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Computational Physics: Scientific Programming with Python
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[Bild: computationalphysicsscajws.jpg]

Computational Physics: Scientific Programming with Python
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 181 lectures (20h 51m) | Size: 5.7 GB

From numerical methods to exciting applications: Differential equations, eigenvalue problems, Monte Carlo methods & more


What you'll learn
Getting Started: A beginner-friendly crash course about NumPy, functions, loops, conditionals, lists, arrays & plots
Numerical 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
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.
Description
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.
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
Why 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. I have used the program for the results in many of my publications and have recommended Python to all of my students.
I hope you are excited and I kindly welcome you to our course!
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
... or who want to prepare for their computational physics exam ;-)


[Bild: computationalphysicss9hkyq.jpg]

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