Sigma Software University has started Data Science Summer School for students of Lviv Polytechnic National University. The program involves the study of key concepts of machine learning, their application in practice, interactive work on practical tasks and on your own project in groups.
The first lecture of the Sigma Software Data Science Summer School program took place on July 22. 20 third-year students of the Department of Artificial Intelligence Systems, majoring in Computer Science, participated in the School. The course lasts five weeks, during which participants must build a strong foundation for further study of Machine Learning.
The opening was attended by representatives of the University and Sigma Software, who participated in the preparation of the educational process. Welcoming speech by Natalia Melnykova, training manager at Sigma Software, prepared everyone for work and charged with the energy of success!
The launch of the Summer School was preceded by many joint initiatives conducted for Lviv Polytechnic students – good partners of Sigma Software. By the way, this is not the first experience of cooperation with the Department of Artificial Intelligence Systems. Last fall, third-year students presented their course projects to Sigma Software experts, and in the spring, Denis Pishev, Senior Software Developer at Sigma Software, participated in a review of fourth-year bachelor students’ theses. Sigma Software representatives were impressed with the high level of teaching. But there are no limits to growth and development, so they decided to start their own study program to help students better understand the required field.
From the very beginning, the training was planned in an offline format. Quarantine made its adjustments, but could not interfere with intentions. Mykhailo Dubovyi, coach at Data Science Summer School and Senior Software Developer at Sigma Software, skillfully adapted the program to the online format. Therefore, now all participants can connect to classes from convenient locations.
Learning format – lectures, full of examples and practice. According to the coach, there will be plenty of interactivity. For the convenience of practical tasks, participants will be divided into four teams. In five weeks, they will present their work to the company’s teachers and experts.
During the first lecture, the coach focused on the key concepts and history of Machine Learning and gave a brief overview of the entire program. Summer school participants will have four more meetings to develop their intuition and understanding of key concepts of machine learning, learn how to apply these concepts in practice, analyze a linear model, and study probability interpretations and statistical tests for linear regression.
Mykhailo Dubovyi is focused on fruitful interaction with the audience, as the topic is not easy, and everyone must fully understand the process. Therefore, he assures that he will encourage participants to be actively involved in the learning process and ask questions so that everyone is on an equal footing.
Work with the participants of Data Science Summer School will not end in the summer. The results can be summed up in the fall, when it becomes clear how students managed to use the acquired skills in their projects and how the knowledge gained helped in learning.