In Descriptive Statistics and Data Visualization, you’ll learn to explore datasets with code and turn findings into targeted visuals that drive clear decisions. This is a skill-based path organized around real analyst job tasks. You’ll start with a quick check of what you already know, then focus on the skills you want to strengthen. Skip topics you’ve mastered and dive deeper where you need practice. Each lesson is curated from expert instructors so every step builds a concrete workplace skill.

Using Python (pandas, seaborn/matplotlib), you’ll perform exploratory data analysis (EDA), compute and interpret measures of central tendency and dispersion, summarize categorical variables with frequency analysis, and create exploratory charts. In Tableau, you’ll identify the right chart for a question and build comparison visuals that stack KPIs against targets and across business segments. By the end, you can explore data reproducibly, summarize results clearly, and design targeted visuals including skills that map to responsibilities in roles like Data Analyst, Business Intelligence Analyst, Reporting Analyst, and Operations Analyst.