Udemy – Computational Physics: Scientific Programming with Python 2021-1

Published on: 2023-06-27 03:00:06

Categories: 28

Descriptions

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 fitting, Derivatives & Integrals, Differential equations, Eigenvalue problems, Monte Carlo methods to solve problems from all areas of physics.

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. I have used the program for the results in many of my publications and have recommended Python to all of my students. 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 as

Calculating 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 more

What you’ll learn

Getting Started: A beginner-friendly crash course about NumPy, functions, loops, conditionals, lists, arrays & plotsNumerical
methods: Derivatives & integrals, differential equations & eigenvalue problems, interpolation & Monte Carlo methods
Practice at Physics Problems: Moment of inertia, magnetic field of a wire, radioactive decay, harmonic oscillators, free fall, rolling balls
Application to Advanced Problems: Chaotic systems, heat equation, 3-body problem, spaceship mission, coupled pendulums, magnetism, graphene & quantum physics

Who this course is for

This course is for everyone: Python beginners & advanced programmers
Everyone who likes physics and/or programming
Science students, who want to explore a modern field of physics
who want to prepare for their computational physics exam

Specificatoin of Computational Physics: Scientific Programming with Python

Publisher : Udemy
Teacher : Börge Göbel
Language : English
Level : All Levels
Number of Course : 181
Duration : 20 hours and 51 minutes

Content on 2/2023

Computational Physics: Scientific Programming with Python

Requirements

Software: None, I will show you how to install Python which is free.
Programming: Previous experience is helpful but not required. We start with a 2h crash course.
School mathematics: Knowing the basics about derivatives & integrals.Physics: Helpful but not required.