Summer School of Research Methods
Have you heard about the Big Bone and Big Data? … bear with us, these things have something in common and that is the Summer School of Research Methods, which happened in the longest week of the year, near one of the highest peaks in Bulgaria. Just let us tell you that it was a Big Deal to all who want to make Science. Why? Keep reading.
The Summer School is indeed a school for grown-up curious nerds who want to advance their knowledge and skills in the domain of Data Science and Research. It was organized by Sofia University and us – the community of data passionate.
At the school, there were renowned professors, Ph.D. students, academia and industry representatives, whose main goal was to improve the participants’ knowledge and to build their motivation for pursuing Ph.D. and making Science in the domain of Data Science.
Among the lectors were prof. Angel Marchev Sr. who shared how Science was born, making a parallel with some big bones from 2001: A space odyssey (a pretty cool analogy, right?). The theory behind Data Science, including topics such as System Theory, Cybernetics, Structure and Optimization of Models, Bayesian theory and Probabilities, was presented by Prof. Aleksander Efremov, Prof. Angel Marchev Jr., Prof. Kaloyan Haralampiev and prof. Mladen Savov.
The main driver for Data Science Society is to support the theory with practice. Among the Society’s mentors and members are Gloria Hristova, prof. Boryana Bogdanova, Martin Martinov, Petar Nikolov, Vladimir Vassilev, Pavel Nikolov and Demir Tonchev who supported the School with workshops for Data Science environments such as R Studio, Orange and Python in Jupiter Notebook. They presented also interesting industry applications of Neuro Networks, Machine Learning, and Text Mining.
During the Summer School, every participant had the opportunity to work in a team on one of three cases with real data from different industries. In spirit “Together against the challenge”, the participants performed data exploration, built machine learning models in different environments. Every team applied various algorithms to solve the cases and extract valuable knowledge. The goals of presented cases were to predict cryptocurrencies, to perform factor analysis in the HR industry and to build a recommender system for E-Commerce. Some of the teams’ solutions you can explore in Data Science Society’s GitHub account.
Of course, there was a Graduation Ceremony – yeah, this time without parents and fireworks but with a hike in nature, bouquets and … “kabapcheta” as a traditional graduation lunch.
We as a community believe that the mission of winning the minds and hearts of the participants for applying the scientific method is accomplished.