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.
The program will cover topics including, but not limited to: Perception, Kinematics, Localization, Control, SLAM, Deep Learning, and Reinforcement Learning. You will learn the basics of what goes into a robotics system by using the Robot Operating System (ROS), and you'll have the opportunity to gain familiarity with the NVIDIA Jetson TX2 Developer Kit.
The Machine Learning Engineer Nanodegree program is the most general of the three programs. It offers a great foundation, and is an excellent choice for anyone pursuing a career in a field where machine learning techniques are used. However, the curriculum is not as advanced as the other two programs, and it does not specialize to the same extent.
Note: The Machine Learning Engineer program is not an official prerequisite for either the Self-Driving Car or Robotics Software Engineer programs, but it may be beneficial to some students to complete this program first, depending on your existing knowledge and experience.
The Robotics Software Engineer Nanodegree program provides an introduction to software and artificial intelligence as applied to robotics. The areas we focus on are perception, localization, path planning, deep learning, reinforcement learning, and control. These are taught using the Robot Operating System (ROS) framework. All of the techniques required to complete the projects in the Robotics Software Engineer Nanodegree program (including machine learning) are taught as part of the program.
The Self-Driving Car Engineer Nanodegree program focuses entirely on a specialized application of robotics—it uses robotics concepts and applies them to a self-driving car. If your primary interest is in the application of robotics, machine learning, and artificial intelligence to self-driving cars, then this is the program for you. However, if you want a broader and more comprehensive robotics curriculum, with an emphasis on software engineering, then the Robotics Software Engineer Nanodegree program is your best option.
As a skilled Robotics Software Engineer, you'll be equipped to bring value to a wide array of industries; you might join a team developing pick and place robotics systems for advanced manufacturing; you could have a hand in developing the next surgical robot for the healthcare industry; you might join a robotics team building the next form of package delivery either on the ground or in the air. These are just a few of the ways in which skilled Robotics Software Engineers are building rewarding careers and creating the world of tomorrow.
Students should have the following skills coming into the program:
Looking to refresh your skills or prepare now? Get started with the following resources:
You will learn the practical application of robotics concepts like perception, localization, path planning and controls, using the languages and frameworks that are in demand in the industry (Python, C++, ROS, Gazebo). In addition, you'll work on deep learning projects that use NVIDIA's DIGITS, TensorFlow, and PyTorch.
The software tools used for robotics are compute-intensive and traditionally built on Linux. Therefore, a native Linux operating system is highly recommended for the best experience. However, it is possible to use virtual and cloud-based solutions for all projects in this course. The minimum computational prerequisite requirements for this Nanodegree program are the following:
Note: If you are eligible to take advantage of the education discount made available through our collaboration with NVIDIA DLI, and you elect to purchase the Jetson TX2 Developer Kit , you will need a host PC running Linux to update your hardware with the latest software components.
The core of this program focuses on robotics applications in software. You can master every skill, and complete every project, while focusing entirely on software, and working in simulation.
That said, we are excited that our collaboration with NVIDIA DLI makes it possible for eligible Term 2 students to receive an education discount that can be applied to the purchase of an NVIDIA Jetson TX2 Developer Kit! Eligible students are encouraged to take advantage of this special offer, as this embedded super computing platform will enable you to take classroom projects (and your own personal projects) out of simulation and bring them into real-world scenarios.
It will not. The skills and concepts we teach can all be mastered in the simulation environment. There is no requirement to purchase the Jetson TX2 Developer Kit. All of the projects will be graded without the use of hardware, and you can successfully graduate from the program without working with the hardware.
Our focus in this program is on the role of a Robotics Software Engineer, so while you will gain a broad understanding of robotics as a field that combines multiple engineering disciplines—including electrical, mechanical, and systems—the specific skills you will master are geared towards developing robotics software solutions.
Udacity has an active Robotics Slack Community here. The Slack community enables you to connect directly with your classmates in real time; all Udacity students regularly use these forums to support each other's work, answer each other's questions, and share relevant ideas and resources. Virtually all of our graduates highlight this community aspect as one of the most important parts of their Nanodegree program experience.
NVIDIA also has a developer community you can explore here.
NVIDIA Jetson is the world's leading platform for “AI at the edge.” Its high-performance, low-power computing for deep learning and computer vision makes it the ideal platform for compute-intensive robotics projects.
For more information, see the NVIDIA Jetson Developer Zone.
Yes! As an enrolled student of the Robotics Software Engineer Nanodegree program, you are eligible to receive a special education discount that can be applied to the purchase of a Jetson TX2 Developer Kit.
The education discount varies by region. For most countries the discount is 50% off the retail price of the Jetson TX2 Developer Kit.
Upon successfully enrolling in Term 2 of the program, you'll receive an email with detailed instructions for buying the Jetson TX2 developer kit at the discounted price from the NVIDIA store, or the local distributor, depending on the country of residence.
*Students must meet eligibility requirements as defined by NVIDIA on their site to purchase the Jetson TX2 Developer Kit with the education discount.
NVIDIA will be supporting the Jetson TX2 hardware directly. You can find more information about support options here.
When you place your order, you should receive confirmation emails and contact information for the distributor who will be handling your order. Contact the distributor with your order number for any assistance needed.
Given the specialized nature of this curriculum, it's important that enrolled students have the required knowledge, skills, and experience in advance. This process allows us to assess each applicant's qualifications, and either accept them to the program, or make recommendations for courses that will help them meet the prerequisites so they can truly succeed in the program.
You must have previous knowledge of math (calculus, linear algebra, statistics) and basic physics. You must also have programming experience in Python or similar language and be able to solve problems given a set of requirements. Experience with ROS, C++ and machine learning experience are helpful but not required.
Udacity offers a number of free and paid courses that can help you with subjects you may need to address. If you would like guaranteed acceptance to our Robotics Software Engineer Nanodegree program, you can complete the Intro to Self-Driving Cars Nanodegree. Below is also a list of potentially relevant courses you may wish to consider:
If you weren't accepted, don't worry! The most common reason for not being accepted is that you still need to build some of the skills required for the program. Fortunately, we have many courses at Udacity that will enable you to hone your skills in the required areas, and position yourself for a successful future application. If you would like to gain guaranteed admission to the Robotics Software Engineer Nanodegree program, you can complete our Intro to Self-Driving Cars Nanodegree program. Alternatively, you can find additional courses offered by Udacity that might be helpful to you. Here is a list of potentially relevant courses you may wish to consider:
Yes, we expect to open enrollment for new terms on a bi-monthly basis.
The program consists of two 4-month long terms. $1200 per term for a total program cost of $2400.
You pay your full tuition fee before the start of each term.
Yes! Click here to start your free preview!
All current scholarship opportunities are posted on our Scholarships page
The program is comprised of 2 terms (4 months each) with fixed start and end dates. Students must successfully complete all assigned projects by the end date for each term to graduate. There are 4-5 projects per term, which give you an opportunity to apply the skills you've learned in the lessons. Each project must be submitted for review by one of the expert project reviewers in the Udacity Robotics network. Your reviewer will give you detailed feedback on your work and let you know where your project needs improvement if necessary. You may submit each project as many times as you like.
No, not currently. Students of this program are welcome to attend Connect sessions, but we will not provide curriculum support at the sessions, nor will there be session leads onsite who are equipped to provide specific program guidance and input.
No, this is not an option. The fixed-term nature of the program, and the need for maintaining a consistent and stable student body throughout, doesn't allow for offering the option to pause your studies.
The start and end dates of each term are fixed, and you must complete all assigned projects by the end dates, so to that extent, the answer is “no, it is not self-paced.” You must complete the program within a fixed time period. However, projects may be submitted at any time during the term, and individual project deadlines are recommendations, not requirements. So within the boundaries of a given term, there is some opportunity to work at your own pace. But you should plan to follow our recommended timeline, as this will best enable you to keep pace with your peers, and complete the program on time.
When we use the term "deadline" with regards to Nanodegree Program projects, we use it in one of two ways:
It is very important to understand the distinctions between the two, as your progress in the program is measured against the deadlines we've established. Please see below for an explanation of what each usage means.
In order to graduate a term, you must submit all projects by the last day of the term and pass all projects once they are reviewed by a Udacity Reviewer (the review may take place after the last day of the term). Passing a project means a Udacity Reviewer has marked a project as "Meets Specifications."
If you do not submit all projects by the end of the term, and also pass all projects once they are reviewed, you will receive a 4-week extension to complete any outstanding projects. You will only receive this extension a maximum of once. Once you submit and pass all projects, you can enroll in the next term, which will potentially be with a later class. If you do not submit and pass all projects within the 4-week extension, you will be removed from the program.
The deadlines you see in your classroom are suggestions for when you should ideally pass each project. They are meant to help keep you on track so that you maintain an appropriate pace throughout the program—one that will see you graduate on time!
Please note that you can submit your project as many times as you need to. There are no penalties if you miss these deadlines. However, you will be at risk of not passing all projects on time if you miss these deadlines, and fall behind, so it is a recommended best practice to try and meet each suggested deadline.
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