Module 4: Data Visualization Using Matplotlib and Seaborn

• Creating line plots, bar charts, histograms, and scatter plots

• Customizing visual elements: titles, labels, legends, colors, and styles

• Leveraging Seaborn for statistical visualizations: boxplots, heatmaps, pairplots

• Best practices for choosing the right chart type

Module 5: Building Interactive Dashboards with Plotly

• Introduction to Plotly Express and graph objects

• Developing interactive charts with hover information, sliders, and zoom

• Exporting interactive visuals to HTML and static images

Capstone Project: Complete Data Analysis and Visualization Project

• Import, clean, and explore a real-world dataset

• Apply analysis techniques and create both static and interactive plots

• Present findings through a polished Jupyter Notebook report

Outcome: Delivery of a comprehensive, end-to-end data analysis and visualization project.