AI Bootcamp XIV - Foundational Models

AI bootcamp XIV is scheduled for March 2nd to March 6th,  2026 in Resnick 120 . This one week course will help graduate students and researchers gain an understanding of foundational models, including: large language models (LLMs), generative models, retrieval augmented generation (RAGs), and reasoning using machine learning.

What to Expect:

• Daily Structure: Each day will feature one to two lectures, complemented by two or more practical, hands-on sessions. We will also have short talks either by participants or other people describing their experience with foundational models
• Topics Covered: large language models (LLMs), generative models, retrieval augmented generation (RAGs), and reasoning using machine learning. 
• Objective: The goal is to equip participants with the knowledge to start applying these concepts in their research or to continue exploring them through regular classes or self-study.

Certificates:  Participants who complete all hands-on assignments will receive a certificate. To be eligible, participants must attend all hands-on sessions and actively work on the assignments during class. If an assignment is not completed during the session, it may be submitted afterward; however, attendance and in-class participation are required.

Prerequisites: To get the most out of this bootcamp, familiarity with the following topics is required:

• Machine Learning Basics: Linear regression and classification, neural networks, ability to build and use models, and familiarity with frameworks like PyTorch or TensorFlow.
• Linear Algebra: Vectors, matrices, vector spaces, matrix operations, eigenvalues and eigenvectors, norms and distance metrics, linear transformations, and basis. (Covered in courses like Ma1b, ACM104)
• Multivariable Calculus: Partial derivatives, integration, limits, and continuity. (Covered in courses like Ma1ac)
• Probability Theory: Random variables, statistical measures, probability distributions, and Bayesian inference. (Covered in courses such as Ma3, ACM116, ACM157, ACM158)
• Python Programming: including NumPy, Pandas, and one of the main ML frameworks such as PyTorch. Certificates:

How to Join the Bootcamp:

• Availability: Limited to 20 participants.
• Registration: Sign up using this link and complete the pre-screening Quiz by Feb 25th, 2026. Please note that your enrollment will not be finalized until you have taken the quiz and received a confirmation email from the bootcamp organizers. Note: since the new quiz covers more topics that our previous quizzes, please make sure to take the quiz even if you have taken AI Bootcamp quizzes before. 
• Optional (but highly recommended): Email a short description of your background and research interests, and explain how you expect this bootcamp to support your work. If qualified applications exceed capacity, priority will be given to applicants who submit this statement.

Contact: 

• Bootcamp Director Reza Sadri
• Administrative assistant: Caroline Murphy
• TAs: Sabrina Wahler, Jinyan Zhao, Volkan Gurses, Manal Sultan, Vishal Yalla, Aditya Pillai

Computing Resources: Hands-on sessions will primarily utilize Google Colab. Participants who need to use larger Colab instances for the hands on sessions will be reimbursed for up to 20 dollars.