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.
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
Skills you'll gain
- LLM Application
- Data Governance
- Data Store
- Data Architecture
- Data Pipelines
- Data Security
- Data Strategy
- Artificial Intelligence and Machine Learning (AI/ML)
- Metadata Management
- Governance
- Data Integrity
- Interoperability
- Data Ethics
- Responsible AI
- Data Loss Prevention
- Data Management
- Data Storage
- Artificial Intelligence
Tools you'll learn
What’s included
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September 2025
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Specialization - 3 course series
What you'll learn
How structured and unstructured data support GenAI applications
Principles of modern data frameworks for AI readiness
Ethical and governance considerations in AI data strategy
Designing enterprise-grade taxonomies and data foundations
Skills you'll gain
What you'll learn
Explain the foundational role of data management, security, and architecture in enterprise AI.
Implement cross-platform compatibility across AI models, datasets, and systems.
Apply vector database and embedding techniques to manage unstructured data.
Build unified data architectures using Iceberg, Delta, and DuckLake.
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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Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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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,