- Feedback and support by AI experts for international participants delivered throughout all contest program
- Cases to solve related to most popular AI Master’s courses.
- Access to the knowledge base on the Moodle platform for all registered participants
- Case solution is accepted as an entrance test to ETU LETI Masters’ Programs
- International participants get benefits of LETI’s international exchange programs. Benefits of LETI’s international exchange programs.
- LETI coins for all participants. LETI Coin is a Unit of Benefit, which you can exchange for bonuses giving you an advantage at the entrance exams and/or participation in the education programs of St. Petersburg Electrotechnical University.
Track 1 Autonomous intellectual systems
Track 2 AI in physiology and medicine science
Track 3 AI Security and Ethics
- Each track opens with the online introductory lecture.
- Contestants get cases with startup package including
o recommendations how to earn maximum scoring points
o milestones and deadlines
o evaluation criteria, etc.
- Case solutions are uploaded to the Moodle platform for the Jury evaluation. A participant can solve cases from all three tracks, the solutions are evaluated independently, and points are summed up.
- All participants get certificates with the contest themes and subject matter mentioned.
- Successfully solved cases can be accepted as tests for entrance exams
- Winners get diplomas with LETI coins, providing bonuses at the university entrance exams.
Four steps to construct autonomous drive along the Duckietown road lane. Contestants get four problems to be solved using the Duckietown simulation environment.
The case deals with the ECG signal analysis using logistic regression. One of the most pressing cardiology challenges today is to improve the quality of automated electrocardiogram (ECG) analysis. Efficient algorithms allow physicians to use long-duration recordings in order to obtain important diagnostic information about a patient's cardiac activity. Contestants solve the task of developing an algorithm, which classifies the QRS complexes into "pathological" and "healthy" categories using the method of logistic regression. The input data include ECG recordings, as well as QRS complexes positions already marked. The task is to identify features for classification, construct and optimize the model, and evaluate its sensitivity and predictive power. Register and get personal access to cases on the Moodle platform.
This case offers several cryptography and security problems, it follows the Olympiad principle. So its tasks are not interrelated, and the points are earned independently for each task. Cryptography knowledge is not needed to solve the case tasks, they are aimed at testing the logical abilities of contestants. Cryptography is currently used in all AI systems to ensure data transfer security, user authorization, access differentiation, secure data storage and user identification. These tasks give contestants an opportunity to test their analytical skills and have a practical exercise with problem solutions integrated into the today’s cryptographic applications. Register and get personal access to cases on the Moodle platform.