About the opportunity
The International Machine Learning Competition (IMLC) is a global competition designed to help students discover how machine learning truly operates, progressing from core mathematical foundations up to contemporary research topics. Participants engage across three structured rounds: an accessible qualification round, a pre-final exam based on a recent research paper, and a comprehensive final exam. The initiative emphasizes practical understanding and accessibility, requiring no prior experience to begin. Students from over 190 countries take part, gaining foundational knowledge for future studies or careers in AI while competing for awards, honours, and a total prize pool worth $1,500.
Funding and benefits
- Compete for a total prize pool of $1,500 in prize money.
- Earn Gold, Silver, and Bronze Honours in the Final Round for participants achieving at least 50% of total points.
- Receive digital participation certificates for all entrants, with physical hard-copy certificates shipped internationally to 1st, 2nd, and 3rd prize winners.
- Gain special national award certificates for top scorers in each nation who achieve at least 50% in the final exam.
- Receive a permanent verification ID on certificates for authenticity checks.
- Access financial aid options for socio-economically disadvantaged participants to help cover Pre-Final Round registration costs.
Who can apply?
- Open to all current high school students and university students worldwide.
- Students between high school and university (such as those in a gap year) planning to start university soon are eligible.
- Participants are categorized into three age groups based on their age or grade on the Qualification Round submission deadline (13 December 2026): Junior (10th grade and below, and under 16 years of age), Youth (11th to 13th grade, or 16 years of age and older), and Senior (1st year college/university and higher, or 19 years of age and older).
- No prior machine learning experience is required to start the qualification round.
Required documents
- Completed solution file for the Qualification Round (accepted formats: PDF and picture files; Word and ZIP files are not accepted).
- Written solutions on paper, scanned and uploaded via QR code upload interface for the Pre-Final Round.
- Valid government-issued ID card or passport if utilizing the online supervision system for exams.
When to apply
- Qualification Round submission deadline: Sunday, 13 December 2026 at 23:59 UTC.
- Qualification Round results announced: Monday, 28 December 2026.
- Pre-Final Round preparation phase begins: Friday, 22 January 2027.
- Pre-Final Round exam window: Sunday, 24 January 2027 to Tuesday, 26 January 2027.
- Final Exam date: Tuesday, 23 February 2027.
- Final Round results announced: Monday, 1 March 2027.
How to apply
- Download the Qualification Round problem set from the official website.
- Solve the problems independently or work collaboratively with friends and classmates for the Qualification Round.
- Submit your solution file through the official online submission form before the deadline (no separate pre-registration required for the qualification round).
- If qualified, register for the Pre-Final Round by paying the 12 EUR registration fee (or applying for financial aid if eligible).
- Complete the Pre-Final Round preparation and take the supervised 60-minute exam either via an in-person teacher supervisor or the online supervision system.
- Select a timeslot and complete the Final Exam online portal requirements on 23 February 2027.
Additional information
- The competition is organized into six core technical areas: Fundamentals, Optimization & Generalization, Deep Learning, Frontier Models, Applications, and Trustworthy AI.
- While individual solution papers are mandatory across all rounds, group work is explicitly permitted during the Qualification Round.
- Teachers can register to track student progress, join school partnerships, and help facilitate local supervision.
Our Take on This Opportunity
This section reflects Open Opportunities’ own analysis of the opportunity from an applicant’s perspective.
You may be a strong fit if…
- An ideal match for high school or university students with an interest in data science, mathematics, or artificial intelligence seeking a structured way to build applied machine learning skills.
- Well-suited for learners who prefer a practical, problem-driven learning curve rather than passive online courses or expensive textbooks.
- A strong fit for self-motivated students looking to test their capabilities against an international peer group across 190+ countries without needing prior coding expertise.
What should you think carefully about?
- Progression requires passing increasingly rigorous evaluation rounds, culminating in timed supervised examinations that require strict adherence to rules and technical setups.
- While entry to the qualification round is free, advancing to the Pre-Final Round involves a 12 EUR registration fee, though financial aid is available for qualifying students.
- Participants must arrange either an in-person accredited school teacher or a compliant multi-device online webcam setup to supervise the Pre-Final Round exam.
How could this fit your current goals and plans?
This competition offers a valuable opportunity to benchmark analytical skills, gain international recognition, and build a strong foundation for future academic or professional paths in artificial intelligence and machine learning. Because participation is structured progressively, it accommodates both absolute beginners starting with basic school math and advanced students looking to grapple with research papers.
Our take
Students curious about artificial intelligence and eager to challenge themselves globally should seriously consider entering the qualification round. It is less suitable for individuals seeking immediate cash grants without competitive testing or those unable to meet the specific technical and supervisory requirements of the advanced rounds.
Ready to apply?
Review the opportunity on the official website before applying.
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