Applied Data Visualisation Mastery with Python

Course Structure 

• Duration: 4 Weeks (Onsite | Online) 

• Onsite Classes: Saturdays 10am - 5pm  (GMT+1) + Extra Weekday Follow-up Practise Sessions 

• Online: Tuesdays & Fridays 5.30pm - 8.00pm  (GMT+1) | Sundays 4.30pm - 8.00pm (GMT+1) 

• Access to the Catalyst AI Hub Africa Alumni Network

• 30 days of post-programme support

• 12 Hands-On Visualisation Labs

• Projects: 3 portfolio-ready projects — a BI report, a deployed interactive dashboard, and an executive data story

• Theory vs Practical: 20% / 80%

Ideal For

This course is designed for:

• Data analysts and business intelligence professionals  

• Data scientists  

• Product managers and business analysts  

• Financial analysts and economists  

• Researchers and academics  

• Anyone who regularly presents data  

Course Description

Participants will learn to create stunning, publication-quality visualisations using Matplotlib, Seaborn, and Plotly — building interactive dashboards, geospatial maps of African data, and compelling data narratives that communicate insight clearly and persuasively to any audience. Hands-on from the first session.

Recommended prior knowledge: Basic Python familiarity — ability to write simple scripts and work with variables and lists. No prior data visualisation experience required.

What Participants will learn

By the end of this course, participants will be able to:

• Apply core data visualisation design principles — including colour theory, chart selection, visual hierarchy, and accessibility — to produce charts that communicate clearly and accurately to any audience

• Build and fully customise every major chart type using Matplotlib — including multi-plot layouts, annotations, custom themes, and publication-quality export settings

• Conduct and communicate a complete exploratory data analysis using Seaborn's statistical visualisation tools — including distribution plots, categorical comparisons, correlation heatmaps, and regression visualisations

• Build fully interactive charts, animated time-series visualisations, and advanced chart types using Plotly Express and Plotly Graph Objects

• Design and deploy multi-page interactive web dashboards using Plotly Dash — with real-time user controls, live data connections, and custom styling — accessible via a live web URL

• Create interactive geospatial maps and choropleth visualisations of Nigerian and African data using Folium and Plotly's mapping capabilities

• Structure and deliver a complete data story — from raw dataset to executive-ready visual narrative — using the single-insight principle, annotation strategies, and presentation design techniques

• Select the right visualisation tool and chart type for any data type, audience, and communication goal — and justify that selection with design reasoning

• Build a professional visualisation portfolio demonstrating proficiency across static reporting, interactive dashboarding, geospatial mapping, and data storytelling

• Export and integrate Python visualisations into PowerPoint, Google Slides, and web publishing formats for professional stakeholder communication