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Hitch2049 curriculum is curated by world-class educators to offer a premier learning experience in cutting-edge technology disciplines. Our in-depth and interactive courses build a solid foundation to elevate our learners’ technical and analytical skills to pursue future careers in fast-growing emerging markets such as AI, Robotics, VR, Metaverse, and Fintech.

HITCH2049 CURRICULUM

Artificial Intelligence Courses

1 - 1

Introduction to Python: I. Basic Programming

Our introductory coding course in Python is a departure from tedious legacy programming exercises. In this course, students will develop a solid foundation in coding for Scientific Computing and AI applications through our modern, streamlined lectures to pursue higher-level applications in Data Science, Machine Learning, and Robotics.

Instructor(s): Dr. Allen Yang

Total Lecture Time: 10 lectures

Prerequisites: N/A

Lecture 1: Introduction to Computer Programming 

Lecture 2: Python Numeric Variable Types 

Lecture 3: Strings and Text Input/Output

Lecture 4: Lists

Lecture 5: Conditions and Loops

Lecture 6: Functions

Lecture 7: Tuples and Dictionaries

Lecture 8: Sets and Hashing

Lecture 9: Classes and Object-Oriented Programming I 

Lecture 10: Classes and Object-Oriented Programming II

1 - 2

Introduction to Python: II. Data Structures and Algorithms

Students who have mastered basic programming skills will advance to study classic data structures and computer algorithms widely used in developing solutions in AI, Data Science, and Robotics.

Instructor(s): Dr. Allen Yang

Total Lecture Time: 10 lectures

Prerequisites: 1-1

Lecture 1: Basic Data Structure

Lecture 2: Debugging Skills

Lecture 3: Sorting Algorithms

Lecture 4: Queues and Breadth-First Search 

Lecture 5: Stacks and Depth-First Search 

Lecture 6: Priority Queues and A* Search

Lecture 7: Tree Structure

Lecture 8: File I/O

Lecture 9: Dynamic Programming I 

Lecture 10: Dynamic Programming II

2 - 1

Python Scientific Programming

Students will learn how to perform complex data analysis and visualization, as well as basic regression and classification in linear/nonlinear problems.

Instructor(s): Dr. Allen Yang

Total Lecture Time: 10 lectures

Prerequisites: 1-1, 1-2

Lecture 1: Numpy

Lecture 2: Visualization

Lecture 3: Vectors and Matrices I

Lecture 4: Vectors and Matrices II 

Lecture 5: Linear Regression I 

Lecture 6: Linear Regression II 

Lecture 7: Gradient Descent I 

Lecture 8: Gradient Descent II 

Lecture 9: Classification I

Lecture 10: Classification II

2 - 2

Learning Computer Vision in Python

Many modern AI theories are derived from studying computer vision problems, as the vision system is the most sophisticated perception system in the human brain. This course will teach undergraduate-level computer vision topics commonly offered at leading university engineering programs.

Instructor(s): Dr. Allen Yang

Total Lecture Time: 10 lectures

Prerequisites: 1-1, 1-2, 2-1

Lecture 1: Introduction to CV 

Lecture 2: 3D Rigid-Body Motion 

Lecture 3: Imaging

Lecture 4: Image Features 

Lecture 5: Adaptive Algorithms 

Lecture 6: Object Detection 

Lecture 7: Cascade Classifiers 

Lecture 8: Object Tracking

Lecture 9: Localization

Lecture 10: 3D Sensing

3 - 1

Introduction to Deep Learning

Students who have mastered the foundation of scientific computing and computer vision will learn the modern approach of Deep Learning in Machine Learning. This course covers basic single- to multi-layer perceptron models, deep convolutional networks, and reinforcement learning in decision-making and games.

Instructor(s): Dr. Allen Yang

Total Lecture Time: 10 lectures

Prerequisites: 2-1, 2-2

Lecture 1: Neural Networks and Perceptrons 

Lecture 2: Multi-Layer Perceptrons

Lecture 3: Convolutional Neural Networks 

Lecture 4: Deeper Neural Networks

Lecture 5: Fine Tuning and Transfer Learning 

Lecture 6: ResNet Classification

Lecture 7: Reinforcement Learning I

Lecture 8: Reinforcement Learning II

Lecture 9: Reinforcement Learning III 

Lecture 10: Reinforcement Learning IV

3 - 2

Introduction to Robotics and Autonomous Driving

This course offers an introductory robotics course with a focused application in teaching autonomous driving practices. The content of this course is comparable to upper-division courses in leading university engineering programs.

Instructor(s): Dr. Allen Yang

Total Lecture Time: 10 lectures

Prerequisites: 2-1, 2-2, 3-1

Lecture 1: Introduction to Robotics and Automation 

Lecture 2: Basic Vehicle Mechanical and Dynamic Models 

Lecture 3: PID Control

Lecture 4: Lane Following

Lecture 5: Collision Detection and Avoidance

Lecture 6: Behavior Mimicking using DNN Models

Lecture 7: Training Controllers via Reinforcement Learning 

Lecture 8: Training Controllers via Reinforcement Learning 

Lecture 9: Tuning Autopilots in CARLA Simulator

Lecture 10: Tuning Autopilots on RC Model Vehicles

HITCH2049 CURRICULUM

Metaverse Master Class​

2 - 3

Learning Unity Game Engine

By the end of this course, students new to Metaverse programming will be able to make, produce, and build their own 2D/3D projects. It will cover essential functions of Unity Game Engine, including Unity interface, GameObject components, entry-level C# scripting, interactive game audio, and importing 2D / 3D art elements (Meshes / Sprites).

Instructor(s): Eddy Hu

Total Lecture Time: 10 lectures

Prerequisites: N/A

Lecture 1: Introduction to Computer Programming 

Lecture 2: Python Numeric Variable Types 

Lecture 3: Strings and Text Input/Output

Lecture 4: Lists

Lecture 5: Conditions and Loops

Lecture 6: Functions

Lecture 7: Tuples and Dictionaries

Lecture 8: Sets and Hashing

Lecture 9: Classes and Object-Oriented Programming I 

Lecture 10: Classes and Object-Oriented Programming II

2 - 4

Unity Programming

This course introduces the fundamentals of C# programming in Unity Game Engine. From Physic engine elements such as Collider, Trigger, and Rigidbody to the concept of instantiating 3D models and bullets in the game scene, the students will learn the variety of tools essential for developing Unity Interactive projects. Students will develop a playable demo as the final assignment of this course.

Instructor(s): Eddy Hu

Total Lecture Time: 10 lectures

Prerequisites: 2-3

Lecture 1: Basic Data Structure

Lecture 2: Debugging Skills

Lecture 3: Sorting Algorithms

Lecture 4: Queues and Breadth-First Search 

Lecture 5: Stacks and Depth-First Search 

Lecture 6: Priority Queues and A* Search

Lecture 7: Tree Structure

Lecture 8: File I/O

Lecture 9: Dynamic Programming I 

Lecture 10: Dynamic Programming II

3 - 4

Foundation of AR/VR and Metaverse

This course will immerse learners in the application of AR/VR and Metaverse. The lectures will assume learners have gained basic knowledge of computer vision (2-2) & gaming programming (2-4), and will introduce the science behind immersive 3D human perception and how modern wearable technologies may accurately stimulate human 3D perception using sensors and displays. The course lays the foundation for the learners to develop future metaverse applications.

Instructor(s): Dr. Allen Yang

Total Lecture Time: 10 lectures

Prerequisites: 2-2, 2-3, 2-4

Lecture1: Introduction to AR/VR

Lecture2: Human Perception of Reality

Lecture3: Near-Eye Display Technologies

Lecture4: Rigid-Body Motion

Lecture5: Cameras and Imaging

Lecture6: Depth Cameras

Lecture7: AR Localization

Lecture8: Human Avatar Creation

Lecture9: Experiment I: Build a Metaverse in Unity3D

Lecture10: Experiment II: Build a Metaverse in Unity3D

3 - 5

Creative Design of 3D World - Next Gen Character Creation

In this course, students will learn in-depth techniques for modeling, texturing, and rendering a cutting-edge real-time character. The class will work similarly to a live mentorship as students approach the creation of AAA game characters for their portfolios. Students should expect to cover head & hair, costume elements, low-poly UVs, and processing required to get the asset real-time ready, and finish with material and texture creation to set up the final model in the engine with final images.

Instructor(s): Mikki Xu

Total Lecture Time: 10 lectures

Prerequisites: 2-3

Lecture 1: Introduction to CV 

Lecture 2: 3D Rigid-Body Motion 

Lecture 3: Imaging

Lecture 4: Image Features 

Lecture 5: Adaptive Algorithms 

Lecture 6: Object Detection 

Lecture 7: Cascade Classifiers 

Lecture 8: Object Tracking

Lecture 9: Localization

Lecture 10: 3D Sensing

AI VVIP Class

The AI VVIP Class is a tailored curriculum dedicated to the immersion and engagement of your learning experience with opportunities to earn credentials from the UC Berkeley AI STEAM program, including learning certification, an invitation to form competitive teams to participate in the ROAR competition, and, for the winning team, an invitation to publish your first technical papers on the ROAR UC Berkeley website.

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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. Successful competition of ROAR Academy summer/winter camp will receive UC Berkeley official summer camp certificate.

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Learning Journey

Once our students successfully complete our rich Hitch2049 Curriculum, they recognize that their exciting journey in science and technology innovation has just begun. Our courses give students the tools they need to succeed in the field of AI, VR, and Metaverse. Hence, we strongly encourage the students to continue the Hitch2049 roadmap and immerse themselves in the Beyond Hitch2049 Innovation Ecosystem, continuing to elevate their creative skills and develop their future careers.

AI VVIP Class Learning Journey

Entry Level Courses

Python 

(20-40 hours) Coding Principles, Data Structure, and AI Algorithm

  • Basic programming skills

Advanced Level Courses

Introduction to AI
(20-40 hours) Machine learning, Robotics Labs, and AI Racing

  • Advanced programming skills

Pre-Competition Training

Customized intensive training courses to the unique composition and background of each team member

  • Complete skillset for AI autonomous racing competition

ROAR Academy Learning Journey

ROAR Academy Summer/Winter Camp

2 weeks intensive online summer (and winter) program

  • UC Berkeley offer official free weekly seminars for eligible ROAR competition team
  • Customized training is offered through our VVIP program

Pre-Competition ROAR Team Practice

UC Berkeley offer official free weekly seminar for eligible ROAR competition team Customized training is offered through our VVIP program.

  • Prepare you to be the NEXT winning team!

Beyond the Hitch2049 Innovation Ecosystem

Berkeley ROAR Ambassador Program ​

Bringing Berkeley ROAR AI Racing, ROAR Research, and ROAR Academy experience to your K-12 schools and colleges to form your ROAR activities with our technical and financial support. Please consider joining our next-level ROAR Ambassador program and developing your leadership skills.
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Publish Your Research Papers​

By participating in ROAR, contestants worldwide will be recognized by their official scores on Berkeley’s ROAR website: roar.berkeley.edu. Teams with winning solutions will be invited to publish their code and technical papers on the UC Berkeley official website.

Indy Autonomous Challenge

Since 2022, the Berkeley ROAR program has participated in the Indy Autonomous Challenge racing competition, the world’s most prestigious Autonomous Racing Car Competition. Our most advanced students will have the opportunity to gain first-hand research and engineering skills to collaborate with a world-class racing team to become a part of the premier full-scale racing car AI competition and win $1.5 Million awards!

OpenARK AR/VR Development​

OpenARK is an open-source C++ library that implements the state-of-the-art vision perception functions for Augmented Reality applications. It is also the recipient of multiple global awards including a Microsoft Imagine Cup Global Finals Mixed Reality Award and a China Internet+ Innovation and Entrepreneurship Gold Medal in 2018. Learners who have demonstrated a promising career in developing computer vision and AR/VR technologies can join the development of OpenARK via our ecosystem.

Our Faculty

Allen photo

Allen Y. Yang, PHD

Allen Yang is an Executive Director of FHL Vive Center for Enhanced Reality & Berkeley Defi Research Initiative at UC Berkeley. 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. Lastly, Allen led the UC Berkeley ROAR team to win first place among all US teams in the Indy Autonomous Challenge.

Eddy Hu

Eddy Hu was a New York University Instructor in Advanced Game Programming and Design. Eddy is a well-known influencer in AI art & restoration and computer vision. He was the producer of AI series of film restoration videos with over 100 million views across the network and cumulative retweets of hundreds of thousands.

Mikki Xu

Mikki also teaches advanced 3D animation in the Department of Digital Art at Pratt Institute as the only Asian female professor and has nearly ten years of extensive experience in animation, visual design, game, and art education.

Teacher Assistant Team

Our TAs are undergraduate and graduate students from top global universities. Some TAs have a bilingual background and can provide guidance about course material, and their experiences excelling at top research universities.

Success Stories

“Interesting, Engaging, Challenging, Comprehensive, Fast-paced, Well-organized, Hands-on, Informative, Intensive.”

Amanda, class of 2020, Phillips Academy Andover

Phillips Academy Andover is ranked as the best private school in the US and is famous for its STEAM education, where Amanda as an alumnus of Hitch2049 VVIP program is pursuing a promising career in engineering and artificial intelligence. When Amanda was still an 8th-grade student from a Bay Area public school, she developed an intense interest in the STEAM field. Working with Hitch2049 career counselor, the program helped her to craft a precise path that best fits her goals. Our VVIP AI curriculum was particularly suitable for her because the entire learning experience could be fully customized based on her existing skill set and her own pace. This experience built a strong portfolio when she applied to Phillips Academy Andover. At Andover, Amanda continued her journey with Hitch2049, where she led a student team of five to compete in Berkeley’s ROAR Competition in 2021. Through Hitch2049’s intensive pre-competition training, Amanda’s team won ROAR’s S2-series First Place Award. Today, Amanda is certain and confident to continue her path to become a computer scientist. Hitch2049 aspires to help more students like Amanda to achieve their academic and career goals, supporting girls in STEAM to open a door to unlimited opportunities.

Zheyuan Wu, class of 2020, Yali School

Zheyuan Wu is a Hitch2049 VVIP alum from Hunan Province, China, and was admitted to the prestigious Washington University in St. Louis, one of the US private research universities known as the Hidden Ivy League. In 2020, Zheyuan started taking Hitch2049 AI curriculum with zero Python coding background. But he discovered that he really enjoys computer science and especially computer games. With the extensive training under Hitch2049 faculty, he attended the ROAR S1-series competition in the same year with his school teammates and won the Second Place in the overall ranking and a special award of Fastest Single Lap, beating even some undergraduate student teams from UC Berkeley. His success in learning further motivated him to become a TA volunteer to coach other junior students from his high school alma mater to get into learning AI early in their careers. Zheyuan’s dedication in research and his talents demonstrated through the ROAR competition persuaded Washington University in St. Louis to extend their invitation to continue his study in his dream major of Computer Science.

Peter Peng, class of 2020, Dulles High School Math and Science Academy

Peter joined Hitch2049 VVIP program as an advanced junior high school student from Houston, Texas. While being the founder of the AI Club at his school and completing the AP course in CS, his most pressing desire was to better understand the practical use of CS and AI in real life. As Peter also has a strong interest in business, practicality and product-market-fit of any technology were important to him. Hitch2049’s counselor was able to identify his pain points and provided him with a curriculum that specifically focused on the skills and knowledge of AI and machine learning in pursuit of autonomous driving applications. To further enhance his application skills, Peter as the team captain formed a competition team to compete in Berkeley’s ROAR competition, where they won ROAR’s S2-series First Place Award in 2021. Peter expressed that this journey added a valuable material to his personal resume. He also came to believe that learning AI would be a key to many future business opportunities.

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