The capstone session for Block 1 requires participants to apply all the skills learned to a small, end-to-end project. In teams, learners will collect or use an existing dataset, clean and analyze it, compute descriptive statistics, create visualizations, and present their findings. Presentations will be evaluated on clarity, accuracy, and the ability to communicate insights […]
This session covers the core statistical measures used to summarize and describe datasets. Learners will calculate and interpret measures such as mean, median, mode, and standard deviation, and understand when each is most appropriate. The module will also cover the concept of variability and how it helps reveal trends, patterns, and anomalies in data.
Introduction to Statistics Read More »
Participants will learn how to use spreadsheet software to organize, clean, and summarize datasets. The module covers essential spreadsheet functions, sorting and filtering, data validation, and creating visual summaries using charts. By the end, learners will be able to prepare a clean, structured dataset ready for statistical analysis or visualization.
Working with Spreadsheets Read More »
In this module, participants will learn the essential skills for gathering and managing data in ways that preserve its accuracy, integrity, and usefulness. We will cover primary data collection through surveys, interviews, and observations, as well as sourcing secondary data from reports, databases, and public records. Participants will learn the principles of data quality —
Data Collection and Management Read More »
This module introduces participants to the structured process of research — the backbone of credible data work. We will explore different types of research, from qualitative interviews to quantitative surveys, and how to choose the right approach based on the goals of a project. The session covers how to define a research problem, formulate research
Basics of Research Methodology Read More »
