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.
In this hands‑on course, you’ll capture provenance from source to model, manage metadata and documentation (datasheets, model cards), and operationalize risk controls aligned to industry guidance.
Practice integrating lineage with the AI lifecycle—ingestion, training, deployment, monitoring—and implement privacy, fairness, and quality assurance guardrails. You’ll produce audit‑ready evidence packs, dashboards, and review artifacts that withstand scrutiny from leadership, regulators, and clients.
By the end, you’ll design governed AI workflows, evaluate risks and mitigations, and institutionalize ethical review gates for reliable, accountable outcomes.
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.
涵盖的内容
8个视频3篇阅读材料3个作业
显示有关单元内容的信息
8个视频•总计36分钟
Course Introduction•2分钟
What is Data Governance•5分钟
Frameworks of Data Governance•6分钟
DuckLake for Data Governance•4分钟
Tagging AI-Generated Content •4分钟
C2PA Explained: Digital Content Provenance •5分钟
Misinformation Detection Usecase •5分钟
Building trust in AI systems•5分钟
3篇阅读材料•总计17分钟
Course syllabus•5分钟
Disclaimer•2分钟
World Economic Forum – AI Governance Framework•10分钟
3个作业•总计80分钟
Understanding Data Governance and Its Frameworks•20分钟
Content Integrity & Oversight•30分钟
Governance Foundations and Content Authenticity•30分钟
Data Pipelines and Lineage
第 2 单元•小时 后完成
单元详情
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.
涵盖的内容
6个视频1篇阅读材料3个作业2个非评分实验室
显示有关单元内容的信息
6个视频•总计33分钟
Introduction to Data Pipelines•5分钟
Building Governance into Data Pipelines•4分钟
Visualizing a Data Pipeline•9分钟
Visualizing Data Lineage•6分钟
Lineage as Pipeline Intelligence•5分钟
Implementing Data Lineage Tracking•5分钟
1篇阅读材料•总计10分钟
Importance of Data Pipelines•10分钟
3个作业•总计80分钟
Designing and Governing Modern Data Pipelines•20分钟
Pipeline Tracking & Lineage•30分钟
Data Pipelines and Lineage•30分钟
2个非评分实验室•总计90分钟
Visualizing and Monitoring Data Flows•45分钟
Data Lineage Tracking•45分钟
Responsible AI & Applied Governance
第 3 单元•小时 后完成
单元详情
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.
涵盖的内容
10个视频3个作业
显示有关单元内容的信息
10个视频•总计49分钟
Principles of Responsible AI •5分钟
Data Governance and RAI•6分钟
Data Governance and Ethical AI•4分钟
Designing Ethics-by-Design Workflows•4分钟
Implementing Governance Automation with Machine Learning•4分钟
Evaluating Governance Effectiveness •5分钟
Security in Governance Frameworks•5分钟
Advanced Governance Patterns•4分钟
Future Trends in AI & Data Strategy •6分钟
Tying it all back•5分钟
3个作业•总计80分钟
Principles and Practices of Responsible AI through Data Governance•20分钟
Continuous learning is imperative to stay relevant in the world of Data Analytics and AI. Fractal Analytics Academy is your learning partner for all your learning requirements.
We offer a variety of learning solutions; from instructor led trainings to blended learning and eLearning covering consulting and business skills, technical skills and life skills.
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.
Who is this course for?
This course is designed for professionals who need to ensure AI systems meet ethical standards and regulatory requirements while maintaining data traceability and governance.
What will I be able to do after completing this course?
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.
What background knowledge is necessary?
A working understanding of data management concepts, familiarity with AI systems, and basic knowledge of data ethics will help you get the most from this course.
What topics are covered in this course?
The course covers data governance principles, traceable data lineage, content authenticity frameworks, ethics-by-design methodologies, governance automation, and regulatory compliance for AI systems.
What is the learning experience of this course?
The course combines theoretical instructions with practical application through hands-on labs, demos, case studies, and expert-led dialogues. You'll work on real-world governance challenges and produce documentation and frameworks applicable to your organization.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.