ROAR Academy Summer/Winter Camp
ROAR Academy is a rigorous and intensive two-week program for high school students who have demonstrated an aptitude for academic and professional careers in science, technology, engineering, arts, and mathematics (STEAM) subjects. Talented and motivated high school students who are entering 10th-12th grade in the Fall have the opportunity to work with UC Berkeley faculty, researchers, and scientists while focusing on learning about Python programming and introductory autonomous driving algorithms.
ROAR Academy x Hitch Interactive
Hitch Interactive is an exclusive partner of UC Berkeley’s Robot Open Autonomous Racing (“ROAR”) Academy. Additionally, ROAR Academy x Hitch Interactive offer an exclusive session in the summer of 2023 for qualified students. All students outside of California must apply through Hitch Interactive. By attending ROAR Academy, students will immerse their learning experience with the Berkeley AI STEAM program and develop a skillset for the ROAR competition. Those with the mindset to win top awards from the competition can continue their studies through our VVIP Class.
Application
Eligibility:
(Merit-based admission)
- 9th grade or above
- Proficiency in setting up online user accounts at Kaggle.com and Github.com
- Proficiency in managing a computer’s file system, preferably know about the Terminal environment
- Have entry to intermediate computer programming experience, such as on BASIC, Scratch, C/C++, and Java
- Familiar with the coding concepts of variables, loops, conditions, and functions
A complete application consists of:
- Application
- Unofficial Transcript
ROAR Academy Summer/
Winter Camp Details
The students through this 10-day program will be expected to learn sufficient knowledge to participate in ROAR competition entirely in software simulation, dubbed the S2 series for K-12 students (compared to the current S1 series that includes college students and professional learners).
Thanks to ROAR virtualization software and other open-source Python and AI libraries, learners may attend the Academy through online lectures for 2024.
Program Goals
ROAR Academy aims to support students in their exploration of engineering as a career path, provide an in-depth and interactive overview of engineering majors, programming, hardware, and software design, and allow students to use this experience in college applications.
– Design innovation via hands on learning
– Learn new skills in coding, programming, hardware and software design
– Engineering applications for the real world
– Exploration of engineering topics
Program Content
Introduction To Python Programming
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built-in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development and for use as a scripting or glue language to connect existing components. Python’s simple, easy-to-learn syntax emphasizes readability and reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms and can be freely distributed.
Introduction To Machine Learning
Machine learning is an application of artificial intelligence (AI) that allows systems to learn and improve from experience without being explicitly programmed automatically. Machine learning focuses on developing computer programs that can access data and use it to learn for themselves.
Introduction To Autonomous Driving
The continuing evolution of automotive technology aims to deliver even more significant safety benefits and automated driving systems (ADS) that — one day — can handle the whole task of driving when we don’t want to or can’t do it ourselves. Fully automated cars and trucks that drive us, instead of us driving them, will become a reality.
Introduction To Reinforcement Learning
Reinforcement learning is an area of machine learning concerned with how intelligent agents should take actions in an environment to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised and unsupervised learning.
Program Schedule
– Class hours will be online from 9AM – 3PM (PST)
– Virtual Engineering and Programming class
– Live virtual hours to help with ROAR project
Sessions (Choose one session)
| Sessions | Week 1 | Week 2 |
|---|---|---|
| Session 1 (Full) | June 26 - June 30 | July 3 - July 8 (skip July 4th) |
| Session 2 (Full) | July 10 - July 14 | July 17 - July 21 |
| Session 3 (Full) | July 24 - July 28 | July 31 - August 4 |
| Session 4 (China Session) | August 7 - August 11 (GMT+8) | August 14 - August 18 (GMT+8) |
Sessions (Choose one session)
| Sessions | Week 1 | Week 2 |
|---|---|---|
| Session 1 (Full) | June 26 - June 30 | July 3 - July 8 (skip July 4th) |
| Session 2 (Full) | July 10 - July 14 | July 17 - July 21 |
| Session 3 (Full) | July 24 - July 28 | July 31 - August 4 |
| Session 4 (China Session) | August 7 - August 11 (GMT+8) | August 14 - August 18 (GMT+8) |
Schedule
| Day 1 | Day 2 | Day 3 | Day 4 | Day 5 | |
|---|---|---|---|---|---|
| 9 AM - 10:30 AM | Introduction to Python Programming | Strings and Text Input/Output | Conditions and Loops | Turples and Dictionaries | Classes and OOPI |
| 10:30 AM - 11 AM | Q&A | Q&A | Q&A | Q&A | Q&A |
| 11 AM - 12:30 PM | Numeric Variables | Lists | Functions | Sets and Hashing | Classes and OOP II |
| 12:30 PM - 1:30 PM | Lunch Break | Lunch Break | Lunch Break | Lunch Break | Lunch Break |
| 1:30 PM - 3 PM | Python/Kaggle Setup | Coding Exercises | Coding Exercises | Coding Exercises | Coding Exercises |
| Day 6 | Day 7 | Day 8 | Day 9 | Day 10 | |
|---|---|---|---|---|---|
| 9 AM - 10:30 AM | Numpy | Vectors and Matrices | Introduction to Machine Learning | Introduction to Autonomous Driving | Introduction to Reinforcement Learning |
| 10:30 AM - 11 AM | Q&A | Q&A | Q&A | Q&A | Q&A |
| 11 AM - 12:30 PM | Visualization | Gradient Descent | Tuning Deep Neural Networks | PID Control for Lane following | Training Controllers using Gym |
| 12:30 PM - 1:30 PM | Lunch Break | Lunch Break | Lunch Break | Lunch Break | Lunch Break |
| 1:30 PM - 3 PM | Debugging in IDE | Using Git and GitHub | Setup Neural Simulator | ROAR S2 Racing Practice | ROAR S2 Racing Final |
Our Mentors
Allen Y. Yang, PHD
Executive Director FHL Vive Center for Enhanced Reality @ UCBerkeley
Allen was born into a family of educators and started learning coding on Apple II since 6 years old. After graduating from University of Illinois specialized in computer vision and machine learning, he has been an innovator in Bay Area in the past 17 years. At UC Berkeley, he founded the AR/VR and autonomous driving degree programs, and he advises more than 100 undergraduate and 20 graduate students annually. He also guest lectured at Haas Business School and for Fortune 500 CEOs. At Silicon Valley, he has co-founded three startup companies and was the chief designer and technician of two AR/VR smart glasses. He co-authored 20+ patents and 100+ publications.
Student Review
“ROAR is a great way to gain insight into the vast realm of autonomous driving. As a student, I learned a lot about computer vision, perception, and control. Additionally, the team is helpful and provides great guidance and support. I would highly recommend ROAR to anyone interested in autonomous driving and racing.”
– Ritika Shrivastava
“ROAR offered me hands-on experience in autonomous vehicle research, even when I had little experience to begin with. The development platform is well-built and contains algorithms for you to try. You only need a small amount of code to start racing!”
– Christian Reyes