Data Visualization Made Easy with Seaborn and Python

Master Seaborn and Matplotlib to turn raw data into powerful, story-driven visual insights.

What you'll learn

• Set up a Python virtual environment and install the libraries needed for Seaborn data visualization.
• Learn how Seaborn and Matplotlib work to create, display, and save professional-quality visualizations.
• Use real-world datasets to build a range of clear, insightful, and visually appealing charts.
• How to plot categorical data with bar plots, box plots & point plots.
• Plot univariate and multivariate time series.
• How to visualise distributions with uni & bivariate histograms, violin plots and KDE plots.
• Show statistical relationships with scatter plots, heat maps, facet grids and joint plots.
• How to show linear models, regression plots and residual plots.

Requirements

A basic understanding of Python would be beneficial!

Description

Unlock the Power of Data Visualization with Seaborn!

Master data visualization in Python using Seaborn, a powerful library built on top of Matplotlib. Whether you’re a data scientist, analyst, or Python enthusiast, this hands-on course will take you from beginner to advanced user — teaching you how to create beautiful, insightful visualizations that clearly communicate your data’s story.

You’ll start by learning how to set up a Python virtual environment and install all the required libraries. Then, you’ll work with a range of real-world datasets to build professional-quality visualizations step by step.

Next, you’ll dive into the mechanics of Seaborn and Matplotlib — learning how to display and customize graphs, save charts as images, create plots in loops, and even export multiple charts into one image.

You’ll also learn how to choose the right type of plot for your data — an essential skill for telling clear, effective stories with your visualizations. By the end of the course, you’ll have a complete toolkit of plots that make your data come alive.

Here's what you'll learn!

Categorical Plots

• Bar Plots (Simple & Advanced)
• Point Plots
• Box Plots

Time Series Plots

• Time Series Plots with Single Variables
• Multi-Variate Time Series Plots

Visualising Distributions

• Univariate & Bivariate Histograms
• Violin Plots
• Kernel Density Estimates

Visualising Statistical Relationships

• Scatter Plots
• Heatmaps
• Facetgrids
• Scatter Plot & Histogram Combinations

Plotting Regression Models

• Regression Plots
• Linear Model Plots
• Residual plots

Each video is backed up with fully documented source code, and a range of datasets is available for you to download and use to create your own plots — helping you cement your skills and gain confidence with Seaborn.

Who this course is for:

Beginner Python developers who want to learn the basics of visualising data with Seaborn