AI/Machine Learning: Foundations to Frontiers

MehtA+ student Meenu A placed first in Washington State Science & Engineering Fair with her MehtA+ final project.

MehtA+ student Jayani M was selected to present her AI/ML Research Bootcamp final project at the International Forum of Research Excellence Conference in Long Beach, California.

Jayani also presented at the International Young Researchers' Conference (IYRC) at the University of Tokyo, Japan! The final paper she wrote for MehtA+ is published with the IYRC.

Multilabel Classification of Retinal Diseases using Convolutional Neural Networks

Using Deep Q-Learning to Optimize Rocket Launch Vehicles

Multimodal Multi-label Classification for Thematic Grouping of Artworks

Solving AMC problems using Large Language Models

Enhancing AGILe with Natural Language Processing Techniques for Ancient Greek Inscription Lemmatization

Home Moguls: Feature Engineering for Automated Valuation Models

The MehtA+ AI/ML Research Bootcamp curriculum, created by MIT and Stanford engineers, is being made accessible to learners around the world.

Over the coming months, we will be publishing all 10 modules of the AI/ML Research Bootcamp on YouTube, which will cover the mathematical foundations of machine learning and deep learning, how to build AI models from scratch and how to conduct AI research.

For learners who prefer a structured, self‑paced option, our certification track provides additional homework questions, answer‑key videos, and module‑level assessments.

To support students who want extra guidance while working through the certification material, we will soon be introducing AI tutors to help learners understand concepts, review homework, and stay on track. AI tutors will focus on course comprehension and skill‑building, not research.

For those seeking the full project‑based experience of the original bootcamp, we will continue offering one‑on‑one research mentorship with MehtA+ mentors for both students and adults, including personalized research guidance, paper‑writing support, and help creating professional research posters. Mentorship students receive access to the complete library of lecture videos and homework assignments from past years, including modules not yet released publicly. If you’re interested in working directly with an AI mentor, choose the age-appropriate option below and fill out the interest form to get started.

No prior experience is required. See past projects of this camp here.

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