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  • Time
    Two 4-month terms

    Study 15 hrs/week and complete in 8 mo.

  • Classroom Opens
    April 10, 2018

    Classroom is open.

  • Prerequisites
    Mathematics & Programming

    See detailed requirements

  • Student Rating

    View all reviews ()

  • Estimated Salary

    Based on US job data

In Collaboration With
  • Nvidia
  • Electric Movement

Why Take This Nanodegree Program?

In this program, you’ll gain hands-on experience developing robotics solutions as you cover topics such as: Robot Operating System (ROS), Kinematics, Control, Simultaneous Localization and Mapping (SLAM), and more. You’ll learn cutting-edge techniques like Deep Reinforcement Learning through our partnership with NVIDIA's Deep Learning Institute. You’ll master the key skills necessary to become a software engineer in the transformational field of robotics and applied artificial intelligence.

By 2019, spending on robotics and related services will hit
$135.4 B

World-Class Curriculum Partners

Udacity has joined forces with NVIDIA and Electric Movement to create a groundbreaking learning experience that features world-class curriculum. You’ll master cutting-edge skills and techniques, gain hands-on experience, and build unique projects focused on the most important concepts and topics in the field of robotics.


Career-Ready Skills

Graduates of this program will emerge fully prepared to join innovative robotics teams, and develop pioneering robotics solutions. You’ll be perfectly positioned to take advantage of rapidly-increasing demand for robotics talent, and the projects you build in this program will become part of a portfolio that demonstrates your mastery of career-ready robotics skills.

Learn with the Best

Sebastian Thrun
Sebastian Thrun

Udacity, President

As the founder and president of Udacity, Sebastian’s mission is to democratize education. He is also the founder of Google X, where he led projects including the Self-Driving Car, Google Glass and more.

Dana Sheahen
Dana Sheahen

Udacity, Curriculum Lead

Dana is an electrical engineer with a Masters in Computer Science from Georgia Tech. Her work experience includes software development for embedded systems in the Automotive Group at Motorola, where she was awarded a patent for an onboard operating system.

Ryan Keenan
Ryan Keenan

Udacity, Curriculum Lead

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.

Anthony Navarro
Anthony Navarro

Udacity, Product Lead

Anthony is a US Army combat veteran with an M.S. in Computer Engineering from Colorado State University. Prior to being a Product Lead at Udacity, he was a Senior Software Engineer at Lockheed Martin in their Autonomous Systems R&D division.

Julia Chernushevich
Julia Chernushevich

Udacity, Instructor

Julia is an instructor of Mechatronics Engineering at the University of Waterloo. Her previous work experiences include designing electric vehicles for underground mines and leading a prestigious STEM enrichment program for gifted high-school students.

Karim Chamaa
Karim Chamaa

Udacity, Instructor

Karim started his early career as a Mechanical Engineer. He earned his M.S. in Mechatronics and Robotics Engineering from NYU. His specialties include Kinematics, Control, and Electronics.



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.

Electric Movement
Electric Movement

Electric Movement Team

Electric Movement is a robotics engineering firm that brings to our program invaluable insights about real-world robotics applications, and deep, market-vetted expertise in ROS, robotics, automation, embedded systems, and agile development.

What You Will Learn

Download Syllabus

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Term 1

ROS Essentials, Perception, and Control

Begin your exploration into the world of robotics software with a practical, system-focused approach to programming robots using the ROS framework. Leverage classical mechanics and modern deep learning techniques to implement the key robotic functions of perception and control.

Explore robotics software using the ROS framework. Leverage classical techniques to implement perception and control.

See Details

4 months to complete

Prerequisite Knowledge

Knowledge of foundational calculus, linear algebra, probability, statistics, basic physics, and intermediate Python is required.

Existing experience with intermediate C++ and knowledge of machine learning techniques is recommended but not required. See detailed requirements.

  • Introduction To Robotics

    In this course, you'll get an introduction to your Nanodegree program, and explore the three essential elements of robotics: perception, decision making, and actuation. You'll also build your first project, which is modeled after the NASA Mars Rover Challenge.

    Icon project Search and Sample Return
  • ROS Essentials

    ROS provides a flexible and unified software environment for developing robots in a modular and reusable manner. In this course, you'll learn how to manage existing ROS packages within a project, and how to write ROS Nodes of your own in Python.

  • Kinematics

    Movement is one of the most exciting elements of building a Robot that interacts with the physical world. In this course, you'll learn to control a robotic arm with six degrees of freedom to perform pick and place actions using Inverse Kinematics.

    Icon project Robotic Arm: Pick and Place
  • Perception

    Robots perceive the world around them by using sensors. Working with sensor data for perception is a core element of robotics. Here you'll work with 3D point cloud data to perform segmentation tasks using techniques like RANSAC and clustering.

    Icon project 3D Perception
  • Controls

    Control systems are a central component to most robots. In this course, you’ll learn how a mechanical system can be described in terms of the equations that govern it. You'll then learn how to manage the behavior of the system using a controller. Lastly, you’ll have an opportunity to observe your controller in simulation.

  • Deep Learning

    Many recent developments in robotics can be attributed to advances in Deep Learning. In this course, you’ll learn about Convolutional Neural Networks (CNN), Fully Convolutional Networks (FCN), and Semantic Segmentation. You will then integrate a Deep Neural Network with a simulated quadcopter drone.

    Icon project Follow Me
Term 2

Localization, Mapping, and Navigation

In this term, you’ll study curriculum developed in partnership with NVIDIA's Deep Learning Institute as you learn to leverage probabilistic and deep reinforcement learning algorithms to solve problems of localization, mapping, and navigation.

Explore probabilistic and deep reinforcement learning algorithms to solve localization, mapping, and navigation problems.

See Details

4 months to complete

Prerequisite Knowledge

Knowledge of foundational calculus, linear algebra, probability, statistics, basic physics and intermediate Python is required.

Existing experience with intermediate C++ and knowledge of machine learning techniques is recommended but not required. See detailed requirements.

  • Introduction to Term 2

    In this course, you’ll get an introduction to Term 2, and explore hardware commonly used in robotics. You’ll learn the uses of common sensors, and which ROS packages you need to support them. Those students with NVIDIA Jetson TX2 Developer Kit hardware will learn how to set up the system and interact with external hardware.

  • Robotic Systems Deployment

    In this course, you’ll learn new tools, and the embedded workflow as you move from code on a host system to code on a target system. You’ll work through a familiar problem with these new tools, then extend what you’ve learned in a project.

    Icon project Robotic Inference
  • Localization

    Learn how Gaussian filters can be used to estimate noisy sensor readings, and how to estimate a robot’s pose relative to a known map of the environment with Monte Carlo Localization (MCL).

    Icon project Where am I?
  • SLAM

    Learn how to create a Simultaneous Localization and Mapping (SLAM) implementation with ROS packages and C++. You’ll achieve this by combining mapping algorithms with what you learned in the localization lessons.

    Icon project Map My World Robot
  • Reinforcement Learning for Robotics

    Begin by learning how to build a basic end-to-end reinforcement learning agent, termed a deep Q-network (DQN). Then, enhance it to create a more complex agent that can pick and place from visual input.

    Icon project Pick and Place with Deep Learning
  • Path Planning and Navigation

    Extend your RL Engine with more advanced techniques for navigation, and compare these with classic approaches. Finally, combine SLAM and navigation into a single comprehensive project!

    Icon project Home Service Robot

“The NVIDIA Deep Learning Institute and Udacity share a common vision—to provide students with hands-on training and challenging curriculum to accelerate their careers. We’re working with Udacity to build a world-class AI and deep learning program so that students can go on to become leading developers, researchers and academics in a variety of fields.”

— Greg Estes, Vice President of Developer Programs, NVIDIA

Start Learning Now

Term 1
Robotics Software


Using ROS, learn to solve robotics problems around perception, control, and deep learning.

Term 2
Advanced Robotics Software


Learn to apply SLAM and reinforcement learning techniques for solving robotics problems.

Start Learning Now

Student Reviews



  • Why should I enroll in the Robotics Software Engineer Nanodegree program?

    The field of robotics is growing at an incredible rate, and demand for software engineers with the right skills far exceeds the current supply. This makes this an ideal time to enter this field, and this groundbreaking program represents a unique opportunity to develop these in-demand skills.

    Expert instructors, personalized project reviews, and exclusive hiring opportunities are hallmarks of this program, and in collaboration with the NVIDIA Deep Learning Institute—one of the most exciting and innovative companies in the world—we have built an unrivalled curriculum that offers the most cutting-edge learning experience currently available.

    You will graduate from this program having completed several hands-on robotics projects in simulation that will serve as portfolio pieces demonstrating the skills you've acquired. This will enable you to pursue a rewarding career in the robotics field.

    Over the course of the program, you'll also have the opportunity to learn about robotics hardware such as the NVIDIA Jetson TX2 Developer Kit—eligible students will even have access to a special education discount on the Jetson TX2 through our collaboration with NVIDIA.

    For anyone seeking to launch or advance a career as a Robotics Software Engineer, and who wishes to be a part of the incredible world of robotics, this is the ideal program.

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