ARCHER, the UK's national supercomputing service, offers training in software development and high-performance computing to scientists and researchers throughout the UK. As part of our training service we will be running a 2 day 'Introduction of Scientific Programming with Python' training session.
This course is aimed at programmers with little or no Python knowledge seeking to learn how to use Python for scientific computing. We will introduce Python's fundamental scientific libraries numpy, scipy and matplotlib. We will also introduce how to interface Python with Fortran and C codes, along with parallel programming methods including MPI via mpi4py.
This course is free to all academics.
Kevin has a background in computational physics and joined EPCC in 2001. He teaches on courses including 'Scientific Programming with Python' and 'GPU Programming with CUDA'.
Juan Rodriguez Herrera
Juan is involved in teaching ARCHER courses related to HPC, MPI, and Python, among others. He's a certified instructor of Software and Data Carpentry workshops. He also supervises EPCC's MSc dissertation projects.
The course will be delivered over two days in person. The course will interleave many practical exercises with short lectures and discussions.
To attend, you must have some experience of writing code and/or scripts and be familiar with programming concepts including conditionals, loops, arrays and functions. You should also have some basic knowledge of the Python language. For an introduction to Python, please see Code Academy's Python tutorial: https://www.codecademy.com/tracks/python
You should also be comfortable with using the bash shell. For an introduction to the shell, please see, for example Software Carpentry's lessons on Unix Shell: https://swcarpentry.github.io/shell-novice/
We recommend you download, before the course, Anaconda python Version 3.6 from https://www.anaconda.com/download/ (version 2.7 will work at a stretch). This has the packages required (and more).
Slides and exercise material for this course.