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Data Visualisation with Python: Bokeh and Advanced Layouts

Elevate your data visualisation skills and better communicate your data insights with the data visualisation package, Bokeh.

Data Visualisation with Python: Bokeh and Advanced Layouts
  • Duration4 weeks
  • Weekly study4 hours
  • 100% onlineLearn at your own paceHow it works
  • Included in an ExpertTrackCourse 3 of 3
  • Get full ExpertTrack access$39/monthFind out more

Learn how to use Bokeh in Python

On the first week of the course, you’ll explore the key functions of Bokeh and how it can be used to create interactive visualisations and dashboards.

You’ll weigh up the benefits of Bokeh compared to other data visualisation packages, and explore the concept of Glyphs within Python and how they can be customised.

Explore data plotting in Python

Once you’ve mastered the basics you’ll learn about plot layouts, advanced features of the layouts, and the application of advanced widgets on Bokeh.

By the end of week two, you’ll understand the basics of layouts, interactions, and annotations, as well as being able to connect sliders to plots by updating plots from selects and putting it all together.

Understand the phases of data exploration

In week three, you’ll engage in an end to end exploration of data analysis. You’ll explore the various phases of data exploration and learn more about data ethics and the role of responsible storytelling.

You’ll also have the chance to conduct extended data analysis and visualisation, bringing all your learning together.

On the final week of the course, you’ll look at data analytics as an emerging field, the role of DataOps and UX design, and new technologies that have the potential to enhance your prospects as a data professional.

Throughout the course, you’ll have the opportunity to engage in a variety of practical exercises and complete real-world tasks that will place you in the role of a data analyst for a boutique streaming service.

Syllabus

  • Week 1

    Introduction to Bokeh, basic plotting, and layouts

    • Welcome to the course!

      Introduction to the course, information about the optional project tasks, and an overview of Week 1.

    • Introduction to Bokeh

      In this activity, you'll learn about a visualisation library called Bokeh.

    • Basic plotting with Bokeh

      Learn about how Bokeh can be used to make visualisations and specific Bokeh components.

    • Layouts, interactions and annotations

      In this activity, you will explore the application of a plot layout and learn the advanced feature of the layout. You will also get hands-on practice in improving your data style using different functions and techniques.

    • Wrap-up

      Now it's time to reflect on your learning throughout the week and look to what's next!

  • Week 2

    Annotations and interactive visualisations

    • Introduction

      Welcome to Week 2! Let's first introduce the week's topics and outcomes. This week, we’ll explore the application of a plot layout and learn the advanced feature of the layout, and application of advanced widgets on Bokeh.

    • Layouts, interactions, and annotations

      In this activity, you will explore the application of a plot layout and learn the advanced feature of the layout. You will also get hands-on practice in improving your data style using different functions and techniques.

    • Building interactive visualisations

      In this activity, you'll explore the application of advanced widgets on Bokeh. You will also get hands-on practice in improving your visualisation and making it more interactive using different functions on Bokeh.

    • Wrap-up

      Let's wrap up what we covered this week and reflect on the learning so far.

  • Week 3

    An end-to-end exploration and analysis

    • Introduction

      An introduction to the week's topics and key learnings.

    • End-to-end data exploration and analysis

      Conduct a detailed data exploration process, visualise your data, and then create an interactive using Bokeh.

    • Ethical concerns

      In this activity, we’ll introduce several broad ethical elements, or issues, facing data analysts today.

    • Wrap-up

      Now it's time to reflect on your learning throughout the week and look to what's next!

  • Week 4

    New ways of working and looking ahead

    • Introduction

      Welcome to Week 4! Let's first introduce the week's topics and outcomes.

    • New ways of working

      In this activity, we will explore digital business transformation with the help of some examples.

    • Next steps

      In this final activity, you'll learn about the importance of data analytics (as well as visualisation) and programming with Python as accelerators in your career.

    • Wrap-up

      To complete the week and course, let’s recap the key points covered so far.

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What will you achieve?

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

  • Use Bokeh to create interactive visualisations and dashboards
  • Articulate the thought process of designing an application
  • Define best practices for setting objectives and planning of the data analytics phases

Who is the course for?

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 want 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.

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?

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 jointly owned by The Open University and The SEEK Group and has been providing online courses for learners around the world over the last eight years.

In collaboration with

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Endorsed by

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About this ExpertTrack

Learn to leverage Python libraries to conduct data modeling and build compelling visualisations.

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