For students

How do I join the national team for 2025?

The Malaysian AI Olympiad will be held in early 2025, with full details to be announced later. Participants will be invited to participate in an online quiz that covers a comprehensive range of machine learning and deep learning topics, with a focus on computer vision and natural language processing. This competition will serve as a selection funnel for the national team.

We will strictly follow the participation criteria of the international olympiads. Specific details will be updated later, but tentatively expect them to be such:

• Students must have not started university. Pre-university in Malaysia counts as Grade 12 in the K12 education system, and is thus allowed.
• Students must be less than 20 years old. 19++ years is OK, but 20 years old is not

Note that the above info is subject to change.

How can I get prepared?

Preparing for the AI Olympiad can seem daunting, given the vast and rapidly evolving landscape of artificial intelligence. On top of that, AI subjects are only taught in university curriculums! You might feel overwhelmed when starting out and that’s okay. All great journeys begin with small steps.

As a pre-requisite, you will want to be familiar with programming in Python and Jupyter Notebooks. The easiest notebook to access will be Google Colab, which is free of charge for limited usage. Otherwise, you can install Jupyter Lab on your own computer.

Next, go through common machine learning / deep learning topics and self-study them. The internet and generative language models like ChatGPT are your best friend here. Learn how to use generative language tools to guide you through new material.

Material recommendations:

• Deep Learning for Python as a structured guide to Pytorch
• Bishop’s Pattern Recognition and Machine Learning book as a reference text for machine learning
• d2l.ai for deep learning

One of wonderful things about AI is that information is readily shared. Most top papers can be read for free on arxiv.org, and seminal papers tend to have code implementations on github.com.