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Data Science: Data Storytelling and Presentation Skills

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Data Science: Data Storytelling and Presentation Skills

Instructor: Jennifer Sexton

Included with

Learn more

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

Prepare for a degree

Learn more

2 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

Prepare for a degree

Learn more

What you'll learn

How to review and improve data visualisations
How to design clear and concise presentation slides & communicate research findings effectively
How to write consistent and well-structured research report
The key skills and competencies of data science professionals

Skills you'll gain

Tools you'll learn

Generative AI

Details to know

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There are 2 modules in this course

This course helps you build the core communication skills needed in data science. You’ll learn how to review and improve data visualisations, design clear and concise presentation slides, and present insights in a way that is accurate and engaging.

You will explore key principles of scientific writing and practise discussing research findings with clarity and consistency. The course also introduces the skills and competencies expected of data science professionals, helping you understand how to communicate technical work to different audiences. By the end, you’ll be able to create stronger visuals, structure research reports effectively, and share your data stories with confidence.

Module details

In Week 1 of this short course, we will explore how presentation and verbal communication skills are vital for data scientists as they ensure clear articulation of project goals, progress and challenges.

What's included

15 readings3 assignments

15 readingsTotal 179 minutes

About this course10 minutes
How to study on this course10 minutes
Short course author10 minutes
1.1 Lesson 1 overview1 minute
1.2 Exploratory vs explanatory data visualisation15 minutes
1.4 Best practice and how to achieve it15 minutes
1.6 Next steps2 minutes
2.1 Lesson 2 overview 2 minutes
2.2 Creating a successful presentation 4 minutes
2.3 Selecting content and planning10 minutes
2.4 Slides and presentation aids30 minutes
2.6 Activity: Improving a slide45 minutes
2.7 Considering the audience: Approaches for differentiating between groups10 minutes
Take your data science skills further10 minutes
2.8 Next steps5 minutes

3 assignmentsTotal 50 minutes

1.3 Goals of explanatory data visualisation15 minutes
1.5 Improve these worked examples20 minutes
2.5 Multiple-choice questions: Identifying issues with slides15 minutes

This week addresses the topic of academic integrity, defines plagiarism and discusses when and how Generative AI can be used as a tool to support rather than replace critical analysis. 

What's included

11 readings3 assignments1 discussion prompt

11 readingsTotal 204 minutes

3.1 Overview of Lesson 32 minutes
3.2 Scientific writing20 minutes
3.3 Descriptive vs critical writing10 minutes
3.6 Plagiarism10 minutes
3.7 Next steps5 minutes
4.1 Overview of lesson 45 minutes
4.2 Introduction and policy documents15 minutes
4.5 Next steps5 minutes
4.6 Presenting data in practise: Reflective assignment120 minutes
Take your data science learning further2 minutes
Course Summary10 minutes

3 assignmentsTotal 50 minutes

3.4 Scientific writing: Review10 minutes
3.5 LaTeX in R Markdown: Review30 minutes
4.3 The basics of using Generative AI10 minutes

1 discussion promptTotal 10 minutes

4.4 Generative AI10 minutes

Prepare for a degree

Taking this course by University of Leeds may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.