From this page you can download three useful documents to help you get started with computing in the School of Mathematics and Statistics.  More detailed information on the computing component of each course will be posted on Moodle.

Lab information

The Computing Laboratories Information for Students (PDF) provides an overview of the workings of the computer labs in the School of Mathematics and Statistics.

Maple-based courses

The First year maple notes (PDF) will help you become familiar with the Maple package. Maple lab consultants are another source of help.

MATLAB-based courses (e.g. Maths for Actuarial Studies and Finance)

This Introduction to Matlab (PDF) will help you become familiar with Matlab. There are also some self-paced Matlab lessons which can be accessed online.

Obtaining copies of Maple or Matlab

It is not necessary for students to buy their own copy of Maple or Matlab, as these packages are available on all computers in the School of Mathematics and Statistics labs or remotely via myAccess.

For advice on ontaining mathematical or statistical software that will be useful in your course see the Obtaining software page.

The Python programming language

These 10 Python lessons from Bill McLean will help you become familar with Python.

The Julia programming language

Bill McLean's 10 Julia lessons and Gary Froyland's  Quick-start guide to Julia will help you to begin using Julia. Further mathematical topics are illustrated in the following Pluto notebooks:

A sample Pluto notebook

Multivariable continuous optimization

An interactive pendulum

Multivariate root finding

Fitting and sampling statistical distributions

Numerical integration

Examples of some dynamical systems in Julia