Transform how your organization builds trust in AI. Learn to design end‑to‑end data lineage and ethical governance frameworks that make AI explainable, auditable, and compliant—without slowing innovation.

Data Lineage & Ethical Frameworks for Responsible AI

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


Instructors: David Drummond
Access provided by Interbank
Recommended experience
What you'll learn
Translate business requirements into lineage models and control points
Capture and visualize lineage from source data to deployed models, build datasheets/model cards that make AI decisions explainable
Apply NIST AI RMF‑aligned assessments and define mitigations
Conduct privacy impact assessments and implement consent/retention controls & produce audit‑ready evidence packs and governance dashboards
Skills you'll gain
Details to know

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9 assignments
September 2025
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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 assignments
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 labs
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 assignments
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