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Our students make real AI products that people can use.

By creating an AI product, our students apply what they have learned through first-hand experience of being an engineer, a product manager, or a data scientist. If you want to learn how to make these products, join us!

It will only take a min to apply. More than 5,000 students have done so.

AI Camp Product Demos

AI Identifies Celestial Bodies

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Andrew M, Arjun A, Harrison H, Lucas H, Miguel F, Vishnu M

We used Computer Vision to create an AI application that can identify celestial objects of our solar system through images.


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GitHub Repository

Crystal Vision

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Arnav S, Christopher H, Jaedyn T, Shivani M, Varini K, Winston Y

We used Computer Vision to create an AI application that can help individuals streamline rock and crystal classification.


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GitHub Repository

AI Detects Potholes

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Bryan L, Cheuk S, Londo H, Stephen T, Zi L, Zeina K

We used Natural Language Processing to create an AI application that can detect potholes from images.

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GitHub Repository

AI Navigates Streets in Your Native Language

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Antonio C, Druthi P, Hana S, Justin D, Justin W, Luke N

We built an AI to translate street signs of all shapes and sizes to your native language.

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GitHub Repository

AI Detects Wildfires

Griffin B, Manav B, Pierre Q, Smiriti D

Our product is designed to help fire fighters across the West Coast by alerting them of various fire risks.

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GitHub Repository

AI Identifies Endangered Marine Species

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Martin X, Nash W, Preston C, Ryan V, Satyam G, William S

We created this application to help identify endangered marine species in order to better protect them.

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GitHub Repository

Cloud Identification

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Andrew C, Neil G, Prarthan G, Rahul R, Yuping W

We used Computer Vision to create an AI application that can identify cloud types from images.

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GitHub Repository

AI Detects Poisonous Berries

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Audrey H, Anu T, Cedric A, Gavin D, Ronok T, Stephen K

We built an AI which can recognize the type of a berry and whether it is poisonous or not.

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GitHub Repository

AI Detects Leaf Disease

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Aasha Y, Connor B, Jaydon G, Lukas W, Surya S, Zachary B

We built an AI to classify leaves and detect whether they are diseased or healthy.

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GitHub Repository

AI Detects Corn Leaf Disease in Food

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Advay A, Disha G, Lauren P, Ronald L, Sreenidhi C, Xiaofan L

We built an application to identify the type of disease present on a corn leaf to help prevent major loss of crop supplies worldwide.

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GitHub Repository

AI Classifies Garbage

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Alan S, Amadi U, Elizabeth I, Joanna S, Taran P

We built an application to help identify objects such as recyclable items to help reduce unneeded waste in landfills.


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Github Repository

AI Detects Toxic Plants

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Allison Y, Jacqueline D, Karanvir S, Manav G, Victoria J

Our product can help national park tourists, campers, and everyday Americans determine which whether the plants they are interacting with may or may not be a threat.

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GitHub Repository

AI Classifies Garbage 

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Allister D, Harshith S, Isaiah R, Javier G-T, Safeeyah H, Zac B

We built an application to visually detect various types of waste and whether it should be recycled or not.


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GitHub Repository

AI Detects Bleached Coral

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Brandon L, Julio B, Kai K, Marissa T, Siddharth P

We built this application to increase coral bleaching awareness and protection of the coral reefs by providing a product to easily identify if a coral reef is bleached or not.

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GitHub Repository

Self-Driving Cars Perception

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Anant A, Arnold Z, Jiankai F, Ramona C, Sophia M

We used Computer Vision to find out if that plant on your hiking trial is poisonous!


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Alexander Z, Cathy T, Riley C, Samantha S, Siddhant H

Self-driving cars are complex - one of the most important components of them is the perception module. Here we created and trained an application that can recognize street signs such as stops signs and traffic lights.


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Join us, make something cool,
and be ready for the future.

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Bernice Lau

"My experience at AI Camp was very insightful and rewarding. I'm really grateful to have had this opportunity because I was not only able to expand my knowledge in Python, but I was also able to implement machine learning and AI training models to large-scale products in a fast-paced environment, all while developing valuable skills at the same time."

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Kai Karadi

"My favorite part of the classes was the lecture that Richard gave... about precision, recall, and evaluation. He went at the perfect pace for me and his use of examples really solidified my understanding. Without the fraud example, I don't think I would have understood the difference between precision and recall, nor why each was important in different settings."

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Lauren Park

"I really enjoyed the lectures on training neural networks! Learning about back propagation was really interesting and I hope to learn about the math formulas after taking calculus. My favorite part of the class was coding the buttons and other things with flask for my team's project website. Even though it was confusing at times, it was a fun challenge!"

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Jack Lieberman

"I liked the interactive piece during the lesson. I also liked learning about linear regression because I learned about it in school, but not with some of the technicalities about it and definitely not with anything code-related."

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Sidharth Mandava

"I liked our expansion of pandas, although it was somewhat difficult. I will probably review over the weekend, to make sure that I am at a good place to continue learning next week. I also liked the lecture on using data to make career decisions... that will be helpful to me in the future."

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Zihan Wang

"I loved that I actually got to do some hands on coding on assigning vectors to tokens and gain a deep understanding of how neural networks work. [I was also] able to thoroughly understand why clearing up data is so important for Artificial Intelligence."

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