MTH2051 - Introduction to computational mathematics - 2018

6 points, SCA Band 2, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.



Organisational Unit

School of Mathematical Sciences

Chief examiner(s)

Professor Hans De Sterck


Professor Hans De Sterck

Unit guides



  • Second semester 2018 (On-campus)


One of MTH2010, MTH2015, ENG2005 or MAT1830; and one of MTH2021, MTH2025, MTH2040 or MAT1841




When mathematics is used in real-world applications, it almost always involves the use of computers. This unit provides an introduction to numerical methods for solving maths-related problems on computers. Topics covered include introduction to Matlab programming; error analysis; methods for solving linear systems, least-squares problems and eigenvalue problems; methods for finding roots of nonlinear equations; polynomial interpolation; numerical differentiation and integration; and numerical methods for ordinary differential equations. Students will receive a solid introduction to the theory of the numerical methods (with derivations of the methods and some proofs), and will learn to implement the computational methods efficiently in Matlab. The methods and techniques learned have broad applicability in areas that include the natural sciences, engineering, the biomedical sciences, finance, business, machine learning, and data science.


On completion of this unit students will be able to:

  1. Understand the mathematical theory behind important numerical methods for solving real-life problems on computers.
  2. Implement numerical methods for a variety of problems in Matlab, and test the accuracy and efficiency of implementation.
  3. Understand the approximations introduced in algorithms and the effects of those approximations on the quality of calculations.
  4. Solve theoretical and applied problems of analysing and employing numerical methods.
  5. Be aware of the reach and importance of numerical methods in science, engineering, finance and technology.
  6. Demonstrate advanced problem solving skills, both individually and collectively with staff and fellow students.
  7. Demonstrate advanced skills in the written and oral presentation of theoretical and applied numerical mathematics problems.


Examination (3 hours): 60% (Hurdle)

Continuous assessment: 40%

Hurdle requirement: To pass this unit a student must achieve at least 50% overall and at least 40% for the end-of-semester exam.

Workload requirements

Three 1-hour lectures and an average of one hour of laboratory classes per week

See also Unit timetable information

This unit applies to the following area(s) of study