Data Visualization with Python, PowerBi and Tableau

About Course

Data Visualization with Python, Power BI, and Tableau is designed for learners who already have a solid understanding of Python and want to master the art of turning raw data into compelling visual stories across multiple industry-standard tools.

The course begins with Python’s powerful visualization libraries such as Matplotlib, Seaborn, Plotly, and Folium to create static, animated, and interactive charts, dashboards, and geospatial visualizations. Learners will then extend these skills to Power BI and Tableau, learning how to translate analytical insights into polished, interactive dashboards suitable for business and decision-making environments.

By the end of the course, learners will be able to choose the right visualization for the right insight, build end-to-end data stories, and confidently present data using Python, Power BI, and Tableau.

Fundamentals of data visualization and design principles
How to use Matplotlib for basic and customized plots
Creating statistical plots with Seaborn
Building interactive charts and dashboards with Plotly and Dash
Visualizing geospatial data using Folium and Choropleth maps
Advanced visuals: waffle charts, word clouds, sunburst plots
Best practices for storytelling with data
Dashboard layout and interactivity for non-technical audiences

Course Content

Module 1 — Visualization foundations
Understand why visualization matters and how to choose the right chart.

Principles of effective data visualization
Chart types and when to use them
Color theory, accessibility, and storytelling

Module 2 — Matplotlib basics
Learn the core plotting library in Python.

Module 3 — Statistical plots with Seaborn
Create beautiful, informative statistical visuals.

Module 4 — Interactive charts with Plotly
Build dynamic visuals and dashboards.

Module 5 — Geospatial visualization with Folium
Map data and tell location-based stories.

Module 6 — Advanced visuals and storytelling
Go beyond basics to create memorable visuals.

Module 7 — Capstone project
Build a dashboard or visual report from scratch.

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About Course

What Will You Learn?

Course Content

Module 1 — Visualization foundations Understand why visualization matters and how to choose the right chart.

Principles of effective data visualization

Chart types and when to use them

Color theory, accessibility, and storytelling

Module 2 — Matplotlib basics Learn the core plotting library in Python.

Line, bar, scatter, histogram, pie charts

Customizing axes, labels, legends, styles

Subplots and figure layout

Saving plots for reports

Module 3 — Statistical plots with Seaborn Create beautiful, informative statistical visuals.

Distribution plots: hist, kde, box, violin

Categorical plots: bar, count, swarm, strip

Regression plots and correlation heatmaps

Styling and themes

Module 4 — Interactive charts with Plotly Build dynamic visuals and dashboards.

Scatter, line, bar, bubble, pie, sunburst charts

Hover tooltips, zoom, filters

Layouts and tabs

Intro to Dash for dashboard building

Module 5 — Geospatial visualization with Folium Map data and tell location-based stories.

Mapping points and markers

Choropleth maps with real data

Styling maps and adding layers

Kenyan geospatial datasets (optional)

Module 6 — Advanced visuals and storytelling Go beyond basics to create memorable visuals.

Waffle charts and word clouds

Animated charts and transitions

Dashboard design principles

Exporting dashboards and reports

Module 7 — Capstone project Build a dashboard or visual report from scratch.

Choose a dataset (e.g., local business, public health, education)

Apply full visualization pipeline

Deliverables: notebook, dashboard, 5-slide summary

Earn a certificate

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