Computational Physics: Scientific Programming with Python
Computational Physics: Scientific Programming with Python Udemy Course
From numerical methods to exciting applications: Differential equations, eigenvalue problems, Monte Carlo methods & more
This Computational Physics: Scientific Programming with Python 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. 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.
What you’ll learn in Computational Physics: Scientific Programming with Python Course
- 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.
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