Data Visualisation with Python

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Course Features



12 weeks


Delivery Method



Available on

Lifetime Access



Mobile, Desktop












4 hours per week


Teaching Type

Self Paced

Course Description

Are you looking to improve your data visualisation skills and Python skills?

Data analysis is becoming an increasingly important practice in many industries, including finance, healthcare, and education. This means that there is a growing demand for data analytics skills.

This ExpertTrack will teach you how to use Python libraries to perform data modelling and create engaging data visualisations.

You will be able to use Python functions like Matplotlib to create scatter plots and plot bar charts histograms.

Seaborn, another data-visualisation tool that combines aesthetic appeal with powerful technical insight, will also be covered. Bokeh can also be used to create complex interactive visualisations by using advanced layout widgets.

As you move through the courses, you will learn how to interpret statistical visualisations and quantitative comparisons. You'll also be able to identify various types of data plots.

This course will teach you how to show uncertainty in data by using confidence bands and point estimate intervals.

Many organisations are not able to effectively collect and analyse data but transform them into useful decision-making that creates organisational value.

This ExpertTrack will teach you advanced data visualization skills. These skills will allow you to bring insight to life and communicate data in a meaningful and accessible way.

These courses will show you how to create powerful visualisations using spreadsheet tools.

Your training will conclude with an exploration of data analytics as an emerging field, and the role of new technologies such as DataOps and UX design.

After completing all three courses, you will feel confident creating dashboards using a variety data visualization tools and applying data insight.

Yes. Yes. Job postings for data visualisation have increased by 540% in the past five year. Tableau skills are also highly sought after.

People who combine fundamental skills like data wrangling, statistical analysis, and Python can quickly gain traction as a data analyst or business owner in this expanding i!eld.

Course Overview


Alumni Network


International Faculty


Post Course Interactions


Instructor-Moderated Discussions

Skills You Will Gain


There are no prerequisites to joining this ExpertTrack

However its advised that you have some prior knowledge or experience working with data statistics and using spreadsheets

The learnings of this ExpertTrack will solidify and enhance any prior understanding of working with data and analytics as well as develop critical employability skills in using Python libraries for visualisation

During the ExpertTrack well be using Tableau Public and Excel

If you dont have Excel, you might find this online version useful

What You Will Learn

Leverage Python libraries to conduct data modeling and build compelling visualisations

Identify and critique components of effective visualisations, charts and visualisation of complex relationships

Define best practices for setting objectives and planning of the data analytics phases

Articulate the thought process of designing an application

Target Students

This ExpertTrack will grow your confidence in using Python to produce exploratory and explanatory visualisations,building dashboards, and communicating dashboard insights

It is suitable for professionals with a fundamental understanding of data analytics who work with data on a regular basis but want to become more employable or progress in their career

Business analysts and junior data analysts looking to further develop their data visualisation skills using Python

Individuals with existing programming capabilities looking to enter the data analytics field

Course Instructors

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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.
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