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.
Play Trailer Play TrailerDifferential Equations in Action
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.
Course Leads
-
Jörn Loviscach
Instructor
-
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
Udacity 现已提供中文版本！ A Udacity tem uma página em português para você! There's a local version of Udacity for you! Sprechen Sie Deutsch?
Besuchen Sie de.udacity.com und entdecken Sie lokale Angebote, unsere Partnerunternehmen und Udacitys deutschsprachigen Blog.
Zu de.udacity.com
continue in English