Practical Data Science: Tools for Social Change

Applied data science is already shaping how the world tackles pressing social challenges — from fighting discrimination, to allocating resources for refugees, to managing water scarcity in Africa. This course invites students from a wide range of backgrounds — social sciences, policy, business, environmental studies, or anyone simply curious about data — to learn how to use data science tools in ways that matter. Over fifteen weeks, you’ll get hands-on experience with Python in Google Colab (no installation required), organize your work on GitHub, create interactive visualizations with Plotly, and even try your hand at building a simple application in Streamlit. You’ll also see how modern AI coding assistants can serve as partners in debugging, exploration, and idea generation. By the end of the course, you will be able to: Collect and prepare real-world datasets for analysis. Visualize complex information with clear, interactive charts. Build a basic predictive model and interpret its results in plain language. Share your work through well-structured GitHub repositories. (Optionally) create and publish a lightweight data app to communicate your findings. Each class combines lecture and tutorial time, and the course concludes with an individual project where you choose a social issue that matters to you and use data to explore, explain, or propose solutions. All tools used are free and web-based, and alternatives will be provided when needed — so you can fully participate from anywhere in the world.