Partial Differential Equations: Comprehensive Course
Partial Differential Equations: Comprehensive Course, available at $59.99, has an average rating of 3.92, with 65 lectures, based on 75 reviews, and has 6202 subscribers.
You will learn about How to use the Fourier Trasforms to tackle the problem of solving PDE's Fourier Transforms in one and multiple dimensions Method of separation of variables to solve the Heat equation (with exercises) Method of separation of variables to solve the Laplace equation in cartesian and polar coordinates (with exercises) How to apply the Fourier Transform to solve 2nd order ODE's as well How to derive the Black Scholes equation in Finance How to derive (and in some cases solve) the Navier-Stokes equations concept of streamlines Mathematical tricks How to derive Heisenberg Uncertainty Principle using concepts of Probability Theory This course is ideal for individuals who are Students who are interested in Physics and in mathematical derivations of concepts or engineers or mathematicians or physicists or data scientists or computer programmers It is particularly useful for Students who are interested in Physics and in mathematical derivations of concepts or engineers or mathematicians or physicists or data scientists or computer programmers.
Enroll now: Partial Differential Equations: Comprehensive Course
Summary
Title: Partial Differential Equations: Comprehensive Course
Price: $59.99
Average Rating: 3.92
Number of Lectures: 65
Number of Published Lectures: 65
Number of Curriculum Items: 65
Number of Published Curriculum Objects: 65
Original Price: €34.99
Quality Status: approved
Status: Live
What You Will Learn
- How to use the Fourier Trasforms to tackle the problem of solving PDE's
- Fourier Transforms in one and multiple dimensions
- Method of separation of variables to solve the Heat equation (with exercises)
- Method of separation of variables to solve the Laplace equation in cartesian and polar coordinates (with exercises)
- How to apply the Fourier Transform to solve 2nd order ODE's as well
- How to derive the Black Scholes equation in Finance
- How to derive (and in some cases solve) the Navier-Stokes equations
- concept of streamlines
- Mathematical tricks
- How to derive Heisenberg Uncertainty Principle using concepts of Probability Theory
Who Should Attend
- Students who are interested in Physics and in mathematical derivations of concepts
- engineers
- mathematicians
- physicists
- data scientists
- computer programmers
Target Audiences
- Students who are interested in Physics and in mathematical derivations of concepts
- engineers
- mathematicians
- physicists
- data scientists
- computer programmers
Solving Partial Differential Equations using the Fourier Transform: A Step-by-Step Guide
Course Description:
This course is designed to provide a comprehensive understanding of how the Fourier Transform can be used as a powerful tool to solve Partial Differential Equations (PDE). The course is divided into three parts, each building on the previous one, and includes bonus sections on the mathematical derivation of the Heisenberg Uncertainty Principle.
Part 1: In this part, we will start with the basics of the Fourier series and derive the Fourier Transform and its inverse. We will then apply these concepts to solve PDE’s using the Fourier Transform. Prerequisites for this section are Calculus and Multivariable Calculus, with a focus on topics related to derivatives, integrals, gradient, Laplacian, and spherical coordinates.
Part 2: This section introduces the heat equation and the Laplace equation in Cartesian and polar coordinates. We will solve exercises with different boundary conditions using the Separation of Variables method. This section is self-contained and independent of the first one, but prior knowledge of ODEs is recommended.
Part 3: This section is dedicated to the Diffusion/Heat equation, where we will derive the equation from physics principles and solve it rigorously. Bonus sections are included on the mathematical derivation of the Heisenberg Uncertainty Principle.
Course Benefits:
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Gain a thorough understanding of the Fourier Transform and its application to solving PDE’s.
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Learn how to apply Separation of Variables method to solve exercises with different boundary conditions.
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Gain insight into the Diffusion/Heat equation and how it can be solved.
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Bonus sections on the Heisenberg Uncertainty Principle provide a deeper understanding of the mathematical principles behind quantum mechanics.
Prerequisites:
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Calculus and Multivariable Calculus with a focus on derivatives, integrals, gradient, Laplacian, and spherical coordinates.
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Prior knowledge of ODEs is recommended.
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Some knowledge of Complex Calculus and residues may be useful.
Who is this course for?
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Students and professionals with a background in Mathematics or Physics looking to gain a deeper understanding of solving PDE’s using the Fourier Transform.
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Those interested in the mathematical principles behind quantum mechanics and the Heisenberg Uncertainty Principle.
Course Curriculum
Chapter 1: Fourier Transform and its inverse
Lecture 1: Fourier series
Lecture 2: Fourier Transforms
Lecture 3: How to interpret improper integrals of sinusoids
Lecture 4: Dirac delta
Lecture 5: Multiple Fourier Transforms
Lecture 6: Why the Dirac delta helps derive the Inverse Fourier Transform
Chapter 2: Solution of a PDE equation
Lecture 1: Gradient and Laplacian: quick summary
Lecture 2: Example of pde
Lecture 3: Solution to the pde part 1
Lecture 4: Solution to the pde part 2
Lecture 5: Solution to the pde part 3
Chapter 3: Some more physics behind the pde
Lecture 1: Physics behind the equation part 1
Lecture 2: Physics behind the equation part 2
Chapter 4: Solving the Diffusion/Heat equation by Fourier Tranform
Lecture 1: Setup of the diffusion problem
Lecture 2: Integral equation satisfied by the function f(x,t)
Lecture 3: Diffusion equation
Lecture 4: Some possible boundary conditions of the diffusion equation
Lecture 5: Solution of the diffusion equation part 1
Lecture 6: Solution of the diffusion equation part 2
Lecture 7: Solution of the diffusion equation part 3
Lecture 8: Solution of the diffusion equation part 4
Chapter 5: 2nd order ODE solved via Fourier Transform
Lecture 1: 2nd order non-homogeneous ODE solved via Fourier Transform
Chapter 6: PDE solved with the method of characteristics
Lecture 1: Non linear first order PDE solved with the method of characteristics
Chapter 7: Heat equation solution via Separation of Variables
Lecture 1: Separation of variables to solve the heat equation (part 1)
Lecture 2: Separation of variables to solve the heat equation (part 2)
Lecture 3: Separation of variables to solve the heat equation (part 3)
Chapter 8: Laplace Equation solved via the method of Separation of Variables
Lecture 1: Laplace Equation in Cartesian Coordinates (exercise)
Lecture 2: Laplace Equation in Polar coordinates (exercise 1)
Lecture 3: Laplace Equation in Polar coordinates (exercise 2)
Lecture 4: Laplace Equation in Polar coordinates (exercise 3)
Lecture 5: Laplace Equation in Polar coordinates (exercise 4)
Lecture 6: Concept of streamlines (with exercise)
Chapter 9: Nonhomogeneous Heat Equation
Lecture 1: Nonhomogeneous Heat Equation: Exercise 1
Lecture 2: Nonhomogeneous Heat Equation: Exercise 2
Lecture 3: Nonhomogeneous Heat Equation: Exercise 3
Chapter 10: Wave Equation (Exercises)
Lecture 1: Nonhomogeneous Wave Equation (Exercise 1)
Lecture 2: Nonhomogeneous Wave Equation: D'Alambert formula
Lecture 3: Solving a wave equation using D'Alambert formula (exercise)
Lecture 4: Energy conservation law for the wave equation
Chapter 11: Bi-dimensional problems (heat and wave equation)
Lecture 1: Bi-dimensional heat equation: exercise 1
Lecture 2: Bi-dimensional heat equation: exercise 2
Lecture 3: Bi-dimensional wave equation: exercise 1
Chapter 12: Black Scholes equation
Lecture 1: Mathematical Derivation of the Black-Scholes equation
Chapter 13: Derivation of the Navier-Stokes equations and their solution in a 2D case
Lecture 1: Mathematical derivation of Navier Stokes equations part 1
Lecture 2: Mathematical derivation of Navier Stokes equations part 2
Chapter 14: How Einstein mastered Navier-Stokes equations in his PhD dissertation
Lecture 1: How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 1
Lecture 2: How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 2
Lecture 3: How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 3
Lecture 4: How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 4
Lecture 5: How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 5
Lecture 6: How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 6
Chapter 15: Stokes law obtained from Navier-Stokes equations
Lecture 1: derivation of Stokes law from Navier Stokes part 1
Lecture 2: derivation of Stokes law from Navier Stokes part 2
Chapter 16: Appendix on PDE's
Lecture 1: Derivation of the incompressible fluid equation
Chapter 17: Bonus section: Introduction to the Heisenberg Uncertainty Principle
Lecture 1: Mathematical summary of how to prove the uncertainty principle
Lecture 2: Introduction to the short course on the Heisenberg Uncertainty Principle
Lecture 3: Probability that a particle exists at a certain time
Lecture 4: Probability that a particle has a certain_energy
Lecture 5: Uncertainty in the localization in time and in the energy of the particle
Chapter 18: Bonus Section: Uncertainty Principle derivation
Lecture 1: Derivation of the uncertainty principle part 1
Lecture 2: Derivation of the uncertainty principle part 2
Lecture 3: Derivation of the uncertainty principle part 3
Chapter 19: Bonus Section: Consequences of the Uncertainty principle
Lecture 1: Probability that particles come into existence with high energy
Lecture 2: Distribution for which we have the minimum uncertainty
Chapter 20: Appendix
Lecture 1: Derivation of some formulas used in previous lectures
Instructors
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Emanuele Pesaresi
PhD in Mechanics and Advanced Engineering Sciences
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 3 votes
- 3 stars: 7 votes
- 4 stars: 23 votes
- 5 stars: 40 votes
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