Intro to Self-Driving Cars

Intro to Self-Driving Cars

Nanodegree key: nd113

Version: 3.0.0

Locale: en-us

Learn the essentials of building a self-driving car, including probability, C++, machine learning, and linear algebra.

Content

Part 01 : Orientation

Welcome to the Intro to Self-Driving Cars Nanodegree program! In this section you'll get a sneak peak of the classroom, meet the team, and learn about the services provided. Then you'll take a readiness assessment and check out some learning resources to help you make the most out of your experience.

Part 02 : Bayesian Thinking

Learn the framework that underlies a self-driving car’s understanding of itself and the world around it, and to see the world the way a self-driving car does.

Part 03 : Working with Matrices

This course will focus on two tools which are vital to self-driving car engineers: object oriented programming and linear algebra.

Part 04 : C++ Basics

This course is the first step in a rewarding journey towards C++ expertise. The goal is translation: get a program written in Python, and translate it into C++.

Part 05 : Performance Programming in C++

Explore how to write good code that runs correctly. We’ll focus primarily on low level features of C++, but we’ll discuss other best practices as well.

Part 06 : Navigating Data Structures

Algorithmic thinking is a skill you’ll refine throughout your career. In this course you’ll focus on frequently used data structures and algorithms.

Part 07 : Career Services

These Career Services will ensure you make meaningful connections with industry professionals to accelerate your career growth - whether looking for a job or opportunities to collaborate with your peers. Unlike your Nanodegree projects, you do not need to meet specifications on these Services to progress in your program. Submit these Career Services once, and get honest, personalized feedback and next steps from Udacity Career Coaches!

Part 08 : Vehicle Motion and Control

This course is a crash course in two branches of mathematics which are crucial to self driving cars: calculus and trigonometry. You will learn how a self driving car uses various motion sensors to help it understand its own motion.

At the end of this course you will use raw sensor data (which give information about distance driven, acceleration, and rotation rates) to reconstruct a vehicle's trajectory through space.

Part 09 : Computer Vision and Machine Learning

In this course you’ll learn how a computer sees an image, and how we can use machine learning to teach a computer to identify images programmatically.

Part 10 : Graduation!

Congratulations! You're ready to graduate. Learn how you can continue your Udacity journey by enrolling in a Career-Ready Nanodegree Program