Data Science Ethics from Coursera

What are the ethical considerations regarding the privacy and control of consumer information and big data, especially in the aftermath of recent large-scale data breaches?

This course provides a framework to analyze these concerns as you examine the ethical and privacy implications of collecting and managing big data. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency as you gain a deeper understanding of the importance of a shared set of ethical values. You will examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems while also learning best practices for responsible data management, understanding the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten."

This course will help you answer questions such as who owns data, how do we value privacy, how to receive informed consent and what it means to be fair.

Data scientists and anyone beginning to use or expand their use of data will benefit from this course. No particular previous knowledge needed.

What's inside

Syllabus

What are Ethics?

Module 1 of this course establishes a basic foundation in the notion of simple utilitarian ethics we use for this course. The lecture material and the quiz questions are designed to get most people to come to an agreement about right and wrong, using the utilitarian framework taught here. If you bring your own moral sense to bear, or think hard about possible counter-arguments, it is likely that you can arrive at a different conclusion. But that discussion is not what this course is about. So resist that temptation, so that we can jointly lay a common foundation for the rest of this course.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Suitable for data analysts with limited prior knowledge of ethics

Delves into complex topics like algorithmic fairness and societal consequences of data science

Practical examples and case studies illustrate ethical dilemmas in data management

Covers foundational concepts in ethics, such as informed consent and privacy principles

Emphasizes the importance of shared ethical values in data science practices

Provides a framework for analyzing ethical concerns related to data privacy and control

Reviews summary

Foundations of data science ethics

According to learners, this course provides a solid foundation in the ethical considerations relevant to data science. Many found the topics covered, such as privacy, data ownership, and algorithmic fairness, to be highly relevant and important in the current data landscape. Reviewers frequently praised the clear and accessible lectures, noting that they make complex concepts easy to understand. While well-suited as a good introduction for beginners or those new to the subject, several students felt the course was too basic and lacked sufficient depth for individuals with prior experience in ethics or data analysis. The course is seen as a valuable starting point for raising awareness on critical ethical issues.

Assessments help solidify understanding.

"the quizzes help reinforce the learning."

"the quizzes solidify the concepts..."

"The quizzes tested understanding effectively."

Concepts explained clearly and easy to follow.

"The content is presented clearly..."

"The explanations are clear."

"The structure makes it easy to follow..."

"The concepts are explained clearly..."

"It’s accessible and easy to digest."

Covers critical and timely ethical issues.

"Highly relevant and provides a much-needed framework..."

"It tackles important, timely topics in data science ethics."

"The coverage of privacy and the 'right to be forgotten' felt very current."

"Absolutely essential course for anyone touching data."

"The ethical dimension is often overlooked in technical training."

Excellent introduction to core ethical concepts.

"A concise, well-structured course that effectively introduces the ethical considerations..."

"providing a solid foundational understanding."

"This course is a great starting point for understanding data ethics..."

"It gives a good overview..."

"Good for getting the core concepts down."

May lack depth for those with prior background.

"While it doesn't delve into extreme technical depth, which might disappoint some..."

"it felt a bit too basic for me. As someone with some background..."

"It gives a good overview, but doesn't really challenge you to think deeply..."

"But the coverage felt superficial at times."

"Might be too simple if you already know about these topics."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Science Ethics with these activities:

Review basic concepts of statistics and probability

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Ensure a strong foundation in statistics and probability for understanding data analysis techniques.

Browse courses on Statistics

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Revisit textbooks or online resources to refresh your understanding of basic statistical concepts
Practice solving probability problems to enhance your analytical skills

Review the book 'Ethics of Big Data' by Viktor Mayer-Schönberger

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Gain a comprehensive understanding of the ethical implications of big data from a leading expert.

View Access Rules on Amazon

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Read the book thoroughly and take notes on key concepts and arguments
Identify the main ethical challenges discussed in the book
Summarize the author's proposed solutions and evaluate their strengths and weaknesses

Practice exercises on data privacy and ethics

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Reinforce understanding of data privacy and ethical considerations through repetitive exercises.

Browse courses on Data Privacy

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Complete the quizzes at the end of each module to test your understanding
Participate in the discussion forums to engage with others and discuss ethical scenarios

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Participate in peer discussions on data ethics cases

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Gain diverse perspectives and enhance critical thinking skills by engaging in peer discussions.

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Join or create study groups with classmates to discuss course materials
Engage in online forums or discussion boards to share insights and learn from others

Follow tutorials on data ethics and privacy best practices

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Enhance knowledge of ethical data practices by following guided tutorials from experts.

Browse courses on Data Privacy

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Explore online resources and videos to gain additional insights into data privacy and ethics
Attend webinars or online workshops on best practices for handling sensitive data

Attend a workshop on responsible data management

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Expand knowledge and skills in responsible data management through hands-on learning.

Browse courses on Data Privacy

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Identify and attend workshops or seminars on data ethics and privacy best practices
Participate actively in discussions and ask questions to gain insights from experts in the field

Create a presentation on the ethical implications of big data

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Deepen understanding of the ethical considerations in big data by creating a presentation.

Browse courses on Big Data

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Research and gather information on the ethical implications of big data collection and use
Develop a compelling narrative that highlights the key ethical issues and their potential impact
Design engaging slides and visuals to support your presentation
Practice presenting your ideas clearly and effectively

Develop a data ethics policy for a hypothetical organization

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Apply ethical principles to real-world scenarios by creating a comprehensive data ethics policy.

Browse courses on Data Ethics

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Research and analyze existing data ethics policies and frameworks
Identify the specific ethical considerations relevant to the hypothetical organization
Develop a clear and concise policy that addresses the identified ethical issues
Include mechanisms for monitoring and enforcing the policy

Career center

Learners who complete Data Science Ethics will develop knowledge and skills that may be useful to these careers:

Data Ethics Officer

Data Ethics Officers are responsible for ensuring that their company's use of data is ethical and responsible. This course would provide a comprehensive overview of data ethics, including topics such as privacy, algorithmic fairness, and societal consequences of data science. This knowledge would be essential for Data Ethics Officers who want to ensure that their company's use of data is ethical and responsible.

See salaries and explore the career path for Data Ethics Officer

Data Governance Specialist

Data Governance Specialists are responsible for developing and implementing policies and procedures to ensure that their company's data is used ethically and responsibly. This course would provide a strong foundation in data ethics, which is essential for Data Governance Specialists. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Data Governance Specialist

Data Scientist

Data Scientists analyze data to extract meaningful insights that can be used to make better decisions. This course would provide a strong foundation in data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science. This knowledge would be invaluable to Data Scientists who want to ensure that their work is ethical and responsible.

See salaries and explore the career path for Data Scientist

Privacy Officer

Privacy Officers are responsible for protecting their company's data from unauthorized access and use. This course would provide a strong foundation in data ethics, which is essential for Privacy Officers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Privacy Officer

Information Security Analyst

Information Security Analysts are responsible for protecting their company's data from unauthorized access and use. This course would provide a strong foundation in data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Information Security Analyst

Data Analyst

Data Analysts use data to identify trends and patterns that can help businesses make better decisions. This course would provide a solid foundation in data ethics, which is becoming increasingly important as businesses collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science. This knowledge would be invaluable to Data Analysts who want to ensure that their work is ethical and responsible.

See salaries and explore the career path for Data Analyst

Risk Analyst

Risk Analysts are responsible for identifying and assessing risks to their company's data. This course would provide a strong foundation in data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Risk Analyst

Business Intelligence Analyst

Business Intelligence Analysts use data to help businesses understand their customers and make better decisions. This course would provide a strong foundation in data ethics, which is becoming increasingly important as businesses collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science. This knowledge would be invaluable to Business Intelligence Analysts who want to ensure that their work is ethical and responsible.

See salaries and explore the career path for Business Intelligence Analyst

Compliance Officer

Compliance Officers are responsible for ensuring that their company complies with applicable laws and regulations. This course would provide a strong foundation in data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Compliance Officer

Auditor

Auditors are responsible for reviewing and evaluating their company's financial and operational data. This course would provide a strong foundation in data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Auditor

Financial Analyst

Financial Analysts are responsible for analyzing financial data to make investment recommendations. This course would provide a strong foundation in data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Financial Analyst

Investment Banker

Investment Bankers advise companies on mergers and acquisitions, capital raising, and other financial transactions. This course would provide a solid foundation in data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

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Management Consultant

Management Consultants advise companies on a wide range of business issues, including strategy, operations, and technology. This course would provide a broad overview of data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Management Consultant

Product Manager

Product Managers are responsible for developing and managing products. This course would provide a basic understanding of data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Product Manager

Software Engineer

Software Engineers design, develop, and maintain software applications. This course would provide a basic understanding of data ethics, which is becoming increasingly important as companies collect more data on their customers. The course covers topics such as privacy, algorithmic fairness, and societal consequences of data science.

See salaries and explore the career path for Software Engineer