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Blane Sundred
and
DeClercq Wentzel
Take Udacity's AWS DeepRacer course and learn the fundamentals of machine learning and reinforcement learning in an engaging way through autonomous driving with AWS DeepRacer.
Register for this course and see more details by visiting:
OpenCourser.com/course/3atc8u/aws
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What's inside
Syllabus
Learn the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Read more
Syllabus
Learn the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Read more
Receive an overview of what you’ll be learning and doing in the course, learn about the items that come in the AWS DeepRacer box, and assemble and calibrate your vehicle!
First, learn how to navigate the standard AWS DeepRacer online platform. Then, build, train and evaluate your own basic racer in the online simulator!
Study the basics of reinforcement learning, including agents, actions, environments, states, and rewards. Then, find out how RL is used with AWS DeepRacer, and investigate other applications of RL.
Go more in depth with how parameters, hyperparameters and different reward functions can affect the racer’s performance. Then, enhance your racer by trying out your new skills on your own model!
Deploy your trained model onto your hardware. Next, learn about ROS. Study the differences between simulated and real-world tracks, and then dive even further in-depth on customizing your training.
Find out how to compete in both online and in-person AWS DeepRacer events, and then get yourself on the leaderboards!
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides an overview of what you’ll be learning and doing in this course, the items that come in the AWS DeepRacer box, and teaches you how to assemble and calibrate your vehicle!
Provides hands-on experience with building, training, and evaluating your own basic racer in the online simulator!
Provides the basics of reinforcement learning, including agents, actions, environments, states, and rewards. Examines how RL is used with AWS DeepRacer, and other applications of RL
Dives into details on how parameters, hyperparameters and different reward functions can affect the racer’s performance. Allows you to enhance your racer by trying out your new skills on your own model!
Provides instructions on how to deploy your trained model onto your hardware, learn about ROS, and study the differences between simulated and real-world tracks
Teaches you how to customize your training process even further, and prepare for competing in both online and in-person AWS DeepRacer events
Save this course
Save AWS DeepRacer Course to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in AWS DeepRacer Course with these
activities:
Read Reinforcement Learning: An Introduction
Show steps
Provides a comprehensive overview of reinforcement learning concepts and algorithms.
View
Reinforcement Learning, second edition: An...
on Amazon
Show steps
-
Read the first three chapters of the book to understand the basic concepts of reinforcement learning.
-
Work through the exercises and examples in the book to reinforce your understanding.
-
Apply the concepts you have learned to build and train your own reinforcement learning models.
Read AWS DeepRacer documentation
Show steps
Provides a strong foundation for the concepts and tools used in the course.
Browse courses on
AWS DeepRacer
Show steps
-
Review the AWS DeepRacer User Guide for an overview of the platform and its components.
-
Follow the AWS DeepRacer tutorials to learn how to build, train, and evaluate racing models.
-
Explore the AWS DeepRacer API Reference to understand how to interact with the platform programmatically.
Build and train racing models in the AWS DeepRacer simulator
Show steps
Provides hands-on experience with the core concepts of reinforcement learning and autonomous driving.
Browse courses on
AWS DeepRacer
Show steps
-
Create a new racing model in the AWS DeepRacer simulator.
-
Train the model using the provided training data.
-
Evaluate the model's performance on different tracks and scenarios.
-
Tune the model's hyperparameters to improve its performance.
-
Deploy the model to the AWS DeepRacer hardware for real-world testing.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Volunteer at an AWS DeepRacer event
Show steps
Provides an opportunity to network with experts and gain practical experience.
Browse courses on
AWS DeepRacer
Show steps
-
Find an AWS DeepRacer event in your area.
-
Contact the event organizers and offer your help.
-
Volunteer for tasks such as setting up the track, managing the competition, or providing technical support.
Develop a research proposal for an AWS DeepRacer project
Show steps
Challenges students to apply their knowledge and skills to a real-world problem.
Browse courses on
AWS DeepRacer
Show steps
-
Identify a research question that you want to explore using AWS DeepRacer.
-
Develop a hypothesis and design a set of experiments to test your hypothesis.
-
Write a research proposal that outlines your project goals, methodology, and expected outcomes.
Mentor other students in the AWS DeepRacer community
Show steps
Provides an opportunity to reinforce your knowledge and skills while helping others.
Browse courses on
AWS DeepRacer
Show steps
-
Join the AWS DeepRacer community forum or Discord server.
-
Answer questions and provide support to other users.
-
Organize or participate in online or in-person meetups.
Participate in an AWS DeepRacer competition
Show steps
Provides an opportunity to test your skills and compete against other enthusiasts.
Browse courses on
AWS DeepRacer
Show steps
-
Register for an AWS DeepRacer competition.
-
Build and train a racing model.
-
Compete in the competition and try to win prizes.
Read Reinforcement Learning: An Introduction
Show steps
Provides a comprehensive overview of reinforcement learning concepts and algorithms.
View
Reinforcement Learning, second edition: An...
on Amazon
Show steps
Show steps
Show steps
- Read the first three chapters of the book to understand the basic concepts of reinforcement learning.
- Work through the exercises and examples in the book to reinforce your understanding.
- Apply the concepts you have learned to build and train your own reinforcement learning models.
Read AWS DeepRacer documentation
Show steps
Provides a strong foundation for the concepts and tools used in the course.
Browse courses on
AWS DeepRacer
Show steps
Show steps
Show steps
- Review the AWS DeepRacer User Guide for an overview of the platform and its components.
- Follow the AWS DeepRacer tutorials to learn how to build, train, and evaluate racing models.
- Explore the AWS DeepRacer API Reference to understand how to interact with the platform programmatically.
Build and train racing models in the AWS DeepRacer simulator
Show steps
Provides hands-on experience with the core concepts of reinforcement learning and autonomous driving.
Browse courses on
AWS DeepRacer
Show steps
Show steps
Show steps
- Create a new racing model in the AWS DeepRacer simulator.
- Train the model using the provided training data.
- Evaluate the model's performance on different tracks and scenarios.
- Tune the model's hyperparameters to improve its performance.
- Deploy the model to the AWS DeepRacer hardware for real-world testing.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Volunteer at an AWS DeepRacer event
Show steps
Provides an opportunity to network with experts and gain practical experience.
Browse courses on
AWS DeepRacer
Show steps
Show steps
Show steps
- Find an AWS DeepRacer event in your area.
- Contact the event organizers and offer your help.
- Volunteer for tasks such as setting up the track, managing the competition, or providing technical support.
Develop a research proposal for an AWS DeepRacer project
Show steps
Challenges students to apply their knowledge and skills to a real-world problem.
Browse courses on
AWS DeepRacer
Show steps
Show steps
Show steps
- Identify a research question that you want to explore using AWS DeepRacer.
- Develop a hypothesis and design a set of experiments to test your hypothesis.
- Write a research proposal that outlines your project goals, methodology, and expected outcomes.
Mentor other students in the AWS DeepRacer community
Show steps
Provides an opportunity to reinforce your knowledge and skills while helping others.
Browse courses on
AWS DeepRacer
Show steps
Show steps
Show steps
- Join the AWS DeepRacer community forum or Discord server.
- Answer questions and provide support to other users.
- Organize or participate in online or in-person meetups.
Participate in an AWS DeepRacer competition
Show steps
Provides an opportunity to test your skills and compete against other enthusiasts.
Browse courses on
AWS DeepRacer
Show steps
Show steps
Show steps
- Register for an AWS DeepRacer competition.
- Build and train a racing model.
- Compete in the competition and try to win prizes.
Career center
Learners who complete AWS DeepRacer Course will develop knowledge and skills
that may be useful to these careers:
Autonomous Vehicle Engineer
Autonomous Vehicle Engineer
An Autonomous Vehicle Engineer designs, develops, and tests autonomous vehicles. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and maintain artificial intelligence systems. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design, develop, and maintain computer vision systems. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Data Scientist
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer science to extract insights from data to help make better decisions.
Data Analyst
Data Analyst
Data Analysts gather, clean, and analyze data to help companies make better decisions.
Simulation Engineer
Simulation Engineer
Simulation Engineers design, develop, and maintain simulations. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Game Developer
Game Developer
Game Developers design, develop, and maintain video games. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
Software Engineer
Software Engineer
Software Engineers apply the principles of computer science to design, develop, maintain, test, and evaluate computer software.
Robotics Technician
Robotics Technician
Robotics Technicians build, maintain, and repair robots. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
DevOps Engineer
DevOps Engineer
DevOps Engineers build and maintain software development pipelines, ensuring that software is developed and deployed efficiently.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts test and evaluate software and systems to ensure that they meet quality standards.
Robotics Engineer
Robotics Engineer
A Robotics Engineer designs, builds, and tests robots that may have various uses. This course may be helpful to you as you will be introduced to the fundamentals of machine learning and reinforcement learning in a fun and engaging way through autonomous driving with AWS DeepRacer.
User Experience Designer
User Experience Designer
User Experience Designers design and evaluate user interfaces to ensure that they are easy to use and enjoyable.
Technical Writer
Technical Writer
Technical Writers create and maintain technical documentation, such as user manuals and white papers.
For more career information including salaries, visit:
OpenCourser.com/course/3atc8u/aws
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
AWS DeepRacer Course.
This is the classic textbook on reinforcement learning, and it provides a comprehensive overview of the field. It good resource for students who want to learn more about the foundations of reinforcement learning.
Save
Provides a comprehensive overview of deep learning, including the latest advances in the field. It good resource for students who want to learn more about the theory and practice of deep learning.
Provides a comprehensive overview of robotics, vision, and control. It good resource for students who want to learn more about the fundamentals of these fields.
Save
Provides a comprehensive overview of computer vision. It good resource for students who want to learn more about the theory and practice of computer vision.
Provides a comprehensive overview of deep learning with Python. It good resource for students who want to learn more about the theory and practice of deep learning with Python.
Provides a comprehensive overview of autonomous driving. It good resource for students who want to learn more about the history, present state, and future of autonomous driving.
Provides a comprehensive overview of deep learning for computer vision. It good resource for students who want to learn more about the theory and practice of deep learning for computer vision.
Provides a comprehensive overview of reinforcement learning for robotics. It good resource for students who want to learn more about the theory and practice of reinforcement learning for robotics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3atc8u/aws
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Effort
9 hours
Via
Udacity
Instructors
Blane Sundred
DeClercq Wentzel
Language
English
Good to know
Provides an overview of what you’ll be learning and doing in this course, the items that come in the AWS DeepRacer box, and teaches you how to assemble and calibrate your vehicle!
Provides hands-on experience with building, training, and evaluating your own basic racer in the online simulator!
Provides the basics of reinforcement learning, including agents, actions, environments, states, and rewards. Examines how RL is used with AWS DeepRacer, and other applications of RL
Dives into details on how parameters, hyperparameters and different reward functions can affect the racer’s performance. Allows you to enhance your racer by trying out your new skills on your own model!
Provides instructions on how to deploy your trained model onto your hardware, learn about ROS, and study the differences between simulated and real-world tracks
Teaches you how to customize your training process even further, and prepare for competing in both online and in-person AWS DeepRacer events
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