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Data Science: Ethical decision-making in practice

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Data Science: Ethical decision-making in practice

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Prepare for a degree
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Prepare for a degree

What you'll learn

  • How to apply professional ethics to real data science work.

  • How to make ethical, informed decisions when planning and evaluating data projects.

  • How to understand responsibility and assess the possible consequences of AI within a project context.

Details to know

Recently updated!

December 2025

Assessments

1 assignment

Taught in English

There are 2 modules in this course

Learn how to make ethical and responsible decisions in real data science projects. This course introduces the foundations of data ethics, professional ethics, and ethical decision-making, giving you the tools to appraise project methods with confidence.

You’ll explore how responsible choices shape outcomes, how to recognise risks in data- driven work, and how to apply ethical frameworks throughout the project lifecycle. Designed with practical application in mind, the course helps you build the judgement needed for working in modern data science roles. By the end, you’ll understand the conditions for responsibility, be able to evaluate methodological decisions, and feel equipped to navigate ethical challenges in data-intensive environments.

In this short course, you will explore the features and practices common to professions and consider whether the field of data science should professionalise or not. You will also examine the conditions for responsibility and apply them to the possible consequences of data science. You will evaluate the value of professions having their own codes of ethics and what the implications could be for your practice in the field of data science. Finally, you will consider the circumstances under which data scientists may have a responsibility to speak out against wrongdoing.

What's included

17 readings1 discussion prompt

17 readings•Total 107 minutes
  • About this course•10 minutes
  • How to study this course•5 minutes
  • Short course author•2 minutes
  • 1.1 Overview of Lesson 1•2 minutes
  • 1.2 Introduction and three distinct meanings of a profession•10 minutes
  • 1.3 Introduction to professional ethics•5 minutes
  • 1.4 Honesty•5 minutes
  • 1.5 Integrity•5 minutes
  • 1.6 Reflective activity: Theories of integrity•20 minutes
  • 1.7 Trust and confidentiality•5 minutes
  • 1.8 Impartiality and conflicts of interest•2 minutes
  • 1.9 Next steps•2 minutes
  • 2.1 Overview of Lesson 2•10 minutes
  • 2.2 The purpose of a code of ethics•10 minutes
  • 2.3 Codes of ethics and data science•2 minutes
  • 2.5 Next steps•2 minutes
  • Take your learning further: MSc Data Science (Statistics) Online•10 minutes
1 discussion prompt•Total 60 minutes
  • 2.4 Should data science be considered a profession?•60 minutes

What's included

6 readings1 assignment

6 readings•Total 40 minutes
  • 3.1 Overview of Lesson 3•10 minutes
  • 3.2 The distance between programmer and end product•5 minutes
  • 3.3 Whistle-blowing•10 minutes
  • 3.4 Next steps•2 minutes
  • Take your learning further•3 minutes
  • 4.2 Reflective activity: Reflecting on ethical approaches•10 minutes
1 assignment•Total 30 minutes
  • 4.1 MCQ•30 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.

Instructor

University of Leeds
1 Course•69 learners

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