At 15 hrs/week
Get access to classroom immediately on enrollment
Students should have experience with Python, C++, Linear Algebra, and Calculus. See detailed requirements.
Learn about how self-driving cars work and about the services available to you as part of the Nanodegree program.
Use a combination of cameras and software to find lane lines on difficult roads and to track vehicles.Finding Lane Lines on the RoadAdvanced Lane Finding
Deep learning has become the most important frontier in both machine learning and autonomous vehicle development. Experts from NVIDIA will teach you to build deep neural networks and train them with data from the real world and from the Udacity simulator. You’ll train convolutional neural networks to classify traffic signs, and then train a neural network to drive a vehicle in the simulator!Traffic Sign ClassifierBehavioral Cloning
Tracking objects over time is a major challenge for understanding the environment surrounding a vehicle. Sensor fusion engineers from Mercedes-Benz will show you how to program fundamental mathematical tools called Kalman filters. These filters predict and determine with certainty the location of other vehicles on the road. You’ll even learn to do this with difficult-to-follow objects by using an extended Kalman filter, an advanced technique.Extended Kalman Filters
Localization is how we determine where our vehicle is in the world. GPS is only accurate to within a few meters. We need single-digit centimeter-level accuracy! To achieve this, Mercedes-Benz engineers will demonstrate the principles of Markov localization to program a particle filter, which uses data and a map to determine the precise location of a vehicle.Kidnapped Vehicle
The Mercedes-Benz team will take you through the three stages of planning. First, you’ll apply model-driven and data-driven approaches to predict how other vehicles on the road will behave. Then you’ll construct a finite state machine to decide which of several maneuvers your own vehicle should undertake. Finally, you’ll generate a safe and comfortable trajectory to execute that maneuver.Highway Driving
Ultimately, a self-driving car is still a car, and we need to send steering, acceleration, and brake commands to move the car through the world. Uber ATG will walk you through building a proportional-integral-derivative (PID) controller to actuate the vehicle.PID Controller
This is the capstone of the entire Self-Driving Car Engineer Nanodegree Program! We’ll introduce Carla, the Udacity self-driving car, and the Robot Operating System that controls her. You’ll work with a team of Nanodegree students to combine what you’ve learned over the course of the entire Nanodegree Program to drive Carla, a real self-driving car, around the Udacity test track!Programming a Real Self-Driving Car
from industry experts
Personal career coach and
Scientist, educator, inventor, and entrepreneur, Sebastian led the self-driving car project at Google X and founded Udacity, whose mission is to democratize education by providing lifelong, on-demand learning to millions of students around the world.
David Silver leads the School of Autonomous Systems at Udacity. Before Udacity, David was a research engineer on the autonomous vehicle team at Ford. He has an MBA from Stanford, and a BSE in computer science from Princeton.
Ryan has a PhD in Astrophysics and a passion for teaching and learning. He is also a lead instructor in the Robotics Nanodegree program. When he’s not building Udacious learning content you’ll find him up in the mountains or out in the surf.
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.
Mercedes-Benz R&D North America develops the world’s most advanced automotive technology and vehicle design with luxury and style. The team from Mercedes built our Sensor Fusion, Localization, and Path Planning content.
NVIDIA is a company built upon great minds and groundbreaking research. GPU deep learning has ignited modern AI - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
Uber ATG Team
The Advanced Technologies Group is comprised of Uber’s self-driving engineering team dedicated to self-driving technologies, mapping, and vehicle safety.
Going good so far.
Everythins goes well since now. Thank you!
Very well run, excellent structure for learning. Your prior experience is important, it could take some people much longer than others depending on how much of the material, or similar material, you've come across before. It's a good fit for me.
Numbers don't lie. See what difference it makes in career searches.*
Career-seeking and job-ready graduates found a new, better job within six months of graduation.
Average salary increase for graduates who found a new, better job within six months of graduation.
The Self-Driving Car Engineer Nanodegree program is one of the only programs in the world to both teach students how to become a self-driving car engineer, and support students in obtaining a job within the field of autonomous systems. The program’s nine projects equip students with invaluable skills across a wide array of critical topics, including deep learning, computer vision, sensor fusion, localization, controllers, vehicle kinematics, automotive hardware, and more. As part of their capstone project, students have the rare opportunity to run their code on an actual autonomous vehicle owned by Udacity.
Our wide-ranging curriculum will prepare you for a variety of roles in the autonomous vehicle industry, including: System Software Engineer, Deep Learning Engineer, Vehicle Software Engineer, Localization and Mapping Engineer and many others. If you elect to work outside of automotive engineering, your foundation in deep learning and robotics will enable you to fill any number of related roles in artificial intelligence, computer vision, machine learning, and more.
This advanced Nanodegree program is ideal for anyone with a programming, technical, or quantitative background who is interested in obtaining a job within the field of autonomous systems, or refreshing or developing their skills within the realm of machine and deep learning, systems integration, sensor fusion, and many others.
The Intro to Self-Driving Cars Nanodegree program is an intermediate program open to anyone with an interest in autonomous systems, who has some programming experience, and/or a quantitative background. The Self-Driving Car Engineer Nanodegree program is an advanced program focusing on in-depth knowledge of autonomous systems. The program is designed for those with moderate to high programming, technical, and/or quantitative skills.
There is no application. This Nanodegree program accepts everyone, regardless of experience and specific background.
Students should have prior experience with the following:
You will also need to be able to communicate fluently and professionally in written and spoken English.
The Self-Driving Car Engineer Nanodegree program is comprised of content and curriculum to support nine (9) projects. We estimate that students can complete the program in six (6) months, working 15 hours per week.
Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Please see the Udacity Nanodegree program FAQs for policies on enrollment in our programs.
The following versions are taught in this program (subject to update):