Marko Mihajlović and Nikola Popović testimonial

We had high hopes for the seminar, but we never expected that we would end up with a scientific paper and a best-paper award at a student conference.

The topics covered in those 10 days are not usually covered by most faculties. You will not be able to grasp most of the details in those topics. Nevertheless, you will get something much more valuable – intuition about those techniques, comments of industry experts on how to use them, the kind of comments you don’t find in books, and hands-on experience through workshops. They will tell you which techniques are used in modern systems through intensive lectures and workshops. Most of the lectures do not require prior knowledge in ML, but fundamental knowledge in algorithms and mathematics is required.

After about a half of the seminar, a very important phase begins – working on a project under the mentorship of a lecturer. You need to choose a topic, whether a recommended one or your own idea – specifically, we have worked on a recommended topic “Adversarial Examples”. An adversarial example is an input to a Machine Learning model that is intentionally designed by an attacker to fool a model into producing an incorrect output. We were pleased with what we did during the seminar, so we decided to continue working on it afterwards. We wrote a scientific paper summing up the results we achieved (https://github.com/Maki94/cnn_adv_examples), got submitted to the IEEESTEC student conference in Nis and won the best-paper award.

The most important part of the seminar is the people. There, you have a great opportunity to grow your professional network and make new friends by meeting a handful of hardworking and talented participants and lecturers. The two of us achieved collaboration and a great friendship after the seminar, while living in different cities, 200 kilometers apart.

We strongly encourage everyone to apply for the seminar because ML, the most promising subfield of Artificial Intelligence, is being used more and more in all walks of life. It is a challenging field and it is very interesting for research.