Designing a Data Science Course for Non-Computer Science Students: Practical Considerations and Findings

This Full Paper in the Research-To-Practice Category illustrates what an online survey of students’ opinions reveals about students’ perceived learning and take-away from a course on Data Science. The course is offered at University of Vienna in the Business Analytics, Data Science, and Digital Humanities faculties as part of the masters’ programs. In this work, we outline the course structures, goals, modules, and present preliminary findings gained while teaching the course. Due to the global pandemic and resulting lock-downs, the course was held online, hence, we also analyze the effects of the current situation on the students.The results revealed that the structure of the course is appreciated by the students. Furthermore, the students liked the open source software taught in the course where they can create visual workflows with an intuitive, drag-and-drop style graphical interface, without the need for coding. The results also confirmed our hypothesis which showed that working in groups is more complex and difficult using online tools. We learn that the instructor-generated technique for forming the groups assigning to each group students with different backgrounds, lead to teams that are able to solve problems faster as they are more cognitively diverse. These findings confirm that the approach used in the Data Science course is viable for teaching computer science skills to non computer-scientist and can be used by other educational institutions.