This course will teach you how to bring big data sets to life through data visualisation using the powerful Python programming language.

Explore the best data visualisation tools to become a programming expert

On this course, you’ll look at Python for beginners in data analytics. Python is one of the most widely used, and easiest to use programming languages, powering the back-ends of some of the world’s biggest online companies, including Google, Dropbox and Instagram.

You’ll learn how a Python programmer uses data to create graphical representations that can be easily analysed and examined.

Learn how to use Seaborn in Python

This course will also introduce you to Seaborn, a data-visualisation library in Python. Seaborn combines aesthetic appeal with the powerful technical insights of the programming language.

You’ll learn how to identify a scatter plot, line plot, and other relational plots, as well as how to understand the differences between them.

Understand quantitative and categorical variables

What are quantitative and categorical variables used for in Python? You’ll see how the programming language visualises categorical data (which has a fixed length) and quantitative data (which can be measured).

You’ll also find out how to categorise plots and other quantitative variables of data visualisation.

Examine uncertainty in data and visualisation workflows

The final section of the course will teach you the basics of uncertainty within visualisations. You’ll examine uncertainty in data, point estimate intervals, and confidence bands.

Using your new knowledge, you’ll be able to confidently display uncertainty in data and walk through creating a workflow of a visualisation based on exploring a dataset.

Syllabus

Week 1
Introduction to Seaborn and visualising quantitative variables
- Welcome to the course!
  Get introduced to information about the optional project tasks, and an overview of Week 1.
- Introduction to Seaborn
  In this activity, you'll learn about the architecture and objects of the Seaborn package.
- Visualising quantitative variables
  Learn the key aspects of rational plots and subplots by exploring the various customisation options in Seaborn.
- Wrap-up
  Now it's time to reflect on your learning throughout the week, and look to what's next!
Week 2
Visualising categorical and quantitative variables and customising Seaborn plots
- Introduction
  Welcome to Week 2! Let's start by introducing the week's topics and outcomes.
- Visualising categorical and quantitative variables
  After exploring scatter plots, line plots, and other relational plots, you will now practice plotting categorising plots and quantitative variables of data visualisation using Seaborn.
- Customising Seaborn plots
  In this activity, you'll learn how to customise Seaborn plots, specifically how to the style, colour, and add labels and titles to them.
- Wrap-up
  To complete the week, let’s recap the key points covered so far.
Week 3
Highlighting data and using colour in visualisations
- Introduction
  Welcome to Week 3! Let's start by introducing the week's topics and outcomes.
- Highlighting your data
  In this activity, you will learn how to highlight and annotate various parts of the data in bar, scatter, and other types of plots.
- Using colour in visualisations
  Here, you'll explore the colour theory of data visualisation.
- Wrap-up
  Now it's time to reflect on your learning throughout the week and look to what's next!
Week 4
Showing uncertainty and visualisation workflow
- Introduction
  This week, you'll be introduced to display errors and uncertainties in your data, and exploration workflow using a marathon data set.
- Showing uncertainty
  Explore how to display errors and uncertainties in your data on a plot using Python.
- Visualisation workflow
  Delve deeper with visualisation by looking at a real data exploration workflow using a marathon data set in data analytics throughout this activity.
- Wrap-up
  To complete the week and course, let’s recap the key points covered so far.

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

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

Who is the course for?

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.

What software or tools do you need?

During this course we’ll be using Tableau Public and Excel. If you don’t have Excel, you might find this online version useful. We recommend you use a computer to access these elements.

Who will you learn with?

Ed Marks

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.

Who developed the course?

FutureLearn

FutureLearn is a leading social learning platform and has been providing high quality online courses for learners around the world over the last ten years.

In collaboration with

Endorsers and supporters

endorsed by

Learning on FutureLearn

Your learning, your rules

Courses are split into weeks, activities, and steps to help you keep track of your learning
Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
Stay motivated by using the Progress page to keep track of your step completion and assessment scores

Join a global classroom

Experience the power of social learning, and get inspired by an international network of learners
Share ideas with your peers and course educators on every step of the course
Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others

Map your progress

As you work through the course, use notifications and the Progress page to guide your learning
Whenever you’re ready, mark each step as complete, you’re in control
Complete 90% of course steps and all of the assessments to earn your certificate

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