Build self-driving cars with Genetic Algorithms from scratch

Build self-driving cars with Genetic Algorithms from scratch, available at $19.99, has an average rating of 4.95, with 27 lectures, based on 21 reviews, and has 216 subscribers.

You will learn about Create a Neural Network that translates car sensors to car controls Train a Neural Network with a Genetic Algorithm Combine Genetic Operators like Select, Cross over and Mutation Create a window and draw backgrounds and cars with Pyglet Build a car simulation to evolve car brains Choose and build a suitable fitness function This course is ideal for individuals who are developers who want to use their basic Python skills to program self-driving cars or developers who want to understand Neural Networks and Genetic Algorithms by building them from the ground up It is particularly useful for developers who want to use their basic Python skills to program self-driving cars or developers who want to understand Neural Networks and Genetic Algorithms by building them from the ground up.

Enroll now: Build self-driving cars with Genetic Algorithms from scratch

Summary

Title: Build self-driving cars with Genetic Algorithms from scratch

Price: $19.99

Average Rating: 4.95

Number of Lectures: 27

Number of Published Lectures: 27

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: $34.99

Quality Status: approved

Status: Live

What You Will Learn

Create a Neural Network that translates car sensors to car controls

Train a Neural Network with a Genetic Algorithm

Combine Genetic Operators like Select, Cross over and Mutation

Create a window and draw backgrounds and cars with Pyglet

Build a car simulation to evolve car brains

Choose and build a suitable fitness function

Who Should Attend

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

Target Audiences

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

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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Introduction

Chapter 2: AI Introduction

Lecture 1: Neural Network and Genetic Algorithm

Chapter 3: Car Mechanics

Lecture 1: Parking Lot

Lecture 2: Keyboard Control

Lecture 3: Track Binary Matrix

Lecture 4: Rounds

Lecture 5: Heads Up Display

Chapter 4: Neural Network

Lecture 1: First Track

Lecture 2: Network

Lecture 3: Car Sensors

Lecture 4: Checkpoints

Lecture 5: Second Track

Chapter 5: Genetic Algorithm

Lecture 1: The Genetic Algorithm

Lecture 2: Fitness Function

Lecture 3: Separate Neural Network from the Genetic Algorithm

Lecture 4: Selection

Lecture 5: Cross Over

Lecture 6: Mutation

Lecture 7: Tweaking the System

Chapter 6: Challenges

Lecture 1: Slipping Cars

Lecture 2: Store and retrieve Car Brains

Lecture 3: Test Drive

Lecture 4: Edge Distance

Lecture 5: Final Test

Chapter 7: Conclusion

Lecture 1: QA #1: What more can be done with genetic algorithms? A mini project.

Lecture 2: Course Conclusion

Lecture 3: Bonus Chapter

Instructors

Loek van den Ouweland
Passionate Python Teacher

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4 stars: 5 votes

5 stars: 16 votes

Frequently Asked Questions

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