First International Data Analysis Olympiad to Be Held in Russia
The IDAO (International Data Analysis Olympiad), created by leading experts in data analysis for their future colleagues, aims to bring together analysts, scientists, professionals, and junior researchers from all over the world on a single platform. This is the first time an event of this scale will be held in Russia. The HSE Faculty of Computer Science, Yandex and Harbour.Space University organize the Olympiad with the support of Sberbank.
‘Our civilization is at the point where we have the technical ability to collect and store large amounts of data’, says Dmitry Vetrov, chair of the IDAO jury, HSE professor, and head of the International Laboratory of Deep Learning and Bayesian Methods at HSE. ‘But we still do not fully understand everything that can be done with these data. There is a clear need for experts in the field of machine learning and data sciences, and this need will only grow. Such olympiads are a great way to support talented young people in their quest to become experts in this field’.
However, the methods that are proposed in articles or that are used in machine learning competitions are often not effective enough to find use in real applications. Many of them work too slowly or require too much memory, which prevents them from being used in a mobile application, for example. The IDAO is prepared to answer this challenge. Participants will try to outdo each other not only as predictions, but also in the practical effectiveness of the models used.
Complex tasks in data analysis and additional requirements for a model's performance will make the IDAO attractive for both participants in machine learning competitions and for sports programming enthusiasts. Moreover, people with different training – analysts and developers, for example – will be able to serve on teams together to create more advanced and relevant solutions.
The International Data Analysis Olympiad (IDAO) consists of two stages. The first, remote online qualifying round will be held on the Yandex.Contest platform from January 15 to February 11, 2018, and will feature two tracks. The first track is a traditional competition in machine learning. Based on the submitted data with the labels assigned to them, participants will need to make new predictions and load them into the automatic verification system. The task of the second track is to develop a solution for the same problem that fits into a tight timeframe and the memory used.
The IDAO website will publish a table with the results and a list of finalists no later than February 18, 2018. Thirty teams that are ranked highest on at least on one of the tracks will be invited to compete in Moscow. The olympiad organizing committee will covers finalists’ accommodation and board expenses.
The second, onsite tour will be held in Moscow in April 2018 at the central headquarters of Yandex. Over the 36 hours of competition, participants will try not only to get up to speed on the model, but to create a full-fledged prototype that will be tested both in terms of accuracy and performance.
As part of the onsite round of the olympiad, speeches and workshops by international experts in machine learning and data analysis are also planned.
IDAO winners will receive valuable prizes. In addition, the HSE Faculty of Computer Science and Harbour.Space University will provide scholarships to the winners that fully cover the cost of their education.
On February 18, the online round of the International Data Analysis Olympiad (IDAO) officially finished. The Data analysis competition is organized by the HSE Faculty of Computer Science and Yandex with the support of Sberbank. This year 1287 teams from 78 countries took part in the online round.
The HSE Faculty of Computer Science and Yandex with the support of Sberbank are to organize the 2nd International Data Analysis Olympiad (IDAO). The Olympiad is held by leading experts in data analysis for their future colleagues and aims to bring together analysts, scientists, professionals, and junior researchers.
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