About this Course

In this course, you'll hone your problem-solving skills through learning to find numerical solutions to systems of differential equations. You'll write code in Python to fight forest fires, rescue the Apollo 13 astronauts, stop the spread of epidemics, and resolve other real-world dilemmas.

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Course Cost
Free
Timeline
Approx. 2 months
Skill Level
Intermediate
Included in Course
  • Rich Learning Content

  • Interactive Quizzes

  • Taught by Industry Pros

  • Self-Paced Learning

  • Student Support Community

Join the Path to Greatness

This free course is your first step towards a new career with the Machine Learning Engineer Nanodegree Program.

Free Course

Differential Equations in Action

Enhance your skill set and boost your hirability through innovative, independent learning.

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Course Leads

  • Jörn Loviscach
    Jörn Loviscach

    Instructor

  • Miriam Swords Kalk
    Miriam Swords Kalk

    Instructor

What You Will Learn

Lesson 1

Rescuing Apollo 13, Part 1

  • Introduction to the Forward Euler Method.
Lesson 1

Rescuing Apollo 13, Part 1

  • Introduction to the Forward Euler Method.
Lesson 2

Rescuing Apollo 13, Part 2

  • Comparing solvers, Heun's Method.
  • Symplectic Euler Method.
Lesson 2

Rescuing Apollo 13, Part 2

  • Comparing solvers, Heun's Method.
  • Symplectic Euler Method.
Lesson 3

Analyzing the Spread of Diseases

  • Implicit methods and stiffness.
Lesson 3

Analyzing the Spread of Diseases

  • Implicit methods and stiffness.
Lesson 4

There's Plenty of Fish in the Sea?

  • Stability, sensitivity, and optimization.
Lesson 4

There's Plenty of Fish in the Sea?

  • Stability, sensitivity, and optimization.
Lesson 5

Antilock Brake Systems

  • Friction, equilibria, and control theory.
Lesson 5

Antilock Brake Systems

  • Friction, equilibria, and control theory.
Lesson 6

The Path of a Forest Fire

  • Partial differential equations and heat conduction.
Lesson 6

The Path of a Forest Fire

  • Partial differential equations and heat conduction.
Lesson 7

Advanced Applications of Numerical Methods

  • Chaos, software, and predictive capability.
Lesson 7

Advanced Applications of Numerical Methods

  • Chaos, software, and predictive capability.

Prerequisites and Requirements

You'll need a basic knowledge of programming in Python for this course, around the level of Intro to Computer Science. An understanding of Python packages, as discussed in Programming Foundations with Python, will also be helpful.

In addition, you'll need to feel comfortable with trigonometry at the high school level, as well as basic vector algebra. This class will primarily involve solving differential equations numerically rather than analytically, but some exposure to calculus and physics at the level of Intro to Physics wouldn't hurt.

Most of all, bring with you a love of learning and problem solving!

See the Technology Requirements for using Udacity.

Why Take This Course

By the end of this course, you'll develop an intuition for the use of differential equations in the applied sciences. You'll also learn how to build mathematical models for systems of differential equations using a variety of techniques. Along the way, you'll learn how to translate mathematical expressions into Python code and solve some really cool problems!

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals
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