Register

UKAIO 2027

How selection works

UKAIO is the official UK national competition within the International AI Olympiad. It identifies the students who will represent the United Kingdom at IAIO 2027, through two phases of theoretical and practical AI challenges.

Phase 1

National Qualifiers

The first phase identifies participants who demonstrate exceptional capability and the potential to represent the UK on the world stage.

First Selection Round

Phase 2

UK Delegation

The second phase determines the UK Delegation: the final team selected to compete at the International AI Olympiad Finals and showcase the nation's talent in artificial intelligence.

Training camp & interviews

Syllabus

What the competition covers

UKAIO follows the syllabus of the International AI Olympiad. Problems combine mathematical reasoning with practical programming in Python. The ten topic areas are:

  1. Data Preparation

  2. Supervised Learning

    • Regression models
    • Classification: decision trees, SVMs, naïve Bayes
    • Regularisation, overfitting and cross-validation

  3. Unsupervised Learning

    • Clustering: k-means, hierarchical, Gaussian mixtures
    • Dimensionality reduction: PCA, t-SNE

  4. Reinforcement Learning

    • Markov decision processes and Bellman equations
    • Q-learning, temporal-difference learning, exploration vs. exploitation

  5. AI Search

    • Uninformed search: BFS, DFS, uniform-cost search
    • Informed search: A* and heuristics, minimax

  6. Logical Reasoning

    • Propositional and first-order logic, CNF, unification
    • Resolution, satisfiability and SAT solvers

  7. Evaluation of ML Models

    • Precision, recall, F1, ROC-AUC
    • Bias–variance trade-off, k-fold cross-validation

  8. Constraint Satisfaction Problems

    • Backtracking and constraint propagation
    • AC-3, forward checking

  9. Kernel Methods

    • Margin maximisation, soft- and hard-margin SVMs
    • The kernel trick, RBF kernel

  10. Recommender Systems

    • Collaborative and content-based filtering
    • Hybrid systems, matrix factorisation, neural approaches

Source: iaio-official.org. The authoritative syllabus is maintained by the IAIO International Scientific Committee.

Preparing

Where to start

  • Work through the syllabus above and make sure you are comfortable with probability, linear algebra and basic calculus.
  • Practise Python, including NumPy, pandas and scikit-learn.
  • Try the past practice tests and browse our free learning resources.
  • Build small AI projects to sharpen your problem-solving.

Register for UKAIO 2027 →