Data Visualisation with Python: Seaborn and Scatter Plots

Course Cover
compare button icon

Course Features

icon

Duration

4 weeks

icon

Delivery Method

Online

icon

Available on

Lifetime Access

icon

Accessibility

Mobile, Desktop

icon

Language

English

icon

Subtitles

English

icon

Level

Advanced

icon

Effort

4 hours per week

icon

Teaching Type

Self Paced

Course Description

This course will show you how to visualize big data using Python programming language. This course will introduce you to Python for beginners in data analysis. Python is one the most popular and easy-to-use programming languages. It powers the back-ends for some of the largest online companies like Google, Dropbox, Instagram, and Instagram. Learn how Python programmers use data to create visual representations that are easy to analyse and examine. Seaborn, a Python data-visualization library, will be introduced to you in this course. Seaborn is a combination of aesthetic appeal and the technical insights of the Python programming language. Learn how to identify line, scatter, and other relational plots as well as the differences between them. What is the purpose of Python's categorical and quantitative variables? The programming language can visualise categorical data, which has a fixed length, and quantitative data that can be measured. Learn how to categorise plots, and other quantitative variables in data visualisation.

The course's final section will cover the basics of uncertainty in visualisations. The course will cover uncertainty in data, point estimation intervals, confidence bands, and other aspects of uncertainty. You'll learn how to use your new knowledge to confidently show uncertainty in data. You can preview some of the course steps here before you sign up.

Course Overview

projects-img

Alumni Network

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Explain the architecture and objects of Seaborn Package

Create Static Visualisations using Seaborn

Customise the Seaborn plots

Apply design and visualisation best practices to static plots

Target Students

This course is designed for professionals looking to grow their confidence in using Python to produce exploratory and explanatory visualisations and build dashboards, as well as better communicate their insights

Course Instructors

Author Image

Ed Marks

Instructor

I truly believe that leveraging the correct technologies in the appropriate way can take us towards a more sustainable economy. My focus is on converging M&E Engineering with Data Science/Analysis.
Course Cover