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Data Ethics Fundamentals

Foundations to develop organizational ethical frameworks.

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About this course

In today’s digital world, understanding data ethics is essential. As data-driven technologies expand, so do ethical challenges, from privacy concerns to transparency and fairness issues. Misuse of data can violate rights, erode trust, and harm reputations. This course equips developers, managers, and leaders to make ethical decisions with confidence, fostering public trust through responsible data management.

In this course, you’ll explore foundational principles of data ethics, focusing on four key frameworks—Deontology, Utilitarianism, Virtue Ethics, and Ethics of Belief. Real-world examples and case studies will help you apply these frameworks to challenges like data privacy, algorithmic bias, and user consent. Each module encourages critical thinking, preparing you to navigate complex data decisions with clarity and responsibility.

What you'll learn—and how you can apply it

By the end of this course, you’ll understand:

  • The key principles and importance of data ethics in today's digital landscape
  • How to create policies and practices that align with ethical guidelines and support responsible data use
  • Different ethical theories, such as Deontology, Utilitarianism, Virtue Ethics, and Ethics of Belief, and how to apply them to real-world data ethics challenges
  • How to balance organizational self-interest with ethical responsibility

And you’ll be able to:

  • Analyze and address data-related ethical dilemmas using practical examples, with a focus on applying ethical frameworks to scenarios like data privacy, algorithmic bias, and transparency
  • Create ethical policies for data practice
  • Develop skills for effectively communicating ethical decisions and justifications to help build an ethical culture within your organization
  • Anticipate and address future ethical data challenges

This training is for you because…

  • You’re an aspiring data professional who wants to develop essential ethical skills to navigate a complex data landscape
  • You’re a business leader or manager who wants to equip yourself with the knowledge to make informed, ethical decisions that protect your organization's reputation and build public trust
  • You’re a technology enthusiasts who wants to enhance your technical expertise with a strong ethical foundation to ensure responsible data handling and compliance with regulatory standards

About the instructor

Jose Mesa is a Staff Software Engineer at Anaconda who supports development, data science, modeling, analytics, and educational partnerships (outreach). Before joining Anaconda, Jose was a Facilities Engineer at Chevron's Subsea, Civil, and Marine Engineering unit, where he integrated data science techniques in the design optimization, analysis, and real-time monitoring of offshore structures. He received his Ph.D. from the University of Michigan Naval Architecture and Marine Engineering (NA&ME) department and held two MSE degrees in Aerospace Engineering and NA&ME. He completed his dual Bachelor's in Civil Engineering and Land Surveying at the University of Puerto Rico.

Questions? Issues? Contact learning@anaconda.com.

Curriculum01:36:26

  • Course Overview 00:06:21
  • What is Ethics?
  • What is Ethics? 00:02:58
  • Importance of Data Ethics 00:05:25
  • Preview
    How Ethics Affects Data 00:03:05
  • Ethical Frameworks
  • Ethical Methodologies 00:02:36
  • Deontology Framework 00:02:14
  • Utilitarianism Framework 00:01:41
  • Virtue Ethics Framework 00:02:55
  • Ethics of Belief Framework 00:03:06
  • Ethical Framework for Your Organization 00:04:19
  • Data Ethical Challenges
  • Misuse in Data Handling 00:08:06
  • Typical Data Ethics Challenges 00:02:14
  • Data Privacy and Security Challenges 00:02:48
  • Data Bias Challenges 00:02:35
  • Transparency and Consent Challenges 00:02:58
  • Data Misuse
  • Internal Organizational Data Misuse 00:05:07
  • Customer Data Misuse 00:04:39
  • Addressing Ethical Challenges 00:06:20
  • Data Ethics Challenges Examples
  • Data Privacy and User Consent 00:05:04
  • Algorithmic Bias in Hiring 00:05:06
  • Targeted Advertising and User Profiling 00:05:02
  • Data Retention and Security 00:06:17
  • Conclusion
  • Data Ethics Fundamentals: Practice Quiz
  • Summary 00:05:30
  • End of Course Survey
  • Course Completion

About this course

In today’s digital world, understanding data ethics is essential. As data-driven technologies expand, so do ethical challenges, from privacy concerns to transparency and fairness issues. Misuse of data can violate rights, erode trust, and harm reputations. This course equips developers, managers, and leaders to make ethical decisions with confidence, fostering public trust through responsible data management.

In this course, you’ll explore foundational principles of data ethics, focusing on four key frameworks—Deontology, Utilitarianism, Virtue Ethics, and Ethics of Belief. Real-world examples and case studies will help you apply these frameworks to challenges like data privacy, algorithmic bias, and user consent. Each module encourages critical thinking, preparing you to navigate complex data decisions with clarity and responsibility.

What you'll learn—and how you can apply it

By the end of this course, you’ll understand:

  • The key principles and importance of data ethics in today's digital landscape
  • How to create policies and practices that align with ethical guidelines and support responsible data use
  • Different ethical theories, such as Deontology, Utilitarianism, Virtue Ethics, and Ethics of Belief, and how to apply them to real-world data ethics challenges
  • How to balance organizational self-interest with ethical responsibility

And you’ll be able to:

  • Analyze and address data-related ethical dilemmas using practical examples, with a focus on applying ethical frameworks to scenarios like data privacy, algorithmic bias, and transparency
  • Create ethical policies for data practice
  • Develop skills for effectively communicating ethical decisions and justifications to help build an ethical culture within your organization
  • Anticipate and address future ethical data challenges

This training is for you because…

  • You’re an aspiring data professional who wants to develop essential ethical skills to navigate a complex data landscape
  • You’re a business leader or manager who wants to equip yourself with the knowledge to make informed, ethical decisions that protect your organization's reputation and build public trust
  • You’re a technology enthusiasts who wants to enhance your technical expertise with a strong ethical foundation to ensure responsible data handling and compliance with regulatory standards

About the instructor

Jose Mesa is a Staff Software Engineer at Anaconda who supports development, data science, modeling, analytics, and educational partnerships (outreach). Before joining Anaconda, Jose was a Facilities Engineer at Chevron's Subsea, Civil, and Marine Engineering unit, where he integrated data science techniques in the design optimization, analysis, and real-time monitoring of offshore structures. He received his Ph.D. from the University of Michigan Naval Architecture and Marine Engineering (NA&ME) department and held two MSE degrees in Aerospace Engineering and NA&ME. He completed his dual Bachelor's in Civil Engineering and Land Surveying at the University of Puerto Rico.

Questions? Issues? Contact learning@anaconda.com.

Curriculum01:36:26

  • Course Overview 00:06:21
  • What is Ethics?
  • What is Ethics? 00:02:58
  • Importance of Data Ethics 00:05:25
  • Preview
    How Ethics Affects Data 00:03:05
  • Ethical Frameworks
  • Ethical Methodologies 00:02:36
  • Deontology Framework 00:02:14
  • Utilitarianism Framework 00:01:41
  • Virtue Ethics Framework 00:02:55
  • Ethics of Belief Framework 00:03:06
  • Ethical Framework for Your Organization 00:04:19
  • Data Ethical Challenges
  • Misuse in Data Handling 00:08:06
  • Typical Data Ethics Challenges 00:02:14
  • Data Privacy and Security Challenges 00:02:48
  • Data Bias Challenges 00:02:35
  • Transparency and Consent Challenges 00:02:58
  • Data Misuse
  • Internal Organizational Data Misuse 00:05:07
  • Customer Data Misuse 00:04:39
  • Addressing Ethical Challenges 00:06:20
  • Data Ethics Challenges Examples
  • Data Privacy and User Consent 00:05:04
  • Algorithmic Bias in Hiring 00:05:06
  • Targeted Advertising and User Profiling 00:05:02
  • Data Retention and Security 00:06:17
  • Conclusion
  • Data Ethics Fundamentals: Practice Quiz
  • Summary 00:05:30
  • End of Course Survey
  • Course Completion