Data Visualization & Storytelling with G

This hands-on course explores how data visualization, storytelling, and generative artificial intelligence can be combined to transform quantitative analysis into effective policy communication. Building on the concepts and methods introduced in Quantitative Techniques I or an equivalent graduate-level statistics course, students will learn to communicate analytical findings clearly, accurately, and persuasively to technical, managerial, and executive audiences.

The course introduces foundational principles of data visualization alongside the practical use of contemporary generative AI tools to support the full analytics-to-story workflow, from organizing and interpreting data to developing presentations, policy briefs, and executive summaries. Through applied exercises, in-class laboratories, and a collaborative project, students will learn how to communicate uncertainty, maintain analytical rigor, and translate quantitative evidence into actionable recommendations.

By the end of the course, students will be able to design effective visualizations, critically evaluate AI-generated outputs, tailor communications to different stakeholder audiences, and convert complex quantitative findings into compelling policy narratives that support decision-making.