Continuing Group AI Programs for AI Scholars Alumni

AI Deep Dives are project-based intensive courses for returning students to continue building graduate-level Artificial Intelligence skills. Explore applications of machine learning models in your domain of interest, from healthcare and generative AI to deep learning. This program is designed for students who have completed AI Scholars.

AI Deep Dives Program Offerings

In the first half of the course, students learn AI’s core technologies including applications, foundational concepts, and programming tools through live online lectures and coding labs. In a multi-week final project, students apply innovative machine learning techniques to model how a self-driving car works using reinforcement learning, fight bias in criminal justice, preserve privacy in natural language processing models, detect skin cancer from photographs, or more.

Generative AI and ChatGPT

  • Module 0: Python and AI Review

  • Module 1: The Power of GPT-3

  • Module 2: Fine-Tuning ChatGPT

  • Module 3: Transformers and GANs

  • Module 4: Implement Safe and Ethical GPT

  • Module 5: Final Project

Designing Deep Learning Systems

  • Module 0: Python, CNN, and NLP Review

  • Module 1: Design Choices in Deep Learning

  • Module 2: Training Neural Networks

  • Module 3: NLP and Sequences (RNNs, LSTMs)

  • Module 4: NLP and Transformers

  • Module 5: Final Project

AI in Medicine

  • Module 0: Python, CNN and NLP Review

  • Module 1: Medical AI

  • Module 2: Medical Imaging

  • Module 3: Explainable AI

  • Module 4: Drug Discovery with AI

  • Module 5: Final Project

Deep Dives Program and Application Information

Prerequisites

High School Students (Grades 9 to 12) or equivalent.

Prior AI programming and computer science experience required. This program is designed for students who have completed AI Scholars.

Program Fees

Program Fee: USD $1200
(all inclusive)

Admitted students will be emailed a link for online payment.

Payment plans available.

Application Deadlines

Summer 2024: May 1, 2024

Applications are processed on a rolling basis. Limited seats.

Deep Dives 2024 Program Schedule

The program runs for 10 sessions of 2.5 hours each (25 hours total) of live online, small-group learning.
All times for virtual programs are listed in Pacific Time. Please adjust for your time zone.

Summer 24

Weekday Date Options:
(Monday to Fridays)
June 17th to June 28th
July 15th to July 26th
August 12th to August 23rd

Weekend Date Options
(Every Saturday & Sunday):
July 13th to August 11th

Time Options:
8AM-10:30AM PT
12:30PM-3PM PT
7PM-9:30PM PT

Meet Some of Our AI Deep Dives Instructors

  • Phil Bell

    Master’s in International Education Policy from Harvard University | Bachelor’s in History from Oxford University

  • Emily Liang

    Master’s in Computer Science from Columbia University | Bachelor’s in Economics and Computer Science from NYU

  • Peter Washington

    Ph.D. in Bioengineering from Stanford University | Master’s in Computer Science from Stanford University | Computer Science Professor at UHawaii

  • Erica Yuen

    Master’s in Computer Science from MIT | Bachelor’s in Computer Engineering from MIT

  • Ashley Francisco

    Ph.D. Candidate in Computer & Information Sciences at University of Pennsylvania | Bachelor’s in Computer Science from Dartmouth College

  • Anil Palepu

    Ph.D. Candidate in Medical Engineering & Medical Physics at MIT | Master’s in Biomedical Engineering from Johns Hopkins

Apply Now

Instructor Spotlight: AI and Healthcare

Vicky Valverde

B.S. Bioengineering, M.S. Biomedical Informatics | Stanford University

Reimagining Drug Development with AI

With a background in Bioengineering, Vicky is interested in the use of AI in drug development given its potential to redesign, streamline, and improve the traditional production of drugs.

  • “I have always had a strong interest in helping treat disease and improve people's quality of life. This led me to study bioengineering, which is at the intersection of medicine and engineering. During my undergraduate career, I realized that the field of medicine is shifting to the heavy use of artificial intelligence, which pushed me to get involved in the field.”

  • “Witnessing the improvement of my students! Many come in with no knowledge of Python or AI, and are able to code on their own by the end of the program.”