Computational Physics: Scientific Programming with Python

This course is for everyone who wants to learn and get better in Python and physics. Except for some school mathematics, no prior knowledge is required. We will start from the basics and climb the ladder up to advanced projects.

Python is an enormously powerful tool and widely used in theoretical and computational physics. It is not difficult to use but the whole topic can be overwhelming to learn if you are on your own. In computational physics we use numerical techniques from mathematics, such as:Interpolation & Model fittingDerivatives & IntegralsDifferential equationsEigenvalue problemsMonte Carlo methodsto solve problems from all areas of physics.

You are kindly invited to join this carefully prepared course that will teach you all you need to know about Python for scientific programming. It includes a crash course, quizzes, exercises, solutions and, of course, hands-on programming sessions in which we will solve real-life examples, such asCalculating the magnetic field of a charged wire (integrals & derivatives)Chaos & the butterfly effect (differential equations)Heat propagation in a sample (differential equations)Simulating (and navigating) a spaceship interacting with sun, earth and moon (differential equations)The strange behavior of coupled oscillators (Eigenvalue problems, Fourier analysis & fitting procedure)Ferromagnets & Antiferromagnets (Monte Carlo methods)Special properties of graphene (Advanced science lecture about the Nobel prize winning material). & many moreWhy me.

My name is Börge Göbel and I am a postdoc working as a scientist in theoretical physics. I have refined my advisor skills as a tutor of Bachelor, Master and PhD students in theoretical physics and have other successful courses here on Udemy. Especially when I started my PhD, I was impressed how easily you can solve demanding tasks with Python.