Program Overview
AlphaStar AI Program aims to train students towards STEM research, science fairs, prestigious STEM project competitions from regional to international level (such as ISEF, Broadcom, Siemens), ultimately the USA AI Olympiad (USAAIO) and similar prestigious AI competitions. USAAIO is a new Olympiad, potentially the most prestigious pre-college AI competition in the US. AlphaStar’s AI Program teaches Machine Learning in the right order balancing the theory and practice with real-worlds, hands-on fun projects.
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The USAAIO pathway progresses through Round 1 → Round 2 → USAAIO Camp, and the competition emphasizes both theory and programming-based AI problem solving.
AlphaStar’s USAAIO Preparation Program is designed to help students:
- build the core programming foundations for ML,
- learn how machine learning works from first principles,
- develop deep learning intuition and implementation skill,
- solve real-world machine learning problems,
- and train specifically for AI Olympiad problem formats (timed + rigorous).
Click for the details on USAAIO.
Curriculum
AI Courses can be offered in different paces at different times. Here’s the comparison of the same course offering options:
| Live courses | Fall / Spring Terms | Summer |
|---|---|---|
| Pace | weekly session | daily session |
| Sessions | 16 sessions | 15 sessions |
| Session time | 2 hours | 3 hours |
| Homework (average) | 1 hours per session | rarely |
| Total workload | 32 instruction and practice hours + 16 hours of homework | 45 hours instruction and practice |
| Exams | in-class | in-class |
Note that summer courses require a little bit less time than the year-round ones since students do the practice in class with guidance and they are more focused. On the other hand, students need more time to digest the instruction in year-round courses due to their school work or other distractions.
AI Program Levels and Course Flow
The following chart shows levels and summarizes the flow of courses in the AlphaStar AI curriculum.
AlphaStar AI Program has 5 levels some of which have basic and advanced courses as follows (click to the course codes for course details):
- Programming: In machine learning, the main programming language is Python. This level has two Python courses: CS21F-1 and CS21F-2. These courses do not require programming background.
- Data Science: This level’s course is AI25F and it is for students who finished Python courses and have a Pre-algebra level math background. The course teaches the basics of data science: how to analyze data, find patterns, and communicate insights using Python. Students also complete real projects and learn how to use AI tools to work faster and smarter. By the end, they develop projects that can be geared towards local or regional STEM project competitions.
- Machine Learning: This level’s course is AI31F. Students learn how core machine learning algorithms work and how to apply them in Python to real-world datasets. By the end, they develop projects that can be geared towards top-tier STEM competitions such as ISEF or Broadcom MASTERS.
- Deep Learning: This level’s course is AI41F. This course introduces neural networks and modern deep learning workflows. Students learn the core building blocks of neural networks, develop intuition for how training works, and explore optimization techniques for stable learning. By the end, they develop projects that can be geared towards top-tier STEM competitions such as ISEF or Broadcom MASTERS.
- AI Olympiad: There are 2 courses in this level: AI51F-1 and AI51F-2. These courses focus on theoretical grounds of AI courses and math topics required for the USAAIO. USAAIO level problems will be solved.
