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AI Bootcamp - ML Basics

Thursday, February 22, 2024
All Day
Add to Cal
383 S. Hill Ave., Annex
  • Internal Event

Announcing the Third EAS AI Bootcamp: ML  Basics

We're excited to announce that the third AI bootcamp is scheduled for February 19 to 23, 2024. This session is designed for researchers who want to grasp fundamental ML concepts and explore the potential of integrating ML into their research. Following the high demand for our previous bootcamp in October, which regrettably left some interested participants unaccommodated, we are offering this repeat session to ensure more researchers can benefit from it. 

What to Expect:

  • Daily Structure: Each day will feature one to two lectures, complemented by two or more practical, hands-on sessions.
  • Topics Covered: AI fundamentals, including regression, classification, clustering, embeddings, and neural networks.
  • Objective: Our goal is to equip you with the necessary skills to incorporate ML tools into your research and to aid your ability to explore more advanced ML techniques independently.

Joining the Bootcamp:

  • Availability: Limited to 25 participants.
  • Registration: Sign up here and complete the pre-screening Python Programming Quiz before 12 PM Pacific Time on Feb 15 . Please note that your enrollment won't be complete until you have taken the quiz and have received a confirmation email from the bootcamp organizers. 
  • (Optional but highly recommended) email us about yourself and your research and let us know how you think that this bootcamp can help you with your research. 


To maximize your learning experience, familiarity with the following is required:

  • Linear Algebra: Vectors, matrices, vector spaces, matrix operations (The Matrix Cookbook), eigenvalues and eigenvectors, norms and distance metrics, linear transformation and basis.  Covered in Ma1b, ACM104
  • Multivariable Calculus: Partial derivatives, integration, limits, and continuity. Covered in Ma1ac
  • Probability Theory: Random variables, statistical measures, probability distributions, and bayesian inference. Covered in courses such as Ma3, ACM116, ACM157, ACM 158
  • Python Programming: Basic syntax and libraries. Covered in CS1.  We will cover Numpy and other important libraries during the first day. 


  • Bootcamp director Reza Sadri
  • Administrative assistant: Caroline Murphy
  • Head TAs: Alejandro Stefan Zavala and Panteleimon Vafeidis
  • TAs: Sahithi Ankireddy, Jay Siri, Kevin Do, Agnim Agarwal

Deadline for Registration: Feb 15, 2024

Computing Resources: Hands-on sessions will primarily utilize Google Colab. Should there be a need for more computational resources than the free tier of Colab provides, participants can opt for Colab Pro. We will offer reimbursements for a certain number of credits. Further details will be provided on the first day of the bootcamp.

Working on Your Own Projects: If you wish to use your own project data, please schedule an office hour with our team before Feb 15th, to ensure its suitability for the bootcamp.

For more information, please contact Reza Sadri, Director by email at [email protected] or visit