Explanation
Computational Physics: Scientific Programming in Python This course is for anyone who wants to learn and become proficient in Python and physics. Except for some school math, no previous knowledge is required. We’ll start with the basics and work our way up the ladder to advanced projects! Python is a powerful tool widely used in physics and computing. It is not difficult to use but the whole topic can be difficult to learn if you are alone. In computational physics we use numerical techniques in mathematics, such as: Interpolation & Model fitting, Derivatives & Integrals, differential equations, Eigenvalue problems, Monte Carlo methods to solve problems in all areas of physics.
My name is Börge Göbel and I am a postdoc working as a scientist in theoretical physics. I have improved my mentor skills as a teacher of Bachelor, Master and PhD students in theoretical physics and I have other successful courses here on Udemy. Especially when I started my PhD, I was impressed by how easily you can solve demanding tasks in Python. I have used the program for many of my publications and recommend Python to all 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, questions, exercises, solutions and, of course, hands-on programming sessions where we will solve real-life examples, such as
- Calculation of the magnetic field of a charged wire
- Chaos & butterfly effect (differential equations)
- Thermal diffusivity of a sample (differential equations)
- Simulation (and flow) of a spaceship interacting with the sun, earth and moon (differential equations)
- Phenomenal behavior of coupled oscillators (Eigenvalue problems, Fourier analysis & fitting method)
- Ferromagnets & Antiferromagnets (Monte Carlo methods)
- Special properties of graphene (a scientific lecture on materials by a Nobel Prize winner)
- … & many more
What will you learn?
- Getting Started: A beginner-friendly crash course on NumPy, functions, loops, conditionals, lists, arrays & numerical schemes.
- Methods: Derivatives & integrals, differential equations & eigen value problems, interpolation & Monte Carlo methods
- Practice Physics Problems: Momentum, magnetic field in a wire, radial decay, harmonic oscillators, free fall, rolling balls
- Application of advanced problems: Chaotic systems, heat equation, 3-year problem, space mission, coupled pendulums, magnetism, graphene & quantum physics
Who is this course for?
- This course is for everyone: Python beginners and advanced programmers
- Anyone who likes physics and/or programming
- Science students, who want to explore the field of modern physics
- who want to prepare for their physics calculus exam
Specialties in Computational Physics: Scientific Programming in Python
- Publisher: Udemy
- Teacher: Borge Gobel
- Language : English
- Level : All Levels
- Number of courses: 181
- Duration: 20 hours and 51 minutes
Content 2/2023
Requirements
- Software: No, I will show you how to install Python for free.
- Programming: Previous experience is helpful but not required. We start with a 2 hour crash course.
- School math: Knowing the basics about fundamentals & combinations.
Pictures
Sample Clip
Installation Guide
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Subtitle : English
Quality: 720p
Download Links
Password file: free download software
file size
5.9GB