Data Visualization with Python By IBM Course Syllabus

Overview: This course provides a comprehensive introduction to data visualization using Python, designed for beginners with basic Python knowledge. Learners will explore key visualization libraries such as Matplotlib, Seaborn, Plotly, and Folium through hands-on labs and real-world datasets. The curriculum progresses from foundational plotting techniques to advanced visualizations and interactive dashboards. With approximately 17 hours of total content, this course combines theory and practice to build strong data storytelling skills applicable in academic and industry settings.

Module 1: Introduction to Data Visualization Tools

Estimated time: 2 hours

• Understand the importance of data visualization in data analysis
• Learn the basics of Matplotlib
• Create simple line plots
• Explore a dataset on Canadian immigration

Module 2: Basic and Specialized Visualization Tools

Estimated time: 3 hours

• Create area plots, histograms, and bar charts using Matplotlib
• Generate pie charts and box plots
• Construct scatter plots for correlation analysis
• Plot directly with Matplotlib for greater control

Module 3: Advanced Visualizations and Geospatial Data

Estimated time: 2 hours

• Generate waffle charts to visualize categorical data
• Create word clouds from text data
• Use Seaborn for regression plots

Module 4: Geospatial Data Visualization with Folium

Estimated time: 2 hours

• Visualize geospatial data using Folium
• Create maps with markers and pop-up labels
• Build choropleth maps for geographic distributions

Module 5: Creating Dashboards with Plotly and Dash

Estimated time: 5 hours

• Understand the benefits of interactive dashboards
• Create interactive charts using Plotly Express
• Build advanced visualizations with Plotly Graph Objects
• Develop dashboards using Dash for interactive data presentation

Module 6: Final Project

Estimated time: 3 hours

• Apply visualization techniques to a real-world dataset
• Create a comprehensive interactive dashboard
• Tell a compelling data-driven story using learned tools

Prerequisites

• Basic understanding of Python programming
• Familiarity with data handling concepts
• No prior experience in data visualization required

What You'll Be Able to Do After

• Create a wide variety of static and interactive visualizations using Python
• Apply best practices in data visualization to communicate insights effectively
• Visualize geospatial data with Folium, including choropleth maps
• Develop interactive dashboards using Plotly and Dash
• Tell compelling data stories through visual narratives