Data analysis has become an essential skill across research, policy, development, and business sectors. Yet many aspiring researchers and professionals find it difficult to get started due to limited exposure to practical analytical tools and workflows.
This in-person workshop was designed to provide participants with a practical foundation in data analysis using Python on Google Colab, one of the most accessible and widely used cloud-based coding platforms. Out of 200+ applicants, 36 were selected to receive intensive training across two sessions overseen by BIGD’s Senior Research Associates Tahmid Bin Mahmud and Marzuk A. N. Hossain, as well as Program Coordinator Saadman Faisal.
- Session 1 introduced participants to data analysis using Python on Google Colab, where they were first briefly refreshed on key concepts including causality, regression, and randomized controlled trials, before working hands-on through a complete data analysis pipeline—loading, exploring, cleaning, visualizing, and analyzing real research data using the Tennessee STAR experiment, a landmark RCT measuring the causal effect of class size on student achievement.
- Session 2 introduced participants to advanced data workflows, covering how to fetch and integrate satellite data from Google Earth Engine as covariates in predictive models, and how to incorporate AI tools into the coding workflow for more efficient and productive analysis.
