Free · Self-Paced · Real Charts

Data Visualization with Python.
5 Days. Zero Cost.

Charts that actually communicate instead of just showing data. Learn matplotlib, seaborn, and Plotly — plus the design principles that separate good visualizations from confusing ones.

Free forever · No credit card · No spam

dashboard.py
import plotly.express as px

# Day 3: Interactive chart with Plotly
fig = px.line(df, x='date', y='revenue',
             color='region',
             title='Revenue by Region Over Time')

fig.update_layout(
    template='plotly_white',
    hovermode='x unified'
)
fig.show()  # Interactive in browser
3
Libraries
Design
Principles
Interactive
Charts
Full Report
Day 5

Visualization is a skill. This course teaches it like one.

Most chart tutorials show you how to make a bar chart. This course shows you when to use a bar chart, when not to, and how to make it clear enough that anyone understands immediately.

Three Libraries

Matplotlib for control. Seaborn for statistical charts. Plotly for interactive dashboards. You'll know when to reach for each one.

Design Principles

Day 4 is pure design: right chart type, color theory, reducing chart junk, and making labels do the work. These principles apply to any tool.

Full Report Day 5

Day 5 takes a messy CSV and builds a complete visual report — five charts that tell a coherent story. Portfolio-ready output.

Five days. One complete skill set.

1
Day

Matplotlib Fundamentals — Line, Bar, Scatter

Create your first charts. Line charts for time series, bar charts for comparisons, scatter plots for relationships. Control titles, labels, colors, and figure size.

matplotlibLine chartsBar chartsScatter plots60 min
2
Day

Seaborn — Statistical Visualizations

Use seaborn for statistical charts. Histograms, box plots, violin plots, heatmaps, and pair plots. Understand what each chart reveals about distributions.

seabornBox plotsHeatmapsPair plots60–75 min
3
Day

Plotly — Interactive Charts for Dashboards

Build interactive charts with Plotly. Hover tooltips, zoom, and filter. Create subplots and faceted views. Export to HTML for sharing.

PlotlyInteractivitySubplotsHTML export75–90 min
4
Day

Design Principles — Right Chart, Color, Clarity

Choose the right chart type. Apply color principles. Reduce chart junk. Write titles that tell the story, not just label the axes.

Chart typesColor theoryData-ink ratioStorytelling60–75 min
5
Day

Build a Complete Visual Report from Raw Data

Start with a messy CSV. Clean it with pandas. Build five charts that tell a story. Export as self-contained HTML. Walk away with a portfolio piece.

pandasFull pipelineHTML reportPortfolio90–120 min

Start Day 1 right now.

Data Visualization with Python — Free 5-Day Course

All 5 days free. Forever. No paywall.

No spam. No credit card. Or go straight to Day 1.

Ready to Go Deeper?

Finish the free course. Then join the live bootcamp.

Three days of intensive, hands-on AI training. Build production systems with real data, real APIs, and a cohort of peers. $1,490 all-in. Coming to 5 cities in October 2026.

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