This specialization equips learners with the skills to create, analyze, and customize data visualizations using Python’s Seaborn library. Starting from foundational plots, learners progress to advanced statistical and multivariate visualizations, mastering techniques for exploratory data analysis and storytelling. With hands-on coding practice, guided examples, and real datasets, participants gain practical expertise to communicate insights effectively. Designed for aspiring data analysts, scientists, and Python developers, the program blends data wrangling, visualization, and interpretation skills essential for data-driven decision making.
Seaborn Python Data Visualization & Analysis Specialization
Discover new skills with 30% off courses from industry experts. Save now.
Seaborn Python Data Visualization & Analysis Specialization
Master Python Data Visualization with Seaborn. Build, customize, and analyze statistical data visualizations using Python Seaborn
Instructor: EDUCBA
Included with 
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Apply Seaborn to construct and customize statistical and categorical plots.
Analyze and interpret multivariate data relationships using advanced visualizations.
Communicate insights effectively through exploratory data analysis and storytelling.
Overview
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
September 2025
22 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from EDUCBA
Specialization - 4 course series
What you'll learn
Construct scatter, line, and faceted relational plots to analyze data trends.
Design and interpret categorical plots such as box, violin, and bar charts.
Apply Seaborn’s figure-level functions to create clear, multi-variable insights.
Skills you'll gain
Category: Matplotlib
Category: Plot (Graphics)
Category: Pandas (Python Package)
Category: Statistical Visualization
Category: Data Presentation
Category: Seaborn
Category: NumPy
Category: Scatter Plots
Category: Data Visualization Software
Category: Data Literacy
Category: Statistical Analysis
Category: Exploratory Data Analysis
Category: Descriptive Statistics
Category: Box Plots
What you'll learn
Analyze and visualize univariate and bivariate data distributions in Seaborn.
Build regression-based visualizations to model and interpret relationships.
Customize statistical plots using hue, facet grids, and styling for insights.
Skills you'll gain
Category: Statistical Modeling
Category: Matplotlib
Category: Descriptive Statistics
What you'll learn
Prepare and preprocess census datasets for exploratory data analysis.
Create scatter, violin, swarm, heatmap, and multivariate plots in Seaborn.
Enhance chart readability and interpret insights for data storytelling.
Skills you'll gain
Category: Data Visualization Software
Category: Seaborn
Category: Plot (Graphics)
Category: Statistical Visualization
Category: Data Storytelling
Category: Exploratory Data Analysis
Category: Matplotlib
Category: Pandas (Python Package)
Category: Scatter Plots
What you'll learn
Configure Python and Seaborn to prepare and explore census datasets.
Generate scatter, violin, heatmap, and multivariate visualizations.
Enhance plots for readability and interpret data insights effectively.
Skills you'll gain
Category: Data Processing
Category: NumPy
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
The Specialization can typically be completed within 6 to 8 weeks, with learners dedicating an average of 3–4 hours per week. This flexible schedule is designed to accommodate both working professionals and students, allowing learners to progress steadily through the courses while building strong, hands-on proficiency in data wrangling and visualization using Python’s Seaborn library. By the end of the program, participants will have gained practical, job-ready skills to create and interpret advanced data visualizations for real-world applications.
Learners should have a basic understanding of Python programming, including working with data structures and libraries such as Pandas. Prior exposure to statistics or data analysis concepts is helpful but not required.
Yes, it is recommended to take the courses in the suggested order. The curriculum is designed to build progressively—from foundational visualizations to advanced statistical analysis—ensuring learners develop a structured, step-by-step mastery of Seaborn.
More questions
Financial aid available,