Study 10 hrs/week and complete in 4 mo.
Classroom opens in 21 days.
Students should have some experience with programming—writing short scripts in a programming language—and be comfortable with algebra. You should also feel comfortable reading and modifying code that you are given, with the understanding that solving problems in code may still be challenging. If you believe you need more preparation, here are some additional resources you can use:
Sebastian Thrun and the Udacity Self-Driving Car team are pioneering educators in this field, and Udacity offers the only program of its kind, where you can learn to be a self-driving car engineer.
You’ll never be without support and guidance as you advance through your program. Live Help will keep you connected in the classroom, reviewers will give you actionable feedback on your projects, and you’ll be part of an engaged and supportive peer community.
Anyone with minimal programming experience can learn the essentials of building a self-driving car. You will learn how to solve problems in both Python and C++ as you discover what makes self-driving cars possible.
Graduates of this program will earn guaranteed admission into our Self-Driving Car Engineer Nanodegree program. This is a complete path to a self-driving car career.
Sebastian Thrun is a scientist, educator, inventor, and entrepreneur. As the founder and president of Udacity, Sebastian’s mission is to democratize education by providing lifelong learning to millions of students worldwide.
Andy has a bachelor's degree in physics from MIT, and taught himself to program after college (mostly with Udacity courses). He has been helping Udacity make incredible educational experiences since the early days of the company.
Cezanne is an expert in computer vision with an M.S. in Electrical Engineering from Stanford University. Inspired by anyone with the drive and imagination to learn something new, she aims to create more inclusive and effective STEM education.
As an engineer, Andrew is excited to teach the technology of the future. With an engineering degree from Yale and years of tutoring experience, he strives to provide the most fulfilling learning experiences possible.
Anthony is a US Army combat veteran with an M.S. in Computer Engineering from Colorado State University. He is the Product Lead at Udacity for the Robotics and Self-Driving Car Engineer Nanodegree programs.
Engineer, Author, Host
Elecia is an embedded software engineer at Logical Elegance, Inc, the author of O’Reilly’s Making Embedded Systems, and host of the Embedded.fm podcast. She enjoys sharing her enthusiasm for engineering and devices.
Voyage, Director of AI
As the Director of Artificial Intelligence at Voyage Auto, Tarin works to deliver low-cost, self-driving taxis. He brings a total of 14 years experience in perception and deep neural networks working with companies such as Apple.
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You should be comfortable reading and modifying code. You should also be comfortable with basic algebra. See detailed requirements.
This course will focus on two tools which are vital to self-driving car engineers: object oriented programming and linear algebra.Implement a Matrix Class
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++.Translate Python to 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.Performant C++
Algorithmic thinking is a skill you’ll refine throughout your career. In this course you’ll focus on frequently used data structures and algorithms.Planning an Optimal Path
In this course you’ll learn basic calculus—the mathematics of continuity. You’ll also learn to use some of Python’s most popular visualization libraries.Trajectory Visualizer
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.Image Classifier from Scratch
Learn the essentials of building a self-driving car, including probability, C++, machine learning, and linear algebra.
Self-driving cars are the future of smart transportation, and this introductory program is the perfect way to start your journey to a self-driving car career! This program enables anyone with minimal programming experience to learn the essentials of programming a self-driving car, from machine learning to object-oriented programming to probabilistic robotics. You will learn how to solve problems in both Python and C++ as you discover what makes self-driving cars possible. Best of all, graduates earn guaranteed admission into our career-ready Self-Driving Car Engineer Nanodegree program!
A self-driving car can’t afford to waste any cycles or memory unnecessarily. In this project you’ll take some functioning (but inefficient) C++ code and optimize it.
Jump into writing code that controls a simulated vehicle. Send throttle and steering commands to the car to get it to navigate around a test track.
You turn on your self-driving car, buckle up, and enter a destination. Navigating from A → B is not an easy problem. In this project you’ll use your knowledge of data structures (in particular, graph data structures) and search algorithms to write an algorithm which uses a map and traffic information to find the quickest route between two points.
In this project you’ll build an image classifier from scratch. When you’re done you’ll have an algorithm that can reliably classify an image as “pedestrian” or “car.”
In this project you’ll apply your knowledge of C++ syntax by translating the Histogram Filter code from the first course into C++.
As a self-driving car engineer, a lot of the code you write involves simulation, visualization, testing, and debugging. In this project you’ll write a visualization tool that will let you visualize the continuous trajectories that come from various search and control algorithms.
In this project you’ll practice using your object oriented programming and matrix math skills by filling out the methods in a partially-completed `Matrix` class.
In this project, you will write the `sense` and `move` functions for a 2-dimensional histogram filter in Python.
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