درباره مسابقه#
Online Qualifier
The Online Qualifier will be held on Friday, September 11, 2026.
Teams will work on a real-world data science challenge, and based on their performance, the top 10 teams will qualify for the onsite final.
Final Round Briefing Webinar
Teams that qualify for the onsite final will be invited to an online webinar before the final round.
During this session, the organizing committee will provide important information about the onsite competition, travel arrangements, event schedule, submission process, evaluation criteria, and other logistical details to ensure that all finalists are fully prepared for the onsite event.
Onsite Final
The Onsite Final will be held onsite on Thursday, October 22, 2026, at Pardis Technology Park, Tehran, Iran.
The participation costs for the Top 5 teams in the onsite final will be covered by the organizing committee.
The final event schedule includes:
- Welcome and introduction to the event
- Competition
- Break and refreshments
Closing Ceremony
The Closing Ceremony and Award Presentation will be held on Thursday, October 22, 2026, at Pardis Technology Park, Tehran, Iran, alongside the closing ceremonies of the other competitions in the Pardis Technology Olympics 2026.
جوایز#
✈️ Travel & Accommodation Support
The organizing committee will support qualified international teams by providing:
- Travel support to Tehran (up to $200 per person)
- Hotel accommodation during the onsite final
- Meals and refreshments during the event
🏆 Preliminary Round Awards
Top 5 Teams
The Top 5 teams will receive:
- 1st Place: $600
- 2nd Place: $450
- 3rd Place: $300
- 4th Place: $250
- 5th Place: $200
ash prizes are awarded upon participation in the onsite final.
Teams Ranked 6th–10th
- Qualification for the Onsite Final
تکنولوژیها#
In the Data Track, participants tackle real-world data science and machine learning challenges that require analytical thinking, data exploration, feature engineering, model development, and performance optimization.
The goal of this track is to evaluate participants' ability to analyze datasets, build effective predictive models, and develop practical AI solutions for real-world problems.
Participants are free to use any programming language, machine learning framework, or data science library to develop their solutions, including Python, R, TensorFlow, PyTorch, Scikit-learn, XGBoost, LightGBM, and other commonly used tools.
حامیان رسانهای#
