TIME

3 Three-Month Terms

Application

By May 29!

Prerequisites

Python, Analysis, Git/GitHub

Price

40500 EGP

total

Built in partnership with

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 program will master technologies that are going to shape the future. 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.

Term 1

Computer Vision and Deep Learning

A One-Of-A-Kind Program

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 everything you need to know to launch a successful career as a Self-Driving Car Engineer.

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 curriculum.

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.

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!

What You Will Learn

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.

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.

Traffic Sign ClassifierBehavioral 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.

Advanced Lane FindingVehicle Tracking

Need to prepare?

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.

Extended Kalman FiltersUnscented 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.

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.

PID ControllerModel 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.

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.

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.

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 othe 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!

“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

Learn with the best

Sebastian Thrun

Tutor

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.

David Silver

Tutor

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

Tutor

Ryan has a PhD in Astrophysics and a passion for teaching and learning. He is also one of the lead instructors in the Self-Driving Car Nanodegree program. When he’s not building Udacious robotics lessons you’ll find him up in the mountains or out in the surf.

Cezanne Camacho

Tutorin

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. With more than 120 scientists around the globe, the areas of focus include AI, self-driving cars, high-performance computing, graphics, VR, and augmented reality.

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 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.

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.

What jobs will this program prepare me for?

With curriculum covering topics such as deep learning, computer vision, sensor fusion, localization, control, path planning, and automotive hardware, program graduates will be uniquely prepared for a wide variety of roles in the autonomous vehicle industry.

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 other industries, including: Robotics Software Engineer, Prediction Engineer, Computer Vision Engineer, IoT Engineer, and Automation Engineer!

How are you developing the curriculum, and who are your partners?

Udacity is developing the Self-Driving Car Engineer Nanodegree program in close partnership with leading experts in the autonomous vehicle industry, including Mercedes-Benz, Nvidia and Uber ATG.

For Business

About Udacity

Udacity is not an accredited university and we don't confer traditional degrees. Udacity Nanodegree programs represent collaborations with our industry partners who help us develop our content and who hire many of our program graduates.