Self Driving Simulations- Develop Autonomous Car with Python

Self Driving Simulations: Develop Autonomous Car with Python, available at $64.99, has an average rating of 4.3, with 30 lectures, based on 15 reviews, and has 3064 subscribers.

You will learn about Learning the fundamental concepts of self driving autonomous car, getting to know technologies behind it, as well as its capabilities and limitations Learning and understanding how self driving feature in autonomous car works Building self driving autonomous car simulation project using PyGame and NEAT from scratch Testing the self driving autonomous cars to ensures the car has a good decision making ability, solid sensor integrations, and effective collision prevention This course is ideal for individuals who are People who are interested to build self driving autonomous car simulation with Python or People who are interested to learn about the basic concepts of autonomous car It is particularly useful for People who are interested to build self driving autonomous car simulation with Python or People who are interested to learn about the basic concepts of autonomous car.

Enroll now: Self Driving Simulations: Develop Autonomous Car with Python

Summary

Title: Self Driving Simulations: Develop Autonomous Car with Python

Price: $64.99

Average Rating: 4.3

Number of Lectures: 30

Number of Published Lectures: 30

Number of Curriculum Items: 30

Number of Published Curriculum Objects: 30

Original Price: $24.99

Quality Status: approved

Status: Live

What You Will Learn

Learning the fundamental concepts of self driving autonomous car, getting to know technologies behind it, as well as its capabilities and limitations

Learning and understanding how self driving feature in autonomous car works

Building self driving autonomous car simulation project using PyGame and NEAT from scratch

Testing the self driving autonomous cars to ensures the car has a good decision making ability, solid sensor integrations, and effective collision prevention

Who Should Attend

People who are interested to build self driving autonomous car simulation with Python

People who are interested to learn about the basic concepts of autonomous car

Target Audiences

People who are interested to build self driving autonomous car simulation with Python

People who are interested to learn about the basic concepts of autonomous car

Welcome to Self-Driving Simulations: Developing Autonomous Cars with Python course. This is basically an extensive project based course where you will be fully guided step by step on how to build autonomous vehicle simulation with self driving feature using Python programming language alongside with Python libraries, such as Pygame and NEAT where Pygame will be utilised to create a visual and realistic representation of the simulated environment while NEAT which stands for NeuroEvolution of Augmenting Topologies will be used to train the neural networks to control and design self driving behaviour. The neural network takes input from the car’s sensors. In addition, the neural network will also learn and adapt over time through evolutionary algorithms, improving the car’s driving performance and decision-making skills. In the introduction session, you will be learning the basic fundamentals of autonomous car, getting to know technologies behind it as well as understanding how it works. Then, after learning the basic concepts, you will be guided step by step to set up all necessary tools, for instance Visual Studio Code IDE, installing Python, and other relevant tools. Before getting into the project, there will be a basic python training session where you will learn all important concepts in Python that you need to know and master to prepare you for the upcoming project. The basic Python training session is optional since the session was created and intended only for those who are not very confident with their Python programming skills. In the basic Python training session, you will learn different data types or variables, how to build functions and pass down parameters to the function, how to build class, and basic fundamentals of Pygame. Then, once the basic Python training session has been completed, you will move to the project where you will be fully guided step by step on how to build an autonomous car simulation with advanced self driving features from scratch. Once the project has been built, we are going to be conducting testing, not only to test if the code works but also to test if the output of the code is what we expected to get. There will be three main objectives that will be tested, those are the car’s decision making ability, sensor integration, and collision prevention.

First of all, we need to ask ourselves this question. Why should we learn how to build an autonomous car simulator? It might be very interesting to learn how the self-driving feature in cars like Tesla works, obviously the system is very complicated and a bit difficult to be understood but what if you have a chance to learn the self driving mechanism from a more simple perspective and that’s exactly what you are going to learn in this course. The next follow up question might potentially be, well it is near impossible and definitely unrealistic to create my own real autonomous vehicle like Tesla, it will cost you a lot and even if you have the funding, you might not have the right skill sets and knowledge to begin with. That is actually true to some extent, we are not going to build a brand new car with self -driving features, instead, we can potentially build a very cool self-driving game or maybe build an autonomous object simulator.

Below are things that we are going to learn from this course:

Learning the fundamental concepts of self driving autonomous car, getting to know technologies behind it, as well as its capabilities and limitations

Learning and understanding how autonomous car works

Basic Python training session which prepares you better for the autonomous car project

Building self driving autonomous car simulation project using Pygame and NEAT

Learning how to build and design car track using GIMP painting tool

Testing the self driving autonomous cars to ensures the car has a good decision making ability, solid sensor integrations, and effective collision prevention system

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to the Course

Lecture 2: Highlight of the Course

Lecture 3: Whom This Course is Intended for?

Chapter 2: Tools, IDE, and Libraries

Lecture 1: Tools, IDE, and Libraries

Chapter 3: Introduction to Autonomous Cars

Lecture 1: Introduction to Autonomous Cars

Lecture 2: How Autonomous Car Works?

Chapter 4: Setting Up All Required Tools

Lecture 1: Installing Visual Studio Code

Lecture 2: Installing Python & Adding Extension to VS Code

Lecture 3: Installing PyGame & NEAT

Chapter 5: Basic Python Training Session

Lecture 1: Basic Python Training Session

Lecture 2: Data Types Practice

Lecture 3: Function & Parameters Practice

Lecture 4: Class & Objects Practice

Lecture 5: Basics of PyGame

Chapter 6: Preparing Assets for Autonomous Car Simulation

Lecture 1: Preparing Car Objects for Simulation

Lecture 2: Downloading GIMP

Lecture 3: Building Car Track with GIMP

Chapter 7: Building Self Driving Autonomous Car Project

Lecture 1: Creating Folder for the Project

Lecture 2: NEAT Configuration File Explained

Lecture 3: Create Function to Initialise the Simulation

Lecture 4: Functions to Set Position & Avoid Collision

Lecture 5: Function to Detect Obstacles

Lecture 6: Function to Update Position

Lecture 7: Functions to Get Radars Data & Calculate Fitness Score

Lecture 8: Function to Run Autonomous Car

Lecture 9: Autonomous Car Function Explained

Lecture 10: Function to Run Simulation

Chapter 8: Testing Autonomous Car Simulation

Lecture 1: Autonomous Car Testing Objectives

Lecture 2: Testing Self Driving Autonomous Car Project

Chapter 9: Conclusion & Summary

Lecture 1: Conclusion & Summary

Instructors

Christ Raharja
Ex Technology Risk Consultant, and E-commerce enthusiast

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5 stars: 8 votes

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