International Machine Learning Competition

A competition that tests how deeply you understand AI, over three rounds from the classical foundations to today's frontier research.

190
Countries
$1,500
Prize money
3
Rounds
fig. 1 Support Vector Machine
maximum-margin classifier
About

Understand AI.
Don't just use it.

AI is shaping the world your generation will grow up in, and understanding how it really works should not be reserved for a handful of universities. You do not need a powerful computer or an expensive course. All you need is curiosity and a willingness to think carefully. We give you the rest.

  • a.

    Learn how it actually works

    Not which button to press, but why the ideas behind AI work at all. You build up the reasoning from the ground up, so it stays with you.

  • b.

    Think it through, not just run it

    Real problems, worked out with a pen and clear thinking. You learn to spot what makes a model succeed or quietly fail, the judgement that matters most.

  • c.

    Read the research shaping today

    In the later rounds you read a real, recent paper on the AI everyone is talking about, and show that you understood it. Yes, you can do that.

You will understand this. Machine learning is harder than it looks, and we help you get there step by step.
A real question from the competition
How two attempts to train a model settle into different solutions.

The two curves show a model learning. Which attempt will handle new, unseen data better, and how can you tell just by looking? By the end of the competition, reading a picture like this will feel natural.

No experience required to start · we teach you along the way
Challenge yourself, learn the technology of the future, and compete with students worldwide. Get started
Participate

The clock is already running.

Solutions for the qualification round are due by Friday, 6 November 2026.

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Download Problems Submit Solutions

no GPUs required · open to students worldwide · financial aid available

The spectrum

From SVMs to state of the art.

Six areas, one spectrum: the fundamentals that never change and the research that changes every month. Every round draws on all of it.

T·01

Fundamentals

SVMs, logistic regression, decision trees, kernels: the classical core, derived by hand. This is the math everything else stands on.

svm · logistic regression · kernels
T·02

Optimization & Generalization

How machines actually learn: gradient descent, loss landscapes, regularization, and why models that merely memorize fail to generalize.

gradient descent · bias–variance · overfitting
T·03

Deep Learning

Backpropagation by hand, then the architectures that took over: CNNs, RNNs and the transformer, understood layer by layer.

backprop · cnn · transformers
T·04

Frontier Models

The current research edge: LLMs, fine-tuning, RAG, and the efficiency work, from quantization to distillation, that makes them deployable.

llms · rag · distillation
T·05

Applications

Where it all lands: vision, healthcare, recommender systems, science. The same methods, translated into systems people rely on.

vision · healthcare · recommenders
T·06

Trustworthy AI

Adversarial attacks, robustness, alignment and fairness: how models fail, how they get attacked, and what responsible deployment demands.

adversarial · alignment · fairness
Rounds

Three rounds over five months.

Each round raises the stakes: first the fundamentals, then a real research paper, then one final exam where everything comes together. See the full rounds & process →

R1
Qualification until 6 November 2026

Qualification Round

Start here. A set of questions on the core ideas behind machine learning, from how models make decisions to how they learn from data. Score 15/17/20 points by age group to move on to the next round.

online · solo · from home
R2
Pre-Final December 2026

Pre-Final Round

You receive a recent research paper on a topic like LLM efficiency, vision transformers or adversarial robustness, and answer questions that test whether you truly understood its method, its assumptions and its limits. You have five days. Registration is 12 EUR, and financial aid is available for anyone who needs it.

research paper · reading · written
R3
Final Sunday, 17 January 2027

Final Exam

One timed exam of 30 questions that brings everything together: the foundations, the modern models, and the judgement to reason about both. The top finishers earn awards. Results announced 23 January 2027. See all awards →

supervised · timed · awards
Teachers & Schools

Bring the IMLC to your classroom.

Register your students, follow their progress, and put your school on the leaderboard. Partner schools get reduced registration for every participant.

Teacher Account

Manage and track your students through every round, from qualification to the final exam, in one dashboard.

Register as a teacher →

School Partnership

Partner schools receive reduced registration fees for all students and a certificate shipment to the school.

Become a partner school →

Classroom Materials

Posters, problem sheets and training material to introduce machine learning thinking to your students.

Get the materials ↓
Ambassadors

Represent the IMLC in your country.

Ambassadors bring the competition to their schools, universities and communities. You spread the word, mentor newcomers, and grow a local ML community. We support you with materials, a certificate and an international network.

  • a.

    Promote

    Share the competition at your school or university and on local channels. Every registration through you counts toward your ambassador level.

  • b.

    Support

    Help participants in your region with questions about rounds, registration and preparation.

  • c.

    Grow

    Advance through ambassador levels, earn certificates and references, and join an international network of ML enthusiasts.

Newsletter

Stay in the loop.

Round openings, deadlines and results: a handful of emails a year, nothing else.