The Modern Data Strategy for Enterprise Generative AI program offers a comprehensive journey along three courses—Data Frameworks for Gen AI, Advanced Data Techniques for Enterprise AI Systems, and Data Lineage & Ethical Frameworks for Responsible AI. This specialized program is designed to equip professionals with the right skills and knowledge with respect to modern data strategies, security and governance, and scalable AI systems. Learners will explore structured and unstructured data, metadata tagging, vector databases, unified data architectures, and responsible AI governance through hands-on labs, case studies, and expert-led sessions. With industry expert David Drummond leading the curriculum, the program manages real-world applications and enterprise needs.
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Modern Data Strategy for Enterprise Generative AI Specialization
Lead with Data. Govern with Confidence.. Apply data management, frameworks, and governance for modern, ethical, and scalable AI systems.
Instructors: David Drummond
Included with 
Recommended experience
Recommended experience
What you'll learn
Apply modern data strategy principles to design governed, scalable, and ethical data frameworks for Generative AI systems.
Design secure, interoperable data systems using metadata tagging, vector processing, and unified architectures for advanced AI.
Implement ethical and secure AI systems using modern governance frameworks and explainable AI principles.
Overview
What’s included
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September 2025
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Fractal Analytics
Specialization - 3 course series
What you'll learn
Explain how structured and unstructured data support GenAI applications and drive data strategy.
Apply the principles of modern data frameworks to ensure data quality, governance, and readiness for LLM-powered systems.
Analyze how ethical and governance principles shape modern data strategies for Gen AI.
Design and apply customized data taxonomies within a responsible data framework.
Skills you'll gain
What you'll learn
Explain the foundational role of data management, security, and architecture in supporting scalable and ethical AI systems.
Discuss the importance of cross-platform compatibility and its implementation across AI models, datasets, and data management systems.
Apply vector database and embedding techniques to organize, retrieve, and transform unstructured data efficiently across various use cases.
Utilize robust data architectures and explainable AI to enhance performance, transparency, and ethical decision-making in large-scale AI systems.
Skills you'll gain
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
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Frequently asked questions
The Modern Data Strategy for Enterprise Generative AI specialization is designed for professionals who want to lead AI initiatives with confidence and clarity. Through three hands-on courses, you’ll explore data frameworks, advanced techniques, and ethical governance tailored for enterprise-scale AI systems. You’ll work with structured and unstructured data, metadata tagging, vector databases, and unified architectures—all guided by industry expert David Drummond.
By the end of the program, you’ll be equipped to design AI-ready data ecosystems, implement responsible AI practices, and align data strategy with business goals. This specialization is important because it empowers you to navigate the fast-changing AI landscape with the skills and insight needed to drive innovation, ensure compliance, and create lasting impact.
What sets the Modern Data Strategy for Enterprise Generative AI specialization apart is its deep focus on modern, scalable data architectures and real-world enterprise applications. Unlike other programs, it empowers data professionals—not just data engineers—to work confidently across the full AI data pipeline. You’ll gain hands-on experience with cutting-edge tools like vector databases, unified data architectures, and metadata tagging, while mastering responsible AI governance. The curriculum, led by industry expert David Drummond, is designed to help you move beyond siloed roles and contribute strategically to enterprise AI systems. Whether you're a data scientist, engineer, or developer, this specialization gives you the skills to design, secure, and scale AI-ready data ecosystems that meet today’s business demands.
You’ll be able to design governed data pipelines, apply metadata tagging, implement responsible AI frameworks, and lead enterprise AI initiatives with confidence and accountability.
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Financial aid available,