Differential Equations in Action (Udacity)

Offered by Udacity,
Differential Equations in Action (Udacity)

Making Math Matter. 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.

Class Deals by MOOC List - Click here and see Udacity's Active Discounts, Deals, and Promo Codes.

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 You Will Learn

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 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 5
Antilock Brake Systems

  • Friction
  • equilibria
  • and control theory.

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.

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!

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Mathematical Thinking (Coursera) Coursera
Stanford University

Introduction to Mathematical Thinking (Coursera)

Learn how to think the way mathematicians do - a powerful cognitive process developed over thousands of years. Mathematical thinking is not the same as doing mathematics – at least not as mathematics is typically presented in our school system. School math typically focuses on learning procedures to solve highly stereotyped problems. Professional mathematicians think a certain way to solve real problems, problems that can arise from the everyday world, or from science, or from within mathematics itself.

Nov 30th 2026
5-12 Weeks
Computability, Complexity & Algorithms (Udacity) Udacity
Georgia Institute of Technology,Udacity

Computability, Complexity & Algorithms (Udacity)

The Power and Limitation of Algorithms. In this course, we will ask the big questions, "What is a computer? What are the limits of computation? Are there problems that no computer will ever solve? Are there problems that can’t be solved quickly? What kinds of problems can we solve efficiently and how do we go about developing these algorithms?" Understanding the power and limitations of algorithms helps us develop the tools to make real-world computers smarter, faster and safer.

Self Paced
Self-Paced
An Introduction to Interactive Programming in Python (Part 2) (Coursera) Coursera
Rice University

An Introduction to Interactive Programming in Python (Part 2) (Coursera)

This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple.

Nov 30th 2026
4 Weeks
Data Structures & Algorithms in Swift (Udacity) Udacity
Udacity

Data Structures & Algorithms in Swift (Udacity)

Confidently take on the tech interview. Technical interviews follow a pattern. If you know the pattern, you’ll be a step ahead of the competition. This course will introduce you to common data structures and algorithms in Swift. You'll review frequently-asked technical interview questions and learn how to structure your responses. You will answer practice problems and quizzes to test your abilities. Then you'll practice mock interviews to get specific recommendations for improvement. Be ready for anything the technical interviewer throws at you.

Self Paced
Self-Paced
Principles of Computing (Part 2) (Coursera) Coursera
Rice University

Principles of Computing (Part 2) (Coursera)

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language. The main focus of the class will be weekly mini-projects that build upon the mathematical and programming principles that are taught in the class.

Nov 30th 2026
4 Weeks
High Performance Computing (Udacity) Udacity
Georgia Institute of Technology,Udacity

High Performance Computing (Udacity)

The goal of this course is to give you solid foundations for developing, analyzing, and implementing parallel and locality-efficient algorithms. This course focuses on theoretical underpinnings. To give a practical feeling for how algorithms map to and behave on real systems, we will supplement algorithmic theory with hands-on exercises on modern HPC systems, such as Cilk Plus or OpenMP on shared memory nodes, CUDA for graphics co-processors (GPUs), and MPI and PGAS models for distributed memory systems.

Self Paced
Self-Paced
Analytic Combinatorics (Coursera) Coursera
Princeton University

Analytic Combinatorics (Coursera)

Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations. All the features of this course are available for free. It does not offer a certificate upon completion.

Nov 30th 2026
5-12 Weeks
Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera) Coursera
Duke University

Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera)

In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space.

Nov 30th 2026
5-12 Weeks