**International Artificial Intelligence Olympiad (IAIO) — Lecture Series**

The **International Artificial Intelligence Olympiad (IAIO)** is a premier global competition that brings together the brightest young minds from across the world to compete, collaborate, and learn in the rapidly evolving field of **Artificial Intelligence.** Organized by the International Research Centre on Artificial Intelligence (IRCAI) at the Jožef Stefan Institute under the auspices of UNESCO, IAIO celebrates excellence in both theoretical and practical AI.

The Olympiad is designed to inspire innovation, deepen knowledge, and foster international cooperation by challenging participants in core AI disciplines such as **Machine Learning, Computer Vision, Natural Language Processing, and Robotics.** The competition uniquely blends rigorous academic contests with practical AI model development and solution design, encouraging participants to apply creativity and scientific reasoning to real-world problems.

**IAIO 2026 — Ljubljana, Slovenia**

The **International Winter AI Olympiad 2026** will take place **February 23–27, 2026,** in **Ljubljana, Slovenia.** This edition continues the tradition of uniting talented students from member countries to compete in theoretical and practical AI challenges and to exchange ideas with peers and experts globally.

**About These Lectures**

This video page hosts the **official lecture series** associated with the IAIO and its broader educational mission. Designed to supplement competition preparation and to support contestants’ growth in AI, the lectures include:

• **Foundational AI topics** such as supervised and unsupervised learning, reinforcement learning, and kernel methods
• **Applied sessions** on real-world ML problem solving, working with data, and building AI solutions
• **Ethics and societal impact** discussions that explore responsible AI in global contexts

These lectures are valuable resources for competitors and learners worldwide — enabling students from all countries to access high-quality AI instruction and expert insights regardless of geographic location.

Kernel methods

John Shawe-Taylor

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