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FutureLearn

Data Visualisation with Python: Matplotlib and Visual Analysis

via FutureLearn

Overview

Learn how to use Python for business analysis

Many organisations can collect and analyse data effectively, but not all are able to transform these insights into effective decision-making that results in organisational value. That’s where data visualisation comes in.

This Python online course will supercharge your data visualisation skills for both exploratory and explanatory purposes, using the commonly used programming language.

Python is used across all industries, from healthcare to finance, and in different fields of business analytics. It’s also one of the simplest programming languages to learn.

You’ll learn how to use Python through the use of its robust graphic libraries to bring insights to life and tell stories that help decision-making.

Explore different types of data visualisation

This course will introduce you to design fundamentals, allowing you to identify and critique components of effective visualised data, charts and the visualisation of complex relationships.

You’ll also get to design powerful visualisations using spreadsheet tools.

Create plots in Python using Matplotlib and time series data

Matplotlib is a powerful Python library for creating plots and charts.

You’ll be introduced to the library and time series data, one of the most commonly used data types. You’ll also master the basics of creating and customising plots using Python code, including custom colours, markers and styles.

Learn how to understand quantitative comparisons and statistical visualisations

Visualisations can be used to compare data in a quantitative manner. You’ll explore the different methods used in the creation of quantitative visualisations.

You’ll find out how to plot bar charts, histograms and scatter plots using Python’s plotting library, Matplotlib.

This course is designed for professionals who would like to grow their confidence in using Python to produce exploratory and explanatory visualisations and build dashboards to communicate insights.

  • A professional working with data on a regular basis or have a fundamental understanding of data analytics but wants to become more employable or progress in their career.
  • A business analyst or junior data analysts looking to further develop their data visualisation skills using Python.
  • An individual with existing programming capabilities looking to enter the data analytics field.

If you want to expand your knowledge on this subject, you may be interested in these courses from the same provider which share the same overall learning outcomes:

  • Data Visualisation with Python: Seaborn and Scatter Plots
  • Data Visualisation with Python: Bokeh and Advanced Layouts

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.

Syllabus

  • Introduction to visualisation and visualisation design fundamentals
    • Welcome to the course!
    • Introduction to visualisation
    • Visualisation design fundamentals
    • Wrap-up
  • Designing charts and visualising complex relationships
    • Introduction
    • Designing charts
    • Visualising complex relationships
    • Wrap-up
  • Introduction to Matplotlib and plotting time series data
    • Introduction
    • Introduction to Matplotlib
    • Plotting time series data using Matplotlib
    • Wrap-up
  • Quantitative comparisons, statistical visualisations, and sharing visualisations
    • Introduction
    • Quantitative comparisons and statistical visualisations
    • Sharing visualisations
    • Wrap-up

Taught by

Ed Marks

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