Teaching Dataset Creation in a Classroom Environment

Datasets are crucial for data-driven decision-making in businesses and organizations, allowing for the optimization of processes and the identification of improvement opportunities. They are foundational for training machine learning models to recognize patterns and make predictions, encompassing various forms of data from simple text and numbers to complex images and graphs. Furthermore, datasets are vital for educating future data scientists and machine learning engineers, offering hands-on experience that enhances analytical skills and practical knowledge. However, a gap in university curricula regarding dataset creation skills is noted, which is essential for ensuring the quality of datasets and the robustness of decision processes. This paper proposes to address this educational gap by developing methodologies for teaching dataset creation within university settings, mindful of the distinct skill levels of students compared to professionals.