AWS DeepRacer Scholarship Challenge
AWS and Udacity are teaming up to teach machine learning and prepare students to test their skills by participating in the world’s first autonomous racing league—the AWS DeepRacer League. Students with the top lap times will earn full scholarships to the Machine Learning Engineer Nanodegree program.
Start Your Engines!
Students, start your engines and get ready to race
You’ll build, train and evaluate your own reinforcement learning (RL) models to submit into the virtual race.
You’ll participate in a vibrant scholarship student community, where you can share racing tips with classmates.
Join the AWS DeepRacer League
The world’s first global autonomous racing league for developers.
How it Works
The AWS DeepRacer Scholarship Challenge is open to all students, 18 years of age or older, interested in machine learning. We recommend students have a basic knowledge of Python.
The program begins August 1 and will run through October 31, 2019. You can join the scholarship community at any point during these 3 months and immediately enroll in Udacity’s specialized AWS DeepRacer course.
Once you enroll, you’ll work through the brief AWS DeepRacer course consisting of several short modules that will prepare you to create, train, and fine-tune a reinforcement learning model in the AWS DeepRacer 3D racing simulator. Throughout the program–including while you progress through the course and while you work on your racing submissions–you’ll have access to a custom scholarship student community where you can get pro tips from experts and exchange ideas with your classmates.
Each month you’ll be able to pit your skills against others in virtual races in the AWS DeepRacer console. Students will compete for top spots in each month’s unique race course. Students that record the top lap times in August, September, and October 2019 will qualify for one of 200 full scholarships to the Machine Learning Engineer Nanodegree program.
AWS DeepRacer Scholarship Challenge
Learn the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Dedicate just a few hours going through the initial course and as many as you’d like on your AWS DeepRacer model submissions.
Participate in a vibrant student community where you’ll support and collaborate with classmates and receive tips and guidance from experts.
Use the skills you learn to compete with your peers in the AWS DeepRacer League Virtual Circuit.
Top performers in the AWS DeepRacer Scholarship Challenge will earn one of 200 full scholarships to:
Machine Learning Engineer
Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment.
August 1, 2019 [12pm PST]
October 31, 2019 [11:59pm PST]
October 31, 2019 [11:59pm PST]
August 1, 2019 [12pm PST]
CHALLENGE SCHOLARSHIP PARTICIPANTS BEGIN
Anytime between August 1 and October 31, 2019
This program is open to any student over the age of 18 who wants to strengthen their machine learning skills and test their skills in the global AWS DeepRacer League.
Program closes October 31, 2019 [11:59pm PST]
August 1, 2019 [12pm PST]
AWS DeepRacer at a Glance
AWS DeepRacer is a 1/18th scale race car which gives you an interesting and fun way to get started with reinforcement learning (RL). With AWS DeepRacer, you now have a way to get hands-on with RL, experiment, and learn through autonomous driving. You can get started with the virtual car and tracks in the cloud-based 3D racing simulator. For a real-world experience, you can deploy your trained models onto AWS DeepRacer and race your friends or others in the global AWS DeepRacer league, the world’s first global autonomous racing league for developers.
Start Your Engines!
When does the program begin? When does it end?
The AWS DeepRacer Scholarship Challenge begins on August 1 and ends on October 31, 2019. Interested students can enroll and join the scholarship community at any point during these 3 months. In fact, even students that join in October will be eligible for a full Nanodegree scholarship.
How many Nanodegree scholarships are available?
200 scholarships to the Machine Learning Engineer Nanodegree programs are guaranteed for program participants. Depending on the overall number of students who submit entries into the AWS DeepRacer league, AWS may sponsor even more Nanodegree program scholarships!
How do I qualify for a Nanodegree scholarship?
Race! Program participants will be able to submit entries in each month’s unique AWS DeepRacer Virtual Circuit race track. We will track the performance of the AWS DeepRacer Scholarship Challenge program participants in the leader board and top performers will then receive Nanodegree scholarships. Remember, to qualify for entry to the AWS DeepRacer Scholarship Challenge you must be registered with Udacity for the challenge and you need to submit your model to the AWS DeepRacer League Virtual Circuit leaderboard between August 1 and October 31, 2019.
At the end of the program, Nanodegree scholarships will be provided to the top performers registered in this program specifically (not the overall AWS DeepRacer League) in August, September, and October races, as well as to participants who record the highest total point scores across all 3 months.
How do points work?
You’ll receive points based on your fastest lap time for each month’s race. Points will aggregate across the monthly Virtual Circuit races. The points will be calculated as follows:
- The maximum score of 1000 less the lap time in seconds, to three decimal places.
- Points per entrant per race = max (1000-lap time)
- For example, if your fastest lap time recorded on the leaderboard is 10.500 seconds you’ll get 989.500 points. 1000-10.500 = 989.5000
Points will accumulate across the 3 month program duration (Aug-Oct). You can increase your score by participating in multiple races and improving your models and the resulting lap time for each month’s race.
Remember, you can participate in 1, 2 or all 3 of the monthly races included in this program and score points for your fastest lap. More races, more points.
If I’ve previously participated in AWS DeepRacer before this scholarship, will my lap times or points from earlier months count?
Great to see your enthusiasm. We understand the concern and while we appreciate high performers who have been using the AWS DeepRacer platform for a while, these Nanodegree scholarships are an opportunity for all users to have a healthy competition from the same start date. We encourage you to take advantage of your earlier experience and submit some great new entries for the August, September, and October races.
If I only start the Scholarship Challenge in September or October, would I still be eligible for one of the Nanodegree scholarships?
Yes. Scholarships will be provided to the top performers from each month’s race. So if you only manage to enter into the October race, you are still eligible for a Nanodegree scholarship for that month’s race, depending on your race results. However, students that submit entries each month will have more opportunities to qualify for a Nanodegree scholarships.
Can I qualify for more than one Nanodegree scholarship?
No. To ensure as many students as possible are able to benefit from Nanodegree scholarships, there is a limit of one Nanodegree scholarship per student. This ensures more learners are able to benefit from the program and take the Machine Learning Engineer Nanodegree program.
Must I take the course to sign up for the AWS DeepRacer league? Or can I go straight to the league and qualify for a Nanodegree scholarship?
For AWS and Udacity to recognize you as a program participant and to qualify for a Nanodegree scholarship, you must agree to the basic program terms, including providing your email address and allowing Udacity to share it with AWS to check students’ race scores. Agreeing to these basic terms will allow you to immediately gain access to the course. To be clear, your course progress will not be considered when we award Nanodegree scholarships. These scholarships will be awarded to students with the top racing times in the AWS DeepRacer monthly races. However as the course helps learners fine tune their models and improve their overall race performance, we recommend you take advantage and invest time going through the course.
How do I sign up for AWS DeepRacer League?
You can sign up and start building in the AWS DeepRacer console. While you will need a credit card to create an AWS account, you will not be charged to create the account. Remember, to qualify for entry to the AWS DeepRacer Scholarship Challenge you must be registered with Udacity for the challenge and you need to submit your model to the AWS DeepRacer League Virtual Circuit leaderboard between August 1 and October 31, 2019.
Will I get charged for using AWS services?
With the AWS DeepRacer free tier we’ve got you covered with up to 10 hours of training, which is enough to train your first model and enter the AWS DeepRacer Scholarship Challenge at no cost to you. Upon first use of AWS DeepRacer simulation in the AWS console, new customers (this includes customers new to AWS and also existing AWS customers who are using AWS DeepRacer for the first time) will get 10 hours of Amazon SageMaker training, and 60 Simulation Unit (or SU) hours for Amazon RoboMaker in the form of $30 service credits. The service credits are applied directly to your AWS account at the end of the month and are available for 30 days – you will see a credit on your billing statement, notifying you this was from AWS DeepRacer. A typical AWS DeepRacer simulation uses 6 to 9 Simulation Units per hour, thus the free-tier will allow you to run between 6 and 10 hours for free when running a typical AWS DeepRacer simulation. You will not be charged when you submit a model to take part in any AWS DeepRacer League Virtual Event.
With AWS DeepRacer console services, there are no upfront charges and you will only pay for the AWS service you use. After you have used up your $30 credits, you will be billed separately by each of the AWS Services used to provide AWS DeepRacer console services such as creating and training your models and logs, and evaluating them. You will see the bill for each service on your monthly billing statement.
Do I have to use the same email address to register with AWS DeepRacer and Udacity?
Yes! To ensure you can qualify for one of the Nanodegree scholarships, you must use the same email address for both Udacity and AWS DeepRacer. Udacity and AWS DeepRacer will use student email addresses to identify top racers from the program.
Is there an application?
No. To access the course and join the scholarship community, you just have to agree to some simple terms, primarily agreeing for Udacity to share your email with AWS so that we can see which students were the top performers in the AWS DeepRacer races.
What are the restrictions to participate?
Participants must be over the age of 18.
Residents of a restricted country designated by the United States Treasury’s Office of Foreign Assets Control are not eligible to participate in this program. For more details, see: https://www.treasury.gov/resource-center/sanctions/Programs/Pages/Programs.aspx
How many hours a week am I expected to spend on this program?
You can spend as many as you’d like. Though the course itself is relatively short (90-120 minutes on average), you can work on your AWS DeepRacer submissions for as long as you’d like. You can submit multiple entries each month if you’d like to try to improve your lap time and point score.
Is participation in the scholarship student community required to qualify for a Nanodegree scholarship?
No. However, the community will serve as a focal point to engage with other similarly focused learners and to get tips from experts and classmates. We’ll be organizing office hours and special sessions to provide extra support for your AWS DeepRacer submissions.
Do I need to purchase hardware to participate in the program?
No. Students can use the AWS DeepRacer console online to train their models and compete in the AWS DeepRacer league. Although we encourage you to take advantage of the available hardware, it is not a requirement.
How is the Intro to Reinforcement Learning course different than other courses available?
The course will teach students the fundamentals of reinforcement learning with a special focus on applying it through the AWS DeepRacer platform. The course will consist of existing AWS and Udacity content as well as new content developed specifically for the Udacity community.
Why is AWS sponsoring these scholarships?
AWS understands the need to accelerate adoption of machine learning technologies to build a better future. A critical part of this requires a qualified pool of developers with the necessary skills in machine learning. By partnering with Udacity to develop top-notch programs including the Deep Learning and Machine Learning Nanodegrees, AWS is reaching students around the world and teaching those skills in a practical and fun way.
Through their generous support of this scholarship program, AWS continues to show a strong commitment to lifelong education by investing resources to find the most qualified developers that have shown a strong commitment to learn and empowering them to continue learning skills that are in demand in the AWS ecosystem.
Is the AWS DeepRacer Challenger Scholarship, and the AWS DeepRacer League, available to all students globally?
Yes! We highly encourage students across the globe to participate in the Udacity AWS DeepRacer Course and and DeepRacer League. The only exception is China, where there are technical restrictions prohibiting students from accessing the AWS platform – you can read more here.
If you happen to encounter any trouble trying to access the AWS Console from outside the US, AWS Customers can access the AWS DeepRacer simulator from the US East (N. Virginia) Region. If you get a pop-up saying “Region Unsupported,” please select “US East (N. Virginia)” in the “Supported Regions” option within the pop-up. You will be able to submit entries to AWS DeepRacer without issue even if you are not in the US region. You can find more information here.