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This 1-credit course offers a guided, project-based experience in applied analytics for public-interest challenges faced by nonprofits and government agencies. Students work through the full analytics lifecycle, from translating a social problem into an analytics question and defining measures of impact to data preparation, modeling, interpretation, and communication. The course emphasizes learning by doing: students follow a prescriptive example and structured workflow that prioritizes application and analytical judgment over theoretical derivations. Pre-built code templates are provided so students can focus on analytical reasoning, model comparison, and interpretation rather than building models from scratch. Generative AI is an integral part of the course, with students using GenAI tools throughout the project to support research, analysis, interpretation, and communication. Methods vary by project and may include selected techniques from statistical inference, predictive modeling, unsupervised learning, natural language processing, or time-series analysis, and some projects may involve working with APIs. Students complete individual analyses and collaborate in teams to present their findings through short, pitch-style presentations designed for stakeholder communication and job interviews.