MODULE 5 OF 9 · 20 Hrs · 2 Weeks

Data Visualization (Matplotlib / Seaborn)

Analysis only creates value once it's understood by someone else. This module builds the skill to turn raw findings into clear, compelling visuals — from chart fundamentals through storytelling with data.

Who This Module Is For

Students who have completed the EDA module and are ready to communicate findings visually.

Real-World Relevance

The ability to choose the right chart and tell a clear story with it is what turns a data analyst's work into something stakeholders actually act on.

Program Overview View Hands-On Labs

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Curriculum

What You Will Learn

A detailed, industry-aligned breakdown of every topic covered in this module.

Principles of effective data visualization
Line, bar, scatter & histogram plots
Matplotlib figure & axes customization
Seaborn statistical plots & heatmaps
Multi-panel & faceted visualizations
Storytelling with data
Choosing the right chart for the data
Building simple visualization dashboards

Technology Stack

Tools You Will Use

Hands-on time with the same tools used by working business and data analysts today.

Matplotlib

Core Python plotting library used to build line, bar, scatter and histogram visualizations.

Seaborn

Statistical visualization library built on Matplotlib, used for heatmaps and distribution plots.

Plotly

Interactive charting library used to build explorable, presentation-ready visualizations.

Practical Work

Hands-On Labs

Production-style data analytics lab scenarios, built using real business datasets.

Build line, bar, scatter and histogram plots for a real business dataset using Matplotlib.

Create statistical plots and heatmaps using Seaborn.

Design a multi-panel, faceted visualization comparing multiple variables.

Choose and justify the right chart type for a given business question.

Assemble a small visualization dashboard that tells a coherent data story.

Evaluation

Assessment

Knowledge Assessment

Quiz covering chart-type selection, Matplotlib/Seaborn syntax and visualization best practices.

Practical Evaluation

Students must build a set of clear, business-ready visualizations that tell a coherent story from a real dataset.

Portfolio

Projects

Industry-style deliverables added directly to your project portfolio.

Portfolio Project 01

Data Visualization Portfolio

Build a set of business-ready Matplotlib and Seaborn visuals that tell a clear story from a real dataset.

Module Outcome

What This Module Builds

Students learn to turn raw analysis into clear, compelling visuals that communicate findings to business stakeholders.

Maps to job roles

Data Visualization AnalystData AnalystReporting AnalystInsights Analyst