Build self-driving cars with Genetic Algorithms from scratch

Self-driving car experiments go back to 1939. But it took until the 1980’s when universities started to create true, autonomous cars. In Munich, a driverless Mercedes-Benz was going a whopping 130KM/H in 1984!

That is 81 miles per hour. And without crashing! The project received an astronomical funding of 749,000,000 Euros.

These days, you don’t need such budgets for artificial intelligence. All you need is a computer with Python on it! But where to start to build the AI for self-driving cars?

In this course you learn to build Neural Networks and Genetic Algorithms from the ground up. Without frameworks that hide all the interesting stuff in a black box, you are going to build a program that trains self-driving cars.

You will learn and assemble all the required building blocks and will be amazed that in no time cars are learning to drive autonomously. There is only one way to learn AI and that is to just pick a project and start building. That is what you are going to do in this course!

Target audience

Developers who especially benefit from this course, are:

• developers who want to use their basic Python skills to program self-driving cars.

• developers who want to understand Neural Networks and Genetic Algorithms by building them from the ground up.

Challenges

Artificial Intelligence is a black box to many developers. The problem is that many AI frameworks hide the detailsyou need to understand how all the individual components work. The solution is to build things from the ground up and learn to create and combine genetic operators and what properties you can change to optimize the result. This course starts with an empty script and shows you every step that is needed to create autonomous cars that learn how to drive on tracks. Once you have seen the building blocks of a Genetic Algorithm, you can use them in your future projects!

What can you do after this course?

• define what problems can be solved with Genetic Algorithms

• build Neural Networks and Genetic Algorithms from the ground up

• take any problem that can be solved with genetic algorithms and solve it by re-using the code you created in this course

Topics

• AI Introduction: Neural Networks and the Genetic Algorithm

• Car mechanics: Creating a window, drawing backgrounds and cars, controlling the car. Understanding track information

• Neural Network: Inputs, outputs, sensors, activation, feed forward

• Genetic Algorithm: Fitness, Chromosomes, Selection, Cross over and Mutation

• Challenges: Slipping cars, Store the car brain, Stay in the middle of the road and Test Drives

Duration

2 hours video time, 6 hours including typing along.

The teacher

This course is taught by Loek van den Ouweland, a senior software engineer with 25 years of professional experience. Loek is the creator of Wunderlist for windows, Microsoft To-do and Mahjong for Windows and loves to teach software engineering.

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Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!