How long does it take to complete this course?

<text variant="body1">The course consists of two comprehensive modules with case studies and exercises. Most students complete it in 3-4 weeks with 3-5 hours of study per week.

What background knowledge is necessary?

<text variant="body1">Basic familiarity with data concepts and some exposure to AI fundamentals will help you get the most from this course, but it's designed to be accessible to professionals from varied backgrounds.

What is the learning experience of this course?

<text variant="body1">The course combines expert instruction, case studies, hands-on exercises, and discussions to provide both theoretical understanding and practical implementation skills for data frameworks in AI context.

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.

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.

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.

Advanced Data Techniques for Enterprise AI Systems

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Advanced Data Techniques for Enterprise AI Systems

This course is part of Modern Data Strategy for Enterprise Generative AI Specialization

Instructors: David Drummond

Included with Coursera Plus

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6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

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

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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Build your subject-matter expertise

This course is part of the Modern Data Strategy for Enterprise Generative AI Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 6 modules in this course

As Generative AI transforms industries, data professionals must evolve too. This intermediate-level course empowers you to master the modern data management techniques essential for building scalable, ethical, and intelligent AI systems.

Understand the pillars of modern data strategy—management, frameworks, and governance. Learn how to secure data using encryption, access control, and ISO standards.

What's included

4 videos2 readings2 assignments1 plugin

4 videosTotal 25 minutes

Introduction to Data Management Techniques4 minutes
Data Management and the Pillars of Modern Data Strategy7 minutes
The Pillars of Data Management6 minutes
Security Fundamentals in Data Management7 minutes

2 readingsTotal 20 minutes

Course Syllabus10 minutes
Disclaimer10 minutes

2 assignmentsTotal 60 minutes

Modern Data Strategy Fundamentals30 minutes
Modern Data Strategy Fundamentals30 minutes

1 pluginTotal 30 minutes

Analyzing the Equifax Breach: Data Governance in Crisis30 minutes

Master interoperability across clouds and platforms using Docker, Kubernetes, APIs, and the SECURE framework to build scalable, resilient AI systems.

What's included

5 videos1 reading2 assignments1 ungraded lab

5 videosTotal 32 minutes

Introducing Cross-platform Compatibility and Interoperability 5 minutes
Benefits of Cross-platform Compatibility5 minutes
Strategies for Achieving Cross-Platform Compatibility 6 minutes
Implementing Cross-Platform Compatibility5 minutes
Demo: Cross-Platform Compatibility 10 minutes

1 readingTotal 10 minutes

Solving Integration Challenges: Case Studies10 minutes

2 assignmentsTotal 60 minutes

Cross-platform Compatibility and Interoperability30 minutes
Cross-platform Compatibility and Interoperability30 minutes

1 ungraded labTotal 60 minutes

Cross-platform Compatibility: MCP60 minutes

Organize and retrieve data efficiently using metadata tagging. Learn how tagging powers Retrieval-Augmented Generation (RAG) and enhances AI accuracy.

What's included

6 videos2 assignments1 ungraded lab1 plugin

6 videosTotal 34 minutes

Introduction to Tagging4 minutes
Understanding Tagging Systems 5 minutes
Tagging for Enhanced Retrieval 4 minutes
Metadata-enhanced Vector Search3 minutes
Demo: Data Classification and Tagging10 minutes
Challenges and Solutions in Integration 6 minutes

2 assignmentsTotal 60 minutes

Data Classification and Tagging30 minutes
Data Classification and Tagging30 minutes

1 ungraded labTotal 60 minutes

Tagging Systems: Document Classification System60 minutes

1 pluginTotal 30 minutes

Solving the Metadata Synchronization Challenge: From Theory to Implementation30 minutes

Explore vector databases for semantic and multimodal search. Learn about indexing strategies, ANN algorithms, and hardware acceleration for real-time AI.

What's included

8 videos4 readings2 assignments1 ungraded lab1 plugin

8 videosTotal 44 minutes

Introduction to Vector Stores6 minutes
Metadata-Enhanced Vector Search 3 minutes
Access and Control Considerations4 minutes
Efficacy of Vector Embedding Engine 4 minutes
Efficacy and Cost of Vector Store Search 5 minutes
Speed of Vector Store Search 6 minutes
Creating Indices over Vectors 6 minutes
Demo: Integrating Vector Stores in Your Applications6 minutes

4 readingsTotal 40 minutes

The Mathematics of Vector Databases10 minutes
Securing Your Vector Database10 minutes
Vector Database Best Practices10 minutes
Speedy Vector Databases10 minutes

2 assignmentsTotal 60 minutes

Vector Data Stores, Embeddings, and Indices30 minutes
Vector Data Stores, Embeddings, and Indices30 minutes

1 ungraded labTotal 60 minutes

Vector Data Stores60 minutes

1 pluginTotal 15 minutes

The Vector Database Revolution: Transforming Unstructured Data Retrieval15 minutes

Dive into data lakes, warehouses, and lakehouses. Use tools like DuckLake and Databricks to unify structured and unstructured data for Gen AI.

What's included

8 videos2 readings2 assignments1 ungraded lab1 plugin

8 videosTotal 43 minutes

Why Unified Data Management Matters 3 minutes
Data Warehouses, Lakes, and Lakehouses5 minutes
Modern Lakehouse Architectures: Iceberg, Delta, and DuckLake5 minutes
Understanding and Accessing Tabular Data 5 minutes
Understanding and Accessing Tabular Data Part II5 minutes
Tabular data, Vector Databases, and Data Management3 minutes
DuckLake: Simplifying Lakehouse with SQL Catalogs3 minutes
Demo: DuckLake for Gen AI Data Pipelines11 minutes

2 readingsTotal 30 minutes

Benefits of Data Warehouses, Lakes, and Lakehouses20 minutes
Leveraging Tabular Data Case Studies10 minutes

2 assignmentsTotal 60 minutes

Modern Data Architectures30 minutes
Modern Data Architectures30 minutes

1 ungraded labTotal 60 minutes

DuckLake for Modern Lakehouse Architecture60 minutes

1 pluginTotal 30 minutes

Enterprise AI Architecture in Action: Deconstructing Morgan Stanley's RAG Implementation30 minutes

Apply governance frameworks like DAMA-DMBOK and EDM. Implement Explainable AI, Zero Trust Architecture, and Data Loss Prevention for secure, ethical AI systems.

What's included

6 videos1 reading2 assignments1 plugin

6 videosTotal 34 minutes

Modern Day Data Management Techniques5 minutes
Frameworks of Modern Data Management Techniques3 minutes
DuckLake as a Unified Catalog Solution4 minutes
Data Management Frameworks and Explainable AI (XAI)5 minutes
Securing Data in Advanced Frameworks6 minutes
Tying It All Back9 minutes

1 readingTotal 10 minutes

Acknowledgements10 minutes

2 assignmentsTotal 60 minutes

Data Frameworks and XAI30 minutes
Data Frameworks and XAI30 minutes

1 pluginTotal 15 minutes

Navigating the AI Security Frontier: Threats, Patterns, and Strategic Balance15 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

David Drummond

Fractal Analytics

3 Courses813 learners

Fractal Analytics Academy

Fractal Analytics

23 Courses101,758 learners

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Fractal Analytics

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Frequently asked questions

This course provides foundational knowledge about data frameworks that support generative AI applications. It's important because even the most advanced AI models will produce unreliable results without properly structured, high-quality data foundations.

This course is designed for data professionals, AI leaders, and anyone responsible for implementing or overseeing generative AI initiatives who wants to understand how data strategy impacts AI performance.

You'll be able to design appropriate data frameworks for AI applications, implement effective data taxonomies, apply governance principles to AI data, and ensure your organization's data strategy supports reliable generative AI development.

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.