Purpose
Identify students with strong AI aptitude and problem-solving skills.
Format
Online tests
Duration
2–3 hours.
Content Areas
AI Fundamentals
Basic concepts, history, and applications.
Mathematics for AI
Probability, statistics, linear algebra, calculus (basic to intermediate level).
Algorithms & Data Structures
Core algorithms, complexity, sorting/searching, graph theory basics.
Machine Learning Basics Supervised/unsupervised learning, model evaluation, bias & fairness.
Ethics in AI
Data privacy, fairness, societal impact.
Purpose
Choose the final UK team for the International AI Olympiad Finals.
Format
On-site challenge with a mix of theoretical and project-based tasks.
Duration
1 day.
Content Areas
Advanced AI Concepts
Neural networks, deep learning, reinforcement learning basics.
Programming for AI
Python programming, NumPy, pandas, scikit-learn, TensorFlow/PyTorch basics.
Practical AI Challenge
Data preprocessing, model building, optimisation, and presentation.
Innovation & Creativity Task
Team-based problem-solving with real-world AI applications.
Communication Skills
Presenting AI solutions to judges and peers.