Research Design in Data Science

Catalog description

This advanced Data Science research design course immerses you in diverse methodologies, equipping you with a multifaceted approach to data-driven investigations. From the foundations of quantitative research, which harnesses statistical analyses to draw generalizable conclusions from large datasets to the cutting-edge realm of Constructive Research focuses on models, frameworks, tools, and software used by industry to improve value creation. Throughout the course, you will delve into DSR (Design Science Research) and examine how it integrates theoretical and empirical constructs with industry practices to develop applied and testable models, enhancing the Data Science landscape. Common approaches include experimental design, where controlled experiments are conducted to test hypotheses, observational studies that involve data collection without intervention, and exploratory research to uncover patterns and relationships in data. Furthermore, cross-sectional and longitudinal designs allow for the examination of data at specific time points or over time.