In October 2023 the Institute of Computer Science at the University of Silesia (Faculty of Science and Technology) together with the Institute of Computer Science at Vytautas Magnus University in Kaunas (Lithuania), as a part of the T4E Stronger Together Project funded by NAWA, offered a fascinating “Data Science” module related to data science and its application to the rule-based representation of knowledge. The idea of these classes within the Data Science module for T4E assumes the division of the allocated time of classes into two equal parts.
The part carried out by the Institute of Computer Science at the University of Silesia will be devoted to applying data science algorithms for the rule-based representation of knowledge. Modern intelligent systems assume the induction of knowledge from data, which most often takes the format of rules (cause-and-effect chains IF THEN). The lectures and laboratories were divided into two parts and discuss using efficient solutions in data science methodology (both supervised and unsupervised learning). As part of supervised learning, we discussed issues related to the use of such well-known and very efficient classification techniques as, for example, decision trees or association rules for the analysis of rules induced from data and issues related to the assessment of the quality of these rules as classifiers. As part of unsupervised learning, we showed how to manage a large set of rules through clustering algorithms. In this way, course participants were able to acquire qualifications for the practical application of rules induction methods from large data sets, as well as effective management of these rules by creating complex structures of rule clusters. As a result, it equiped the participants with knowledge on how to create efficient analysis systems with large sets of domain data, e.g., in medicine, economics, or other areas of life where the accumulated knowledge is of great importance but also the size of the data is significant.
The coordinators from the University of Silesia: Beata Zielosko, Asocc. Prof., Agnieszka Nowak–Brzezińska, Asocc. Prof.
The coordinators from the Vytautas Magnus University in Kaunas: Daiva Vitkutė-Adžgauskienė, Prof. dr., Ričardas Krikštolaitis, Prof. dr., Tomas Krilavičius, Prof. dr.
Students’ opinion
“The course was nice in general. There are few key points that I would suggest to change/update.
Data processing part was very good and understood (I discussed projects with other students and saw everyone of them to do some sort of processing -> good sign that content was captured). The course could also note the existence of other processing technologies and approaches that are not covered with a course. It will be especially useful for entrepreneurial students.
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Overall, I had a great time and it would be great to see you soon again. Thank you!”
“Reflecting on the Data Science course, I’m excited to share my thoughts on the two enriching weeks in Kaunas and Katowice.
The engaging lectures and hands-on exercises were real highlights, deepening my understanding of data science concepts. Exploring diverse topics, from data analytics to machine learning, made the learning experience well-rounded and engaging. Collaborating on projects with students from Silesia University added a dynamic and enjoyable element. Beyond just technical skills, this collaborative atmosphere allowed me to forge lasting connections with my colleagues, providing a broader perspective on the world of data science.
A standout moment was our trip to Guido Coal Mine in Katowice, which added a unique cultural experience to the course. Although not directly related to data science applications, it provided a fascinating glimpse into the local history and heritage.
I’m enthusiastic about contributing to the post on the Faculty website and Facebook profile, sharing the positive impact this course had on my knowledge, network, and memorable experiences.”
“My experience with the Data Science course at Vytautas Magnus University in Kaunas and the University of Silesia in Katowice was certainly a unique experience as it was the first time go as an exchange student. It toke me out of my comfort zone, there some of the things i did like and challenges I had to adapt to. Overall, I found the course to be excellent.I also gain new friends, with different ideas and background, that I would have never encountered otherwise. This course also provided me with valuable insights into data science. while the course had its share of adjustments, the overall experience was positive and enriching. Regarding the significance of data science in the IT world, it is indeed a top-ranking field, given its growing importance and impact on various industries.”
“Participating in this course was incredibly valuable. What I liked the most was the depth of knowledge acquired and the practical skills gained. I highly recommend this course to other students as it provided a solid foundation for my professional growth. The interactive nature of the classes made the learning experience interesting and engaging. I believe the acquired skills will be crucial in my future professional endeavors.”
The event was possible thanks to the project ‘Stronger Together – strategic partnerships of the University of Silesia in Katowice within the Transform4Europe network’, funded by the National Agency for Academic Exchange as part of the Strategic Partnerships programme.
