How long does it take to complete the Specialization?

4 to 6 weeks per course, depending on your pace. Total: ~12 to 18 weeks to complete the full specialization.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

What is the refund policy?

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

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.

Can I take the course for free?

No, you cannot take this course for free. 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. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Spezialisierung für Modern Data Strategy for Enterprise Generative AI

Diese spezialisierung ist nicht verfügbar in Deutsch (Deutschland)

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Spezialisierung für Modern Data Strategy for Enterprise Generative AI

Lead with Data. Govern with Confidence.. Apply data management, frameworks, and governance for modern, ethical, and scalable AI systems.

Dozenten: David Drummond

Bei Coursera Plus enthalten

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3-teilige Kursreihe

Befassen Sie sich eingehend mit einem Thema

Stufe Mittel

Empfohlene Erfahrung

4 Wochen zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

3-teilige Kursreihe

Befassen Sie sich eingehend mit einem Thema

Stufe Mittel

Empfohlene Erfahrung

4 Wochen zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

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.

Kompetenzen, die Sie erwerben

Kategorie: Responsible AI
Kategorie: Data Governance
Kategorie: Metadata Management
Kategorie: Artificial Intelligence
Kategorie: Data Strategy
Kategorie: Information Privacy
Kategorie: LLM Application
Kategorie: Data Management
Kategorie: Generative AI
Kategorie: Artificial Intelligence and Machine Learning (AI/ML)
Kategorie: Data Architecture
Kategorie: Data Store

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Unterrichtet in Englisch

Kürzlich aktualisiert!

September 2025

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Erwerben Sie ein Karrierezertifikat von Fractal Analytics.

Spezialisierung - 3 Kursreihen

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.

Praktisches Lernprojekt

Learners will engage in immersive, project-based experiences that mirror real-world enterprise challenges in deploying generative AI responsibly and at scale. These projects span the full AI lifecycle—from data ingestion and pipeline design to governance, security, and ethical oversight. Participants will build governed data pipelines, apply metadata tagging for content authenticity, and implement scalable architectures using tools like OpenLineage, SynthID, and DuckLake. They’ll also simulate scenarios such as misinformation detection, regulatory compliance, and explainable AI deployment. Through hands-on labs, interactive demos, and expert-led discussions, learners will apply modern data frameworks, lineage tracking, and governance automation to solve authentic problems, gaining practical skills to lead enterprise-grade AI initiatives with confidence and accountability.

Data Frameworks for Generative AI

KURS 11 Stunde

Was Sie lernen werden

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

Kompetenzen, die Sie erwerben

Kategorie: Data Science

Kategorie: Machine Learning

Kategorie: Data Ethics

Kategorie: Generative AI

Kategorie: AI Product Strategy

Kategorie: Data Structures

Kategorie: LLM Application

Advanced Data Techniques for Enterprise AI Systems

KURS 211 Stunden

Was Sie lernen werden

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.

Kompetenzen, die Sie erwerben

Kategorie: Data Governance

Kategorie: Metadata Management

Kategorie: Interoperability

Kategorie: Zero Trust Network Access

Kategorie: Data Security

Kategorie: Data Management

Kategorie: Data Strategy

Kategorie: Agentic systems

Kategorie: Machine Learning

Kategorie: Data Storage

Kategorie: Generative AI Agents

Kategorie: Data Store

Kategorie: Data Ethics

Kategorie: Large Language Modeling

Kategorie: Data Pipelines

Kategorie: Data Architecture

Kategorie: Threat Modeling

Kategorie: Data Processing

Kategorie: Responsible AI

Data Lineage & Ethical Frameworks for Responsible AI

KURS 38 Stunden

Was Sie lernen werden

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.

Kompetenzen, die Sie erwerben

Kategorie: Data Governance

Kategorie: Responsible AI

Kategorie: Data Pipelines

Kategorie: Data Ethics

Kategorie: Data Strategy

Kategorie: Artificial Intelligence

Kategorie: Data Quality

Kategorie: Metadata Management

Kategorie: Generative AI

Kategorie: Data Management

Kategorie: Information Privacy

Kategorie: Real Time Data

Erwerben Sie ein Karrierezertifikat.

Fügen Sie dieses Zeugnis Ihrem LinkedIn-Profil, Lebenslauf oder CV hinzu. Teilen Sie sie in Social Media und in Ihrer Leistungsbeurteilung.

Dozenten

David Drummond

Fractal Analytics

3 Kurse835 Lernende

von

Fractal Analytics

Warum entscheiden sich Menschen für Coursera für ihre Karriere?

Felipe M.

Lernender seit 2018

„Es ist eine großartige Erfahrung, in meinem eigenen Tempo zu lernen. Ich kann lernen, wenn ich Zeit und Nerven dazu habe.“

Jennifer J.

Lernender seit 2020

„Bei einem spannenden neuen Projekt konnte ich die neuen Kenntnisse und Kompetenzen aus den Kursen direkt bei der Arbeit anwenden.“

Larry W.

Lernender seit 2021

„Wenn mir Kurse zu Themen fehlen, die meine Universität nicht anbietet, ist Coursera mit die beste Alternative.“

Chaitanya A.

„Man lernt nicht nur, um bei der Arbeit besser zu werden. Es geht noch um viel mehr. Bei Coursera kann ich ohne Grenzen lernen.“

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Häufig gestellte Fragen

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.

This program is ideal for all AI professionals—data scientists, data engineers, software developers—who have 3 to 5 years of experience and are ready to take their skills to the next level. Whether you're building enterprise AI systems or shaping data strategies, this specialization will help you deepen your expertise, stay ahead of the curve, and lead with confidence in the age of generative AI.

A basic understanding of data systems, AI workflows, and governance concepts is recommended. This specialization is ideal for data professionals, engineers, architects, and product managers with experience in enterprise data or AI projects. No advanced technical expertise required—hands-on labs and guided projects will build key skills throughout the program.