Explore and Visualize Data the Python Way

In this course, you'll learn to uncover and communicate insights through powerful data visualization techniques. You'll master both static and interactive visualization tools, from Matplotlib and Seaborn to Plotly, while conducting thorough exploratory data analysis. Using the EngageMetrics and MediTrack datasets, you'll develop the skills to transform complex data into compelling visual stories that drive decision-making. Upon completion, you'll be able to: • Conduct EDA to summarize datasets by using descriptive statistics, identify patterns, and detect anomalies. • Create static visualizations such as line plots, bar charts, boxplots, histograms, and scatter plots. • Build interactive plots that allow user engagement. • Integrate EDA and visualization techniques in a two‑part challenge that requires both static and interactive outputs

• Conduct exploratory data analysis using descriptive statistics
• Identify patterns and detect anomalies in datasets
• Create static visualizations including line plots and histograms
• Build interactive plots for user engagement
• Integrate EDA and visualization techniques in practical challenges

• No deep prior experience required; basic computer skills helpful
• Ability to read English instructions and complete short practice tasks