Scientific Python


One day (usually 0930 to 1600)


Research postgraduate students and above; teaching and lecturing staff.

Course Content

This workshop is aimed at people who want to learn how to use Python for Scientific Computing tasks.

The workshop will give an introduction to Python’s main Scientific libraries (Scipy, Numpy and Matplotlib) and will also cover how to link existing C and Fortran codes and subroutines within your Python code. All exercises will use Python 3.

This would be an ideal course to attend before ‘High Performance Python’.

This hands-on workshop will cover:

  • A recap on Python data types
  • Numpy: arrays, matrices and linear algebra
  • Numpy: random numbers
  • Numpy: Fourier transforms and polynomials
  • Scipy: Linear Algebra and wrappers to LAPACK & BLAS
  • Scipy: Numerical Integration
  • Scipy: Interpolation
  • Scipy: Optimisation
  • Scipy: Special functions
  • Matplotlib: interactive and non-interactive plotting
  • Matplotlib: producing publication-quality figures
  • Matplotlib: creating diagrams
  • Interfacing to C and Fortran


This workshop is aimed at people who can already program in Python at an intermediate level (with a knowledge of loops, functions and ‘if’ statements).


This course is booked through the IT Training Unit