Program Overview

The 10-day bootcamp exposes students to fundamental AI concepts, and helps students build a mentor-led socially impactful AI project.

Meet the team that created the program here

PRerequisites

No prior programming or CS background required, but an interest in AI is appreciated.

Students with programming experience will be placed in an advanced batch.

Prior to the camp, a survey will be sent to help place participants in the appropriate batch based on background and project interests.


STUDENT OUTCOMES

AI Project: Students present their project to parents and guests on the final day. They complete a shareable digital poster and receive suggestions on taking the project forward.

Certificate of Achievement: Students are awarded a certificate for the successful completion of the camp on the final day, signed by our faculty and advisors.

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Admissions

Application open for select batches.

Some of our batches are currently full, you may apply for an open batch or add yourself to the waitlist for a batch that is full.

Applications are processed on a rolling basis, and students will hear back within 3 days of applying. 

Program Fees: ₹75000
Admitted candidates will receive payment details by email.


tEACHING philosophy

The curriculum, designed and taught by Stanford AI academics and alumni, encourages experiential learning.

Student teacher ratio of 12:1 to provide a personalized learning experience.

Stanford design-school inspired approach to stimulate creative thinking.

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INSPIRE

Skills developed: Understanding of AI applications

Explore transformative computer vision applications powering autonomous driving, facial recognition, and more.

Engage with natural language processing discoveries powering Alexa, Siri, machine translation and chatbots.

 

IMBIBE

Skills developed: Conceptual knowledge of AI techniques

Study foundational concepts of machine learning as well as modern deep learning techniques (neural networks).

Understand how AI could be applied to solve real-world problems in healthcare, education, agriculture, and beyond.

 

IMPACT

Skills developed: Coding an AI for Social Good application

Implement AI models for Computer Vision and NLP applications using Python and additional libraries.

Apply learnings to build a shareable AI for Social Good project under the guidance of a Stanford mentor.

See the detailed program schedule here.

 

 
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COLLEGE PREPARATION WORKSHOPS

College Essay Workshop: Receive guidance from mentors who will analyze successful Stanford essays and provide tips on communicating your own story.

CS & AI in College: Learn about the best courses to take and projects to undertake to prepare for admission to a top-ranked CS program in the US.

AI Entrepreneurship Challenge: Engage in an experiential session on pursuing AI ventures and compete in an ideation competition.


AI for Social Good Project

Projects will draw inspiration from topical examples such as the ones below!

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AI for Eye Disease Diagnosis

Diabetic retinopathy is a dangerous eye condition that can lead to blindness if untreated. Detecting the disease typically requires a specialist eye doctor, and only 11 eye doctors exists for every 1 million people in India*. The use of computer vision based Artificial Intelligence models can automate this process allowing significantly more patients to be screened. We would work with deep learning models for detecting various health conditions.

*Source: New York Times

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AI for Distracted Driver Detection

According to the National Highway Traffic Safety Administration (NHTSA) 3,450 people were killed in 2016 due to motor vehicle crashes involving distracted drivers. Innovations in Smart Car trends using AI allow distracted driver detection through a dashboard camera that can alert drivers in dangerous situations (e.g. when falling asleep). We would build deep learning models that allow us to accomplish such tasks.

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AI for Identifying Crop Disease

Crop disease detection plays a vital role in ensuring farmer security. Unhealthy crops can lead to poor yields, and often leave farmers in a devastating predicament. Using computer vision on plant imagery, farmers can automatically predict whether a plant is diseased or not. This project would guide students to build a computer vision model to do so.

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AI for Disaster Relief Improvement

Natural disasters like floods, earthquakes, etc. are times when aid needs to be provided urgently. Due to the volume of SMS messages, Tweets, Facebook posts, and newspaper articles, it can be a significant challenge to process these requests in a timely manner. The speed of processing can be the difference between life and death. AI models can be used to efficiently determine whether a message is actually a request for aid, and if so, can accurately classify the aid as food, clothing, water, etc. so that requests can be appropriately routed.