30% OFF
undefined months access
per month
Start learning today! Switch to the monthly price afterwards if more time is needed.
Estimated Time
6 months
At 15 hrs/week
Enroll by
June 30, 2021
Get access to the classroom immediately on enrollment
Prerequisites
Python, C++, & Mathematics
Built in partnership with
What You Will Learn
Syllabus
Self-Driving Car Engineer
Related NanodegreesPrerequisite Knowledge
Students should have experience with Python, C++, Linear Algebra, and Calculus.
Introduction
Learn about how self-driving cars work and about the services available to you as part of the Nanodegree program.
Computer Vision
Use a combination of cameras and software to find lane lines on difficult roads and to track vehicles.
Deep Learning
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!
Sensor Fusion
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.
Localization
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.
Planning
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.
Control
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.
System Integration
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 to combine what you’ve learned over the course of the entire Nanodegree Program to run your code on a virtual version of Carla, a real self-driving car! NOTE: Due to the ongoing coronavirus pandemic, capstone projects will be tested in simulation only - this will not affect the graduation process or requirements.
As a self-driving car engineer, you have the potential to help save over 1 million people per year!
Program OfferingsFull list of offerings included:
Enrollment Includes:
Class Content
Content Co-created with Mercedes-Benz
Real-world projects
Project reviews
Project feedback from experienced reviewers
Student Services
Technical mentor support
New
Student community
Improved
Career services
Resume support
Github review
Linkedin profile optimization
Succeed with Personalized Services
We provide services customized for your needs at every step of your learning journey to ensure your success!
Get timely feedback on your projects
Reviews By the numbers
1,400+ project reviewers
2.7M projects reviewed
88/100 reviewer rating
1.1 hours avg project review turnaround time
Reviewer Services
- Personalized feedback
- Unlimited submissions and feedback loops
- Practical tips and industry best practices
- Additional suggested resources to improve
Mentors available to answer your questions
Mentors by the numbers
1,400+ technical mentors
0.85 hours median response time
Mentorship Services
- Support for all your technical questions
- Questions answered quickly by our team of technical mentors
Learn with the best
Sebastian Thrun
Udacity President
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
Curriculum Lead
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 Keenan
Course Developer
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 Camacho
Course Developer
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
Mercedes-Benz Team
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
Nvidia Team
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
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.
GET STARTED WITH
Self Driving Car Engineer Nanodegree
Learn
Build the Future of Transportation, today
Average Time
On average, successful students take undefined months to complete this program.
Benefits include
- Real-world projects from industry experts
- Technical mentor support
- Career services
Pay as you go
per month
Start learning today! Get maximum flexibility to learn at your own pace.
Related Nanodegree Programs
Sensor Fusion Engineer
Nanodegree Program
Learn to fuse lidar point clouds, radar signatures, and camera images using Kalman Filters to perceive the environment and detect and track vehicles and pedestrians over time.
Advanced
Flying Car and Autonomous Flight Engineer
Nanodegree Program
Master job-ready autonomous flight software engineering skills as you tackle advanced challenges, write real code for real aircraft, and develop a systems understanding of the Flying Car full-stack.
Advanced
Program Details
PROGRAM OVERVIEW - WHY SHOULD I TAKE THIS PROGRAM?
Why should I enroll?
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 opportunity to run their code on a virtual simulation of Udacity's real self-driving car, Carla.What jobs will this program prepare me for?
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.How do I know if this program is right for me?
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.What is the difference between the Intro to Self-Driving Cars Nanodegree program and the Self-Driving Car Engineer Nanodegree program?
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.
ENROLLMENT AND ADMISSION
Do I need to apply? What are the admission criteria?
There is no application. This Nanodegree program accepts everyone, regardless of experience and specific background.What are the prerequisites for enrollment?
Students should have prior experience with the following:- Intermediate Python or C++
- Basic Linear Algebra
- Basic Calculus
- Basic Statistics
- Basic Physics
You will also need to be able to communicate fluently and professionally in written and spoken English.If I do not meet the requirements to enroll, what should I do?
We have a number of Nanodegree programs and free courses that can help you prepare, including: Intro to Self-Driving Cars Nanodegree program, Robotics Software Engineer Nanodegree program, and AI for Robotics Course.
TUITION AND TERM OF PROGRAM
How is this Nanodegree program structured?
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.How long is this Nanodegree program?
Access to this Nanodegree program runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.Can I switch my start date? Can I get a refund?
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.I have graduated from the Self-Driving Car Engineer Nanodegree program but I want to keep learning. Where should I go from here?
Once you have completed the Self-Driving Car Engineer Nanodegree program, the Robotics Software Engineer Nanodegree program and the Flying Car Nanodegree program are ideal for continuing your learning.
SOFTWARE AND HARDWARE - WHAT DO I NEED FOR THIS PROGRAM?
What software and versions will I need in this program?
For this Nanodegree program, you will need to the minimum equipment requirements outlined here: https://www.udacity.com/tech-requirements.Which version of TensorFlow, Keras, ROS, and C++ are taught in this program?
The following versions are taught in this program (subject to update):- TensorFlow Version 1.3
- Keras version 2
- ROS Kinetic
- Python Version 3
- C++ Version 11