The Machine Learning Bootcamp Exclusively for high-school students. Taught by Stanford lecturers and TAs.
Accelerate your journey into machine learning.
In an increasingly tech-dominated world, machine learning is fast becoming the future. In the last 5 years, the number of jobs in machine learning has increased tenfold!
We are a group of lecturers, TAs, and graduate students from Stanford University interested in helping develop the next generation of ML scientists. We are excited to offer intensive 2-day bootcamps on a variety of ML topics to jump-start your machine learning skills. Registration is live for our Winter 2018 bootcamp.
Who is it for?
The bootcamp is for high school students with at least 1 course of programming experience, or equivalent.
When is it?
The bootcamp is scheduled for the December 1st weekend. It runs from 8:30am to 3pm, Saturday and Sunday.
Where is it?
The bootcamp will be held in the Cubberley Community Center in Palo Alto. We will be in room A6.
Build skills that you can apply anywhere.
Students will learn the fundamental principles behind machine learning, specifically focusing on supervised learning. These principles include featurization, model evaluation, parameter tuning, regularization, and much more.
In addition, students will become familiar with a variety of Python libraries, such as NumPy, Scikit-learn, and Keras. A more detailed curriculum as well as optional pre-bootcamp reading will be sent to all registered participants the week before the bootcamp.
Ready to secure a spot for our next bootcamp? Register with the link below.
During the bootcamp, students will be provided with a variety of open-source and proprietary datasets. Some of the projects may include predicting malignancy of tumors based on breast cancer data, detecting bias in natural language text, and predicting a customer's future purchases based on their shopping history.
During the second day of the bootcamp, we will also allow students to develop their own projects and receive feedback on their ideas.
For information on opportunities after the bootcamp, see our FAQ.
Spots are limited to maximize individual instruction.
Early-bird signups close.
The early-bird promotion ends Thursday, November 1st at 11:59 PM.
Registration closes permanently on Monday, November 26th at 11:59 PM.
Logistics emailed out.
All logistics for the bootcamp will be emailed out the Wednesday prior to its start. This will include specific instructions for finding the location, as well as recommended review material to prepare for the bootcamp.
The A4 Bootcamp begins!
Meet our team of Stanford lecturers, graduate students, and teaching assistants.
Nicholas Hirning Hometown: Seattle, WA Undergrad: Math/Physics Masters: AI/Systems Worked At: Amazon Fun Fact: Worked as a private tutor for Seattle Public Schools and developed part of the middle school curriculum.
Nitya Mani Hometown: Saratoga, CA Undergrad: Math Masters: CS Theory Worked At: Jane Street Fun Fact: Grades for the Stanford math department and privately tutors advanced math topics.
Shreya Shankar Hometown: Bryan, TX Undergrad: CS Masters: AI Worked At: Google Brain Fun Fact: Has served as the head TA for Stanford's intro CS course and published several key papers in machine learning fairness at the NIPS conference.
Reese Pathak Hometown: Portland, OR Undergrad: CS Masters: AI Worked At: DE Shaw Fun Fact: Serves as a lecturer for the Stanford convex optimization course as well as a TA for the linear algebra and intro ML courses.
High-quality instruction, accessible curriculum, and all at a reasonable price.
Registration fee for one student (excluding Stripe processing fees).
Get 15% off if you refer a friend! Discounts will be refunded to your card. Maximum discount capped at 15%.
If your friend has already signed up, enter their name in the signup form to get 15% off. Discounts will be refunded to your card. Maximum discount capped at 15%.
Need-based financial aid may be available upon request. Contact us via email for more details.
Ready to jumpstart your machine learning skills? Register now to reserve your spot!