About the USA AI Olympiad
USAAIO is a K–12 artificial intelligence olympiad for students in the United States and Canada. It runs an annual two-round contest — an online qualifier followed by an in-person final — and selects Team USA for the International Olympiad in Artificial Intelligence (IOAI) and the International AI Olympiad (IAIO).
Format
| Round | Where | What it tests |
|---|---|---|
| Round 1 — Online qualifier | Remote, judged via uploaded notebooks & auto-graded tasks | Math foundations, Python data wrangling, classical ML, basic deep learning |
| Round 2 — In-person final | University venue (recent: Harvard, MIT) | Multi-hour modeling problem on a real dataset; theory questions; reproducibility deliverables |
Exact dates each cycle are posted at usaaio.org. The 2027 cycle registration opens in June 2026.
Eligibility
- K–12 students in the United States or Canada.
- No prior contest experience required to register.
- Self-study is the typical path; many qualifiers are self-taught from courses + practice.
Allowed tools
- Language: Python (3.x).
- Required libraries: NumPy, pandas, matplotlib, seaborn, scikit-learn, PyTorch.
- Forbidden: pre-trained model weights (in most rounds) and external network access during the contest.
Topic coverage
The official syllabus is organized into roughly five strata. Each one has a dedicated page on this site.
Foundations
Linear algebra (vectors, matrices, eigen-decomposition), probability and statistics, multivariable calculus, convex optimization.
CodePython & the data stack
NumPy arrays, pandas DataFrames, matplotlib / seaborn for plots, scikit-learn for ML APIs.
Classical MLSupervised & unsupervised
Regression, classification, ensemble methods, cross-validation, clustering, dimensionality reduction.
Deep LearningNeural networks
Multi-layer perceptrons, standard layers, forward / backpropagation, training loops, regularization, optimizers.
Modern AITransformers & applications
Attention mechanism, transformer blocks, NLP (tokenization, embeddings, pre-train / fine-tune), vision (CNNs, detection, autoencoders, GANs, diffusion).
Scoring & promotion
- Round 1 is auto-graded against hidden test cases / metrics. Cutoff varies year to year.
- Round 2 combines a leaderboard score on the contest problem with a theory short-answer section. Final ranking is a weighted blend.
- Team USA selection: top finishers from Round 2 are invited to a training camp and selected for IOAI / IAIO.
Why this olympiad is worth your time
- End-to-end ML practice. You learn to take a dataset from messy CSV all the way through a deployable model — exactly the skill the rest of your AI career will demand.
- Forces you to actually understand gradients. Treating PyTorch as a magic black box doesn't survive the final-round theory section.
- Direct international path. IOAI exists, the field is young, and getting onto Team USA at Grade 11–12 is a real possibility for a Grade 9 student who starts now.
- Transferable. Whether or not you ever compete again, the syllabus is a clean curriculum for anyone serious about ML.