environmental).

The program consists of nine 4-credit courses to make up a total of 36 credits, plus a project in which theory is applied to a practical problem. All courses will be taught and assessed on the basis of any combination of continuous assessment, examinations and applied mini projects. A letter grade will be awarded for each course completed. Courses will be offered over 3 semesters (18 calendar months). Courses include: Non Linear Systems; Numerical Solution of Partial Differential Equations; Computational and Simulation Methods; Advanced Mathematical Modelling Techniques; Asymptotic Models and Boundary Layer Theory; Geophysical Fluid Dynamics; Biomathematics; Discrete Mathematics and Algorithms; Stochastic dynamic modelling

Admission requirements for the MSc program include a Bachelor’s degree in relevant field with a second class upper (minimum CGPA of 3.0 on a 4 point scale and 3.5 on a 5 point scale). The candidate must obtain a minimum CGPA of 3.0 to graduate from the program. The programme is very intensive and only well-motivated and prepared students are encouraged to apply. The courses are taught as 3- or 4-week modules of 45 to 60 hours, including lectures and problem solving sessions. Details of the course outline are in the handbook. The Problem Based Learning (PBL) and Outcome Based Education (OBE) approaches are used in teaching.


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