Is Visualizing Statistical Data Using Seaborn beginner friendly?

Yes, this course is designed for beginners. It covers foundational concepts and requires no prior advanced knowledge in the subject area.

How long does it take to complete Visualizing Statistical Data Using Seaborn?

The total duration of the course is approximately 1 hour 44 minutes. Since it is generally self-paced, completion time depends entirely on your learning schedule and availability.

Is this course more theory-focused or project-focused?

This course provides a strong mix of conceptual theory and practical application to ensure a comprehensive understanding of the subject matter.

What careers is this course relevant for?

The skills taught in this course are highly relevant for professionals pursuing roles within Data Science and adjacent technical fields looking to upskill.

Data Science

Visualizing Statistical Data Using Seaborn

Name: Visualizing Statistical Data Using Seaborn
Availability: InStock
Rating: 5 (24 reviews)

Data analysts and scientists are tasked with extracting information and insights from huge datasets. This course introduces the Seaborn Python library helping engineers communicate information via its high-level and powerful visualization tools.

5|Reviews (24)

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₹10,563/yr

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₹1,254/mo

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Course Insight

Suitable for beginner learners. This course serves as an entry point into Data Science, building foundational knowledge before moving on to advanced frameworks or specialized paths.

Beginner FriendlySelf-Paced Learning

SKILLS TO
MASTER

Analytics

Exploratory Data Analysis

Modeling

Predictive Machine Learning

SQL Querying

Relational Data Management

Pandas

Matplotlib

Statistics

Tableau

ETL

Careers:Data Scientist, Data Analyst, Machine Learning Engineer.

💡This course fits perfectly into our comprehensiveData Science Learning Path. Explore the ecosystem to see how it compares to other foundational skills.

Quick Facts

1 hour 44 minutes

Below sections are verified from last major sync. For real-time updates and today's latest lectures, Check official page here.

What You’ll Learn

Course Overview : 2mins.
Visualizing Relationships and Distributions in Seaborn : 54mins.
Building Trellis Plots in Seaborn : 29mins.
Controlling Plot Aesthetics and Style in Seaborn : 17mins.

See side-by-side differences in what you’ll learn

Description

As deep learning approaches to machine learning rise in popularity, models are increasingly hard to understand and pick apart. Consequently, the need for sophisticated visualizations of the data going into the model is becoming more and more urgent and important.

In this course, Visualizing Statistical Data Using Seaborn, you will work with Seaborn which has powerful libraries to visualize and explore your data. Seaborn works closely with the PyData stack - it is built on top of Matplotlib and integrated with NumPy, Pandas, Statsmodels, and other Python libraries for data science

You will start off by visualizing univariate and bivariate distributions. You will get to build regression plots, KDE curves, and histograms to extract insights from data.

Next, you will use Seaborn to visualize pairwise relationships of high dimensionality using the FacetGrid and PairGrid.

Plot aesthetics, color, and style are important elements to making your visualizations memorable. Given this, you will study the color palettes available in Seaborn and see how you can manipulate specific plot elements in our graph.

At the end of this course you will be very comfortable using Seaborn libraries to build powerful, interesting and vivid visualizations - an important precursor to using data in machine learning. Software required: Seaborn 0.8, Python 3.x.

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