Overview
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.
You’ll start by mastering data governance principles—learning how to build transparent systems using real-world frameworks. Then, explore the technical side of lineage:
visualizing data pipelines, capturing metadata, and tracing data across its lifecycle with tools like OpenLineage.
But governance isn’t just technical. You’ll tackle the ethical dimensions of AI—embedding responsibility into workflows, tagging AI-generated content with tools like SynthID, and aligning with global standards to ensure compliance and trust.
Through hands-on labs, interactive demos, and expert-led case studies, you’ll gain practical skills to build traceable pipelines and design governance structures that support complex AI systems. Enroll today!
Syllabus
- Governance Foundations and Content Authenticity
As AI-generated content and data-driven systems become central to digital ecosystems, organizations must adopt strong governance practices to ensure transparency, accountability, and trust. This module introduces the need for data governance, explores its core concepts and frameworks, and explains how provenance technologies like C2PA help verify digital content authenticity. You'll learn how to tag AI-generated content, detect misinformation, and apply ethical AI principles in real-time environments. The module also covers tools like DuckLake, use cases in misinformation detection, and global perspectives such as the World Economic Forum’s AI Governance Framework—equipping you to build responsible, resilient, and trustworthy AI systems.
- Data Pipelines and Lineage
In this module, you’ll dive into the world of data pipelines—the invisible engines powering modern analytics and AI. You’ll explore why they matter, how to build them with governance in mind, and what it takes to keep them running smoothly. You’ll get hands-on with demos that show how to visualize and monitor data flows, and discover how data lineage helps track where data comes from, how it changes, and where it goes. By the end, you’ll understand how to design smarter, more trustworthy pipelines that support transparency, compliance, and real-time decision-making.
- Responsible AI & Applied Governance
In this module, you’ll explore how to build AI systems that are not only powerful but also principled. From understanding the core principles of responsible AI to designing ethics-by-design workflows, you’ll learn how to embed trust and accountability into every stage of the AI lifecycle. Discover how governance automation, security frameworks, and advanced governance patterns can elevate your data strategy, while staying ahead of future trends in AI and compliance. Whether you're shaping policy or building systems, this module equips you to lead with integrity in the age of intelligent technology.
Taught by
David Drummond and Fractal Analytics Academy
Subjects
Computer Science
