This course provides a practical, hands-on case study in e-commerce data analysis using Matplotlib with Python. Designed at the intermediate level, it equips learners with the skills to set up the environment, explore datasets, and construct compelling visualizations that reveal meaningful business insights.

In Module 1, learners will demonstrate the installation of Anaconda and Matplotlib, analyze e-commerce datasets by identifying unique values and preparing data, and apply visualization basics by working with figures, axes, and plotting approaches. In Module 2, learners will construct line graphs and histograms to interpret trends and data distributions, apply bar graphs and scatter plots to compare categories and evaluate relationships between variables, and create pie charts and boxplots to assess proportions, quartiles, and outliers for statistical insights. By the end of this course, learners will be able to analyze raw e-commerce datasets, apply Matplotlib techniques to construct visualizations, and evaluate patterns for actionable insights — essential skills for anyone pursuing data science, business analytics, or Python visualization projects.