Summer AI Camps

Overview

☆☆☆ IN-PERSON / ONLINE LIVE CAMP REGISTRATION IS OPEN ☆☆☆

AlphaStar Summer AI Camp is a unique opportunity for interested and talented students to improve their Computer Science skills during summer, where students are guided and trained by expert faculty via utilizing national and international competitions in a fun and challenging environment. It consists of intensive lectures, practice sessions, exams and fun activities.

The lectures of online live courses are recorded. Students will have access to recorded sessions from an online live class.

NOTE: Registered students will receive an email one week in advance the camp regarding the necessary preparations.

AI courses are offered as half-day courses as follows:

  • 15 weekdays,
  • 3 instructional hours per day,
  • morning or afternoon
Camp 1
(Jun 8–26)
Camp 2
(Jun 29–Jul 17)
Camp 3
(Jul 20–Aug 7)
Morning Afternoon Morning Afternoon Morning Afternoon
Python – 1 Online
Python – 2 Online
Python – 1 & 2 Inperson (full day) Inperson (full day)
Intro to Data Science Inperson/
Online
Inperson
Intro to Machine Learning Inperson/
Online
In-person
Intro to Deep Learning Online Inperson

 

ONLINE CAMP SCHEDULE
Here’s the tentative schedule. All times are in Pacific Time.

Morning courses
9:00am – 10:30am Class 1
11:00am – 12:30pm Class 2
Afternoon courses
1:30pm – 3:00pm Class 1
3:30pm – 5:00pm Class 2

 

For In-Person Camp Only

NOTE: Students are expected to bring their laptops.

IN-PERSON CAMP SCHEDULE

Here’s the tentative schedule. All times are in Pacific Time.

Morning courses
9:00am – 10:30am Class 1
10:45am – 12:15pm Class 2
Afternoon courses
12:45pm – 2:15pm Class 1
2:30pm – 4:00pm Class 2

 

LOCATION

TBA (Cupertino Area)

Fees

  • In-Person:
    • $2,850 (15 full days – Python 1&2 combined)
    • $1,600 (15 half days)
  • Online Live:
    • $1,225 (15 half days)
In-person
(full day)
In-person
(half day)
Online
(half day)
Super Early
(by March 1)
$400 off $200 off $100 off
Early
(by May 1)
$200 off $100 off $50 off

Note: Super Early and Early discounts apply to the regular fee.

Available Discounts

Course Schedule

Register Now

Dates

☆ Camp 1: June 8 – June 26, 2026 (In-Person / Online live),
☆ Camp 2: June 29 – July 17, 2026 (In-Person / Online live),
☆ Camp 3: July 20 – August 7, 2026 (In-Person)

Curriculum

The students will be equipped with the necessary background in lectures and trained with different types of problems to master various problem-solving techniques. The classes are problem solving-based, project-based learning and the curriculum is aligned with USA AI Olympiad (USAAIO). Please check USAAIO Website for more information about USAAIO.

Summer vs Year-round Courses

A fundamental course can be offered in different paces in different times. Here’s the comparison of the same course offering options:

Live coursesFall / Spring TermsSummer
Paceweekly sessiondaily session
Sessions16 sessions15 sessions
Session time2 hours3 hours
Homework (average)1 hours per sessionrarely
Total workload32 instruction and practice hours +
16 hours of homework
45 hours instruction and practice
Examsin-classin-class

Levels and Courses

Below is a short description of each level. For more details and diagnostic exams, please

click for details.

Python:

In machine learning, the main programming language is Python.
CS21F-1: Programming with Python – 1
CS21F-2: Programming with Python – 2

Data Science:

This level teaches the basics of data science: how to analyze data, find patterns, and communicate insights using Python.
AI25F: Introduction to Data Science

Machine Learning:

This level teaches how core machine learning algorithms work and how to apply them in Python to real-world datasets.
AI31F: Introduction to Machine Learning

Deep Learning:

This level teaches the core building blocks of neural networks, develop intuition for how training works, and explore optimization techniques for stable learning.
AI41F: Introduction to Deep Learning

Faculty

AlphaStar Academy mainly considers teaching, competition, and education background as well as passion and dedication for the subject when hiring full-time and part-time teachers.
We hire our instructors and TAs from a pool of High School, College, Ph.D. students, school teachers, and University Professors. Our faculty have teaching/coaching/tutoring experience and have expertise in the subject area, regardless of their age.
They have participation and/or training experience in national/international math competitions and Olympiads in Math, CS, AI and Physics such as USAMO, USACO, USAAIO, USAPhO, IMO, IOI, and IPhO.
They are role models and inspiration for students with their backgrounds and achievements.

AlphaStar Summer AI Camps Faculty and guest lecturers for upcoming online/onsite camps and former camps are listed below.

  • 2025
  • /
  • Former
  • /

Fatih Gelgi, Ph.D..

  • AlphaStar Co-founder and CS / AI Dept. Director
  • Ph.D., Computer Science (in Machine Learning), Arizona State University (2007)
  • International Olympiad in Informatics (1999: Bronze Medal)
  • USA Computing Olympiad Coach (2006-2014)
  • Olympiad in Informatics Turkish National Team Coach (1999-2003)
  • Balkan Olympiad in Informatics (1998, 1999)
  • Computing Olympiad Coach (25+ years)

Salma Baig, M.A., M.S..

  • AlphaStar Instructor (since 2018)
  • Computer Science teacher (15+ years)
  • MS in Computer Science, Georgia Tech (2021)
  • MA in Education, University of London (1998)

Asuman Celik, Ph.D..

  • Adjunct Professor, U of Cincinnati (2021-present)
  • Ph.D. Candidate in Information Technology (focused on AI applications in Cancer Research, expected in 2025)
  • Ph.D. in Biomedical Informatics (2022)
  • B.S. in Computer Science (2020)
  • ACM-ICPC, Co-Coach, Contestant, 2017-2018
  • Teaching Computer Science (including machine learning and deep learning since 2017)

Fatih Gelgi, Ph.D..

  • AlphaStar Co-founder and CS / AI Dept. Director
  • Ph.D., Computer Science (in Machine Learning), Arizona State University (2007)
  • International Olympiad in Informatics (1999: Bronze Medal)
  • USA Computing Olympiad Coach (2006-2014)
  • Olympiad in Informatics Turkish National Team Coach (1999-2003)
  • Balkan Olympiad in Informatics (1998, 1999)
  • Computing Olympiad Coach (25+ years)

Salma Baig, M.A., M.S..

  • AlphaStar Instructor (since 2018)
  • Computer Science teacher (15+ years)
  • MS in Computer Science, Georgia Tech (2021)
  • MA in Education, University of London (1998)

Asuman Celik, Ph.D..

  • Adjunct Professor, U of Cincinnati (2021-present)
  • Ph.D. Candidate in Information Technology (focused on AI applications in Cancer Research, expected in 2025)
  • Ph.D. in Biomedical Informatics (2022)
  • B.S. in Computer Science (2020)
  • ACM-ICPC, Co-Coach, Contestant, 2017-2018
  • Teaching Computer Science (including machine learning and deep learning since 2017)

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