Data Science: Data Storytelling and Presentation Skills

Data Science: Data Storytelling and Presentation Skills

Instructor: Jennifer Sexton

Access provided by Xavier School of Management, XLRI

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

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

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

Assessments

6 assignments

Taught in English

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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.

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 readings Total 179 minutes

About this course 10 minutes
How to study on this course 10 minutes
Short course author 10 minutes
1.1 Lesson 1 overview 1 minute
1.2 Exploratory vs explanatory data visualisation 15 minutes
1.4 Best practice and how to achieve it 15 minutes
1.6 Next steps 2 minutes
2.1 Lesson 2 overview 2 minutes
2.2 Creating a successful presentation 4 minutes
2.3 Selecting content and planning 10 minutes
2.4 Slides and presentation aids 30 minutes
2.6 Activity: Improving a slide 45 minutes
2.7 Considering the audience: Approaches for differentiating between groups 10 minutes
Take your data science skills further 10 minutes
2.8 Next steps 5 minutes

3 assignments Total 50 minutes

1.3 Goals of explanatory data visualisation 15 minutes
1.5 Improve these worked examples 20 minutes
2.5 Multiple-choice questions: Identifying issues with slides 15 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 readings Total 204 minutes

3.1 Overview of Lesson 3 2 minutes
3.2 Scientific writing 20 minutes
3.3 Descriptive vs critical writing 10 minutes
3.6 Plagiarism 10 minutes
3.7 Next steps 5 minutes
4.1 Overview of lesson 4 5 minutes
4.2 Introduction and policy documents 15 minutes
4.5 Next steps 5 minutes
4.6 Presenting data in practise: Reflective assignment 120 minutes
Take your data science learning further 2 minutes
Course Summary 10 minutes

3 assignments Total 50 minutes

3.4 Scientific writing: Review 10 minutes
3.5 LaTeX in R Markdown: Review 30 minutes
4.3 The basics of using Generative AI 10 minutes

1 discussion prompt Total 10 minutes

4.4 Generative AI 10 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.