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AI Fundamentals

Build projects utilizing AI and learn the fundamentals of machine learning, the technology that powers self-driving cars to ChatGPT.

New to coding? We recommend our Python Bootcamp.


Featured Projects

Build real-world applications of AI, ranging from healthcare to climate change using the latest techniques and libraries. 

Program Overview


Fundamentals: Gain a comprehensive understanding of machine learning and AI, with an emphasis on modern deep neural networks.

Portfolio Building: Cultivate an impressive portfolio of AI projects to showcase your technical prowess and creativity for college applications and internships. 


Hands-on Experience: Engaging, real-world projects and individualized mentorship with our low student-instructor ratio in a dynamic classroom.

Expert Instruction: Developed and taught by former Berkeley EECS and Stanford CS instructors and software engineers with professional pedagogy training.


Program Dates:

Spring A: 12 weeks: February 4 - April 21. Sundays, 3:30-5:30 pm PT

Spring B: 12 weeks: March 16 - June 1. Saturdays, 1-3 pm PT

Summer A: 3 weeks: June 3 - June 20. Mon-Thurs, 10am-12pm PT

Summer B: 3 weeks: June 24 - July 11. Mon-Thurs, 1-3 pm PT

Summer C: 3 weeks: July 15 - August 2. Mon-Thurs, 10am-12pm PT

Class Format: Meetings are fully online and held over Zoom. Each class is 2 hours long.

45 minutes: Instructor lecture and group problem-solving to reinforce concepts

75 minutes: Project development with instructor mentorship to apply concepts.

Additionally, there are optional projects throughout the week and support from our instructors on our Slack community.

Program Fee: The total cost of the program is $1450. A limited number of need-based scholarships are available.

Career Advancement

University advice: Join an ambitious community of career-oriented students and receive mentorship from top students at Stanford and Berkeley about the college application process as a CS major.

Career advice: Hear first-hand from software engineers at big tech companies on life as a software engineer, how to successfully apply for internships, and more.

Our AI Team

We are a dedicated team of former CS instructors and AI researchers from Stanford and Berkeley.

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Kevin Zhu

Program Director and Instructor

Former UC Berkeley Instructor | Software Engineer at Palantir | Quant at Citadel

Kevin taught 3000+ Berkeley students during his tenure as a lecturer for CS198-112 and 5-time Head GSI, specializing in upper-division algorithms. He has also taken software engineering roles at Palantir and various startups, and ML research roles at Citadel, Goldman Sachs, and Berkeley RISE Lab, where he applied traditional machine learning techniques to the stock market and researched techniques for improving convolutional neural network inference efficiency. Kevin now serves as the lead director for the Algoverse programs, as well as an instructor.

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Thomas Lu

AI Research Mentor

AI Research at CMU | Former AI Research at Tiktok | Berkeley AI Research

Thomas conducts AI research at Carnegie Mellon University as a Master's student in machine learning. He is a co-author of "Learned Incremental Representations for Parsing", which earned the highest distinction of Best Paper at ACL 2022, the premier NLP conference (reference). He has previously researched at Berkeley AI Research, MDI, and Tiktok. Thomas completed his bachelor's at UC Berkeley, triple majoring in CS, data science, and linguistics with a 4.0 GPA.


Sean O'Brien

AI Research Director

AI Research at UCSD | Former AI Resident at Meta | Berkeley AI Research

Sean conducts research on large language models like GPT-4 as a PhD researcher at UCSD. While an AI resident at Meta, he researched language model decoding methods and co-authored Shepherd, a small language model that generates critiques matching the quality of ChatGPT. Previously, at Berkeley AI Research (BAIR), he specialized in transformer architectures for strategy learning. Sean was also a 7-time GSI at Berkeley, teaching introductory programming, discrete mathematics, and upper-division machine learning, while triple majoring in EECS, math, and cognitive science.

*Note: Instructors are tentatively scheduled and subject to change. 


Secure your spot in our acclaimed AI bootcamp. Create impactful AI projects under the mentorship of expert instructors and learn neural network fundamentals.

Enrollment: Enroll with a $50 deposit, refundable upon program completion. Choose weekly payments or a one-time tuition fee of $1450, billed at program start.

Cancellation/Refund Policy: Full refund up to 21 days prior to the start of the program. No refunds are available thereafter.


Referral program: Receive a $200 fee reduction for each student you refer to our program, or if you enroll with a friend. Terms.

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