This hands-on course teaches learners how to prepare, analyze, and visually interpret data using Python’s Seaborn library, with a focus on census datasets. Beginning with foundational setup—such as installing Anaconda, configuring Jupyter Notebook, and loading libraries—the course progresses into exploratory data analysis and practical visualization techniques.

Learners will gain proficiency in generating a range of plots including scatter plots, line graphs, swarm plots, violin plots, heatmaps, and advanced visual grids. Emphasis is placed on enhancing plot readability through axis formatting, label alignment, and plot configuration to support data storytelling. Throughout the course, learners will apply Bloom’s Taxonomy skills such as identifying trends (Understand), configuring tools (Apply), modifying visuals (Analyze), and interpreting relationships (Evaluate). Ideal for data enthusiasts and analysts, this course equips learners to effectively visualize multivariate data, uncover insights, and support data-driven decision-making.