As generative AI becomes deeply woven into enterprise workflows, the need for ethical, scalable, and trustworthy data practices has never been greater. This course dives into two foundational pillars of modern AI strategy: Traceable Data Lineage and Responsible AI Governance.

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Data Lineage & Ethical Frameworks for Responsible AI
This course is part of Modern Data Strategy for Enterprise Generative AI Specialization


Instructors: David Drummond
Included with
Recommended experience
What you'll learn
Explain the role of traceable data lineage in AI reliability
Apply governance frameworks to manage ethical and regulatory risks.
Tag and trace AI-generated content using modern tools.
Design scalable governance strategies for enterprise AI applications.
Skills you'll gain
Details to know

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September 2025
9 assignments
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There are 3 modules in this course
Explore the core principles of data governance and ethical AI. Learn how frameworks like C2PA and tools like DuckLake help verify content authenticity and detect misinformation. Understand global governance perspectives and how to embed trust into AI systems.
What's included
8 videos3 readings3 assignments1 plugin
Dive into the architecture of data pipelines and learn how to build them with governance in mind. Use tools like OpenLineage to visualize, monitor, and trace data across its lifecycle—ensuring transparency and compliance.
What's included
6 videos1 reading3 assignments2 ungraded labs1 plugin
Design AI systems that are both powerful and principled. Learn ethics-by-design workflows, governance automation, and advanced compliance strategies to future-proof your AI initiatives.
What's included
10 videos3 assignments1 plugin
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Frequently asked questions
This course provides practical frameworks and techniques for implementing ethical, traceable, and compliant data practices for AI systems. It's important because organizations face increasing regulatory scrutiny and public expectations regarding AI transparency and ethics.
This course is designed for professionals who need to ensure AI systems meet ethical standards and regulatory requirements while maintaining data traceability and governance.
You'll be able to design governance frameworks for AI systems, implement data lineage tracking, create ethics-by-design workflows, and establish content authenticity verification systems. These skills enable you to build responsible AI systems that maintain trust and compliance.
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