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This online self-guided learning course is for MSD postgraduate researchers who want to gain a good understanding of MATLAB's programming language and applications.


This course aims to give students a good understanding of the MATLAB programming language, and the use of MATLAB in data analysis, image analysis, numerical calculus, linear algebra and the solution of ODEs. Where applicable, a revision of elements of A-level mathematics needed for these areas is provided. Elements of software engineering are covered to give students the ability to write well-structured code, as well as how to use MATLAB to present their work using movies or Graphical User Interfaces (GUIs). The course is self-taught: students will work through guided online material over six weeks, with direct access to the course tutor via MS Teams.



The course comprises 6 units of study. The first three are compulsory and must be completed as a condition of accepting a place on the course. Following completion of the first three units there will be an online assessment. All 6 units will be available to complete online for a period of 6 weeks.

Units 4,5 and 6 are more advanced units and completion is optional.

You will need to have least A-level maths in order to complete this course.

An online tutor will be available at specific times each week to answer your queries.



Unit 1: Basic introduction to MATLAB

In this introductory unit you will learn the basics of MATLAB, from how to start MATLAB through to how to use it to write simple code and to use basic graphic capabilities of MATLAB. The aim of this unit is for you to acquire a familiarity with MATLAB and to learn a few basic commands.

Unit 2: Data analysis, image analysis and basic statistics in MATLAB

Data analysis and statistics are the cornerstones of most quantitative disciplines. MATLAB has many inbuilt commands for calculating statistics from large data-sets. In this unit we will look at some of the MATLAB inbuilt statistical commands and also use of MATLAB to perform some common data analysis techniques. By the end of the unit you should be able to perform simple statistical analyses on data-sets and have gained an understanding of how to use MATLAB to generate various types of random samples. We will also learn how to read data (including images) into MATLAB, how to display this data, how to process this data and how to write the data back to a file.

Unit 3: Basic calculus in MATLAB

The purpose of this unit is to use MATLAB to carry out many of the analytical mathematical techniques that you know. We will look at traditional methods of numerical differentiation and integration as well as root-finding algorithms. Also included is a section on Fourier series which allow discontinuous functions to be approximated by sums of continuous functions. The aim of the unit is to show you how to use MATLAB to undertake all these operations and also to give you practice in creating MATLAB functions.

Optional Further Units:

Unit 4: Linear algebra in MATLAB

The solution of systems of linear equations forms the basis of many techniques in applied mathematics and statistics, so numerical linear algebra forms perhaps the most important set of tools in scientific programming. MATLAB has been developed specifically to handle matrix and vector operations (hence its name is A Portmanteau of Matrix and Laboratory), and has some particularly efficient and effective inbuilt commands to enable the easy manipulation of matrices and vectors, and very straightforward solutions of linear systems (and hence of nonlinear systems). The aim of this unit is to show you how to use the inbuilt functionality to manipulate vectors and matrices and to solve the linear system Ax=b. More importantly, you will see which methods are appropriate in which situation.

Unit 5: Solving ODEs in MATLAB

Systems of Ordinary Differential Equations (ODEs) are used to model many physical and biological systems. MATLAB contains a collection of ODE solvers, which are ideal for investigating such systems. The aim of this unit is to enable you to understand and use these solvers. In addition you will see how to tell which solver is appropriate in which situation.

Unit 6: Software engineering and scientific computing

This unit contains exercises designed to show you how to produce well-structured and efficient code. It is also important to be able to represent the results of your work in the best possible way. In this unit you will therefore also learn how to construct a simple Graphical User Interface (GUI) for your code and how to produce movies in MATLAB to present your results.






This course has pre-course materials needed for reference in the session which can be accessed in the 'My Resources' section of the CoSY booking system. You can find the 'My Resources' section on the CoSY dashboard (landing page).

For the interactive session, you will be sent the link in the automated communication along with joining instructions. To join the session, you can click on the link 15 minutes before the session. Once the tutor has started the session they will tell you what to do. 


A good internet connection, uninterrupted time, camera and microphone enabled on your PC.


It is now a requirement that you complete the three short questions in the survey you receive after attending the course. Once you have submitted the survey, you will be sent an email with a link to your attendance certificate. This is to ensure we receive the feedback we need to evaluate and improve our courses. Survey results are downloaded and stored anonymously.


Where there is no cost in the shopping trolley, no deposit is required. However, two or more non-attendances or late cancellations without good reason will be logged and may mean you cannot attend any further MSD training that term. Please refer to our Terms and Conditions for further information.