Topics covered

Python is a nice programming language for scientific programming. Many high quality libraries are available as building block in a wide variety of  scientific domains. In this training we will concentrate on the core libraries, and give some examples of domain specific libraries.

Subject and Python modules that will be covered:

• multi-dimensional arrrays and algorithms on these data structures: numpy
• methods & algorithms useful for scientific programming, e.g., linear algebra, Fourier transforms, statistics, optimization, root finding, signal processing: scipy
• symbolic computing: sympy
• creating many types of plots: matplotlib
• portable file formats for scientific data: e.g., HDF5
• image processing: scikit-image

Previous knowledge

Experience in Python programming.