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Microcredential

Self Driving Car Engineer

Nvidia , Mercedes Benz , Uber ATG , DiDi , BMW and Mclaren Applied Technologies via Udacity Nanodegree

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Overview

If your goal is to learn the skills necessary to become a self-driving car engineer, and then secure a rewarding role in the field where you can start applying those skills, this program is the ideal choice. The Self-Driving Car Engineer Nanodegree program is one of the only programs in the world that both teaches you the right skills, and supports you in obtaining a job.

Through interactive projects in computer vision, robotic controls, localization, path planning, and more, you’ll prepare for a successful career in the incredible field of autonomous systems.


Self-driving cars are set to revolutionize the way we live. This is transformational technology, on the cutting-edge of robotics, machine learning, software engineering, and mechanical engineering. In this program, you’ll learn the skills and techniques used by self-driving car teams at the most advanced technology companies in the world.

Syllabus

Prerequisite Knowledge

Students should have experience with Python, C++, Linear Algebra, and Calculus. See detailed requirements.

  • 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.

    Finding Lane Lines on the RoadAdvanced Lane Finding
  • 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!

    Traffic Sign ClassifierBehavioral Cloning
  • 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.

    Extended Kalman Filters
  • 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.

    Kidnapped 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.

    Highway Driving
  • 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.

    PID Controller
  • 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 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

Taught by

Sebastian Thrun, David Silver, Ryan Keenan, Cezanne Camacho, Mercedes-Benz, NVIDIA, Uber ATG, Farhan A., Krishna K., Tim H., Anu A., Shreyas R. and Vishal R.

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Reviews for Udacity's Self Driving Car Engineer Based on 2 reviews

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Eric T
Eric this course, spending 15 hours a week on it.
Really challenging course

Udacity's Self-Driving Car Engineer course will give you a chance to write code that will control a car first in the simulator then in a real car. If you want to apply computer science and math to real world challenges, this is the course for you.
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Anonymous
Anonymous this course, spending 18 hours a week on it.
Learn fast and grow as a professional

Self-Driving Car Engineer Nanodegree Program allowed me to start up my skills in self-driving automotive industry. Brilliantly created projects allow to learn cutting-edge program in a space rocket pace!
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