Python Data Visualization with Matplotlib and Seaborn – Intensive I
Duration: 5 Hours
Level: Beginner → Intermediate
Format: Live Human Online Intensive with Hands-On Labs
Tools Used: Python + Pandas + Matplotlib + Seaborn (VS Code or similar IDE)
Intensive Schedule (5 Hours)
Session 1: Visualization Foundations and Design Thinking
Why visualization matters in data analysis
Choosing the right chart for the question
Common visualization mistakes and misleading charts
Matplotlib vs Seaborn: roles and strengths
Lab 1:
Load prepared datasets
Create basic plots with Matplotlib
Compare chart choices for the same data
Validate visual clarity and accuracy
Session 2: Core Plot Types with Matplotlib
Line charts, bar charts, and scatter plots
Axes, labels, titles, and legends
Controlling scale and formatting
Exporting plots for reports
Lab 2:
Build multiple chart types from the same dataset
Customize labels, ticks, and titles
Save plots as image files
Verify plots match underlying data
Session 3: Statistical Visualization with Seaborn
Why Seaborn excels at analytical visuals
Distribution plots (histograms, boxplots, violin plots)
Relationship plots and trend visualization
Using Seaborn styles responsibly
Lab 3:
Create distribution and relationship plots
Compare categories visually
Identify trends and outliers
Cross-check visuals against numeric summaries
Session 4: Multi-Variable and Comparative Visualizations
Visualizing multiple dimensions of data
Color, hue, size, and grouping
Faceted plots for comparisons
Avoiding over-cluttered charts
Lab 4:
Build multi-variable Seaborn plots
Use faceting for clean comparisons
Validate readability and interpretability
Refine visuals for presentation
Session 5: Visualization Workflows and Best Practices
Integrating Pandas analysis with visuals
Creating reusable plotting functions
Preparing visuals for reports and stakeholders
Knowing when not to visualize
Lab 5:
Build a mini visualization pipeline
Create reusable plotting code
Generate report-ready charts
Review visuals for accuracy and bias
Intensive Description
Python Data Visualization with Matplotlib and Seaborn – Intensive I is a hands-on deep dive into turning analyzed data into clear, honest, and effective visuals.
This intensive focuses on intentional visualization, not just chart creation. Participants learn how to select appropriate chart types, design visuals that communicate insight accurately, and avoid common pitfalls that mislead or confuse audiences.
Rather than treating visualization as decoration, this course treats it as a critical analytical skill—one that must be grounded in data validation and clarity.
By the end of the intensive, attendees will confidently create professional-quality visualizations that support analysis, decision-making, and communication.
Lab & Exercise Structure
Each lab is:
Instructor-led with live explanation
Based on realistic analytical datasets
Focused on clarity, accuracy, and intent
Designed to complement Pandas-based analysis
Labs emphasize why a visualization works—not just how to code it.
Who This Intensive Is For
Python users analyzing data with Pandas
Analysts and accountants presenting insights
Professionals moving beyond spreadsheet charts
Anyone needing clearer, more trustworthy visuals
What You’ll Gain
Strong foundation in Matplotlib and Seaborn
Confidence choosing the right visual for the data
Ability to validate charts against underlying numbers
Skills to produce presentation-ready visuals
Other Python Analytics & Visualization Intensives
This intensive builds on Pandas-based analysis.
Additional intensives expand on this foundation by covering:
Advanced visualization techniques
Time series and financial charts
Interactive visualization tools
Dashboard design and storytelling
Python Data Visualization with Matplotlib and Seaborn – Intensive I ensures your visuals tell the truth—clearly, accurately, and effectively.
