• Time
    3 Three-Month Terms

    Study 15 hrs/week and complete in 9 mo.

  • Classroom Opens
    January 18, 2018

    Classroom opens in 34 days.

  • Prerequisites
    Python, C++, Mathematics

    See detailed requirements

  • Student Rating

    View all reviews ()

  • Estimated Salary

    Based on US job data

In Collaboration With
  • Mercedes
  • Nvidia
  • Uber ATG
  • Didi
  • BMW
  • McLaren

Why Take This Nanodegree Program?

Self-driving cars represent one of the most significant advances in modern history. Their impact will go beyond technology, beyond transportation, beyond urban planning to change our daily lives in ways we have yet to imagine.

Students who enroll in this self-driving car program will master driverless car technologies that are going to shape the future and impact the lives of people around the world. Through interactive projects in computer vision, robotic controls, localization, path planning, and more, you’ll prepare yourself for a key role in this incredible field. If your goal is to build the future, then your future begins here.

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Researchers estimate driverless cars will save 10 million lives per decade!

Features 1
Amazing content & live sessions

A One-Of-A-Kind Program

Sebastian Thrun and the Udacity Self-Driving Car team are pioneering educators in the autonomous vehicle field, and Udacity offers the only program of its kind, where you can learn everything you need to know to launch a successful career as a Self-Driving Car Engineer.

Projects with expert feedback

World-Class Curriculum

In this program, you’ll learn from the some of the most innovative companies operating in this field. Companies like NVIDIA, Mercedes-Benz, and more. Their teams are defining the future of autonomous transportation, and they helped us build this incredible driverless technology curriculum.

Features 2
Guaranteed Admission

Valuable Hiring Partnerships

Our hiring partners are some of the most forward-looking companies in the world, and they're looking for Udacity graduates to fill critical roles today. These partnerships represent a unique opportunity to benefit from fast-tracked consideration for open roles at partner companies, and this affords you a distinct leg up in your job searches.

Earn a Udacity Foundation Nanodegree

Real-World Learning

In addition to the groundbreaking work you’ll do in simulation, you’ll have the opportunity to run your code on a real self-driving car!

Learn with the Best

Sebastian Thrun
Sebastian Thrun

Udacity President

Scientist, educator, inventor, and entrepreneur, Sebastian led the self-driving car project at Google X, and founded Udacity with a mission is to democratize education by providing lifelong learning opportunities to millions of students around the world.

David Silver
David Silver

Curriculum Lead

David Silver leads the Self-Driving Car Engineer Nanodegree Program. 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
Ryan Keenan

Content Developer

Ryan has a PhD in Astrophysics from the University of Wisconsin-Madison. He is also a lead instructor for the Self-Driving Car and Flying Car Nanodegree programs.

Cezanne Camacho
Cezanne Camacho

Content 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

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

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

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.

Elektrobit
Elektrobit

Elektrobit Team

Benjamin Brentrop, Elektrobit’s Head of Functional Safety Consulting, has been working in the testing and functional safety field since 2006. In his current role at EB, he consults with OEM and Tier 1s, to provide functional safety knowledge and expertise for global automotive projects.

What You Will Learn

Download Syllabus

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Term 1

Computer Vision and Deep Learning

In this term, you'll become an expert in applying Computer Vision and Deep Learning on automotive problems. You will teach the car to detect lane lines, predict steering angle, and more all based on just camera data!

In this term, you'll become an expert in applying Computer Vision and Deep Learning on automotive problems.

See Details

3 months to complete

Prerequisite Knowledge

To optimize your chances for a successful application to our Self-Driving Car Engineer Nanodegree program, we’ve created a list of prerequisites and recommendations to help prepare you for the program curriculum. See detailed requirements.

  • Introduction

    In this course, you will learn about how self-driving cars work, and you’ll take a crack at your very first autonomous vehicle project - finding lane lines on the road! We’ll also introduce the Nanodegree Program and the services we provide over the course of the journey.

    Icon project Finding Lane Lines on the Road
  • Deep Learning

    Deep learning has become the most important frontier in both machine learning and autonomous vehicle development. Experts from NVIDIA and Uber ATG will teach you to build deep neural networks and train them with data from the real world and from the Udacity simulator.

    Icon project Traffic Sign Classifier Icon project Behavioral Cloning
  • Computer Vision

    You’ll use a combination of cameras, software, and machine learning to find lane lines on difficult roads and to track vehicles. You’ll start with calibrating cameras and manipulating images, and end by applying support vector machines and decision trees to extract information from video.

    Icon project Advanced Lane Finding Icon project Vehicle Tracking
Term 2

Sensor Fusion, Localization, and Control

In this term, you'll learn how to use an array of sensor data to perceive the environment and control the vehicle. You'll evaluate sensor data from camera, radar, lidar, and GPS, and use these in closed-loop controllers that actuate the vehicle.

In this term, you'll learn how to use an array of sensor data to perceive the environment and control the vehicle.

See Details

3 months to complete

Prerequisite Knowledge

To optimize your chances for a successful application to our Self-Driving Car Engineer Nanodegree program, we’ve created a list of prerequisites and recommendations to help prepare you for the program curriculum. See detailed requirements.

  • 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.

    Icon project Extended Kalman Filters Icon project Unscented Kalman Filters
  • Localization

    Localization is how we determine where our vehicle is in the world. GPS is great, but it’s 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.

    Icon project Kidnapped Vehicle
  • Control

    Ultimately, a self-driving car is still a car, and we need to send steering, throttle, and brake commands to move the car through the world. Uber ATG will walk you through building both proportional-integral-derivative (PID) controllers and model predictive controllers. Between these control algorithms, you’ll become familiar with both basic and advanced techniques for actuating a vehicle.

    Icon project PID Controller Icon project Model Predictive Control
Term 3

Path Planning, Concentrations, and Systems

In this term, you'll learn how to plan where the vehicle should go, how the vehicle systems work together to get it there, and you'll perform a deep-dive into a concentration of your choice.

Learn how to plan where a vehicle should go, and how its systems work together to get there. Plus, choose your concentration!

See Details

3 months to complete

Prerequisite Knowledge

To optimize your chances for a successful application to our Self-Driving Car Engineer Nanodegree program, we’ve created a list of prerequisites and recommendations to help prepare you for the program curriculum. See detailed requirements.

  • Path Planning

    The Mercedes-Benz Vehicle Intelligence team will take you through the three stages of path 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.

    Icon project Path Planning Project
  • Elective: Advanced Deep Learning

    Students in this elective, built with the NVIDIA Deep Learning Institute, will learn about semantic segmentation, and inference optimization, active areas of deep learning research. This course is an elective. Students choose between completing either Advanced Deep Learning or Functional Safety for graduation.

    Icon project Elective: Advanced Deep Learning
  • Elective: Functional Safety

    Students who select the Functional Safety specialization, built with Elektrobit, learn functional safety frameworks to ensure that vehicles are safe, both at the system and component levels. This course is an elective. Students choose between completing either Advanced Deep Learning or Functional Safety for graduation.

    Icon project Elective: Functional Safety
  • System Integration

    This is 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 the 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!

    Icon project Programming a Real Self-Driving Car!

Apply Now

Term 1
Computer Vision and Deep Learning
$800

total

Start your self-driving car training by applying Computer Vision and Deep Learning to automotive problems.

Apply Now

“There's an enormous market for self-driving car engineers. Lots and lots of companies that you wouldn't suspect have entered that field and are massively hiring.”

— Sebastian Thrun, Udacity

Student Reviews

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FAQ

  • Why should I enroll in this program?

    Udacity is the only place to offer this kind of opportunity. We have partnered with the best companies in the field to offer world-class curriculum, expert instructors, and exclusive hiring opportunities. Almost any student anywhere in the world with an internet connection can study to become a self-driving car engineer at Udacity. You'll even build and run code on an actual autonomous vehicle that is owned by Udacity.

See More Questions

Self-Driving Car Engineer

Apply today, and start putting your skills to work!

Apply Now
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