We may earn an affiliate commission when you visit our partners.
David Drummond
and
Fractal Analytics Academy
Led by renowned data scientist David Drummond, this course blends expert instruction with hands-on practice to help you implement cutting-edge tools like vector databases, metadata tagging, and cross-platform architectures. You’ll also explore governance frameworks and Explainable AI (XAI) to ensure transparency and trust in your AI systems.
Register for this course and see more details by visiting:
OpenCourser.com/course/c9xjgv/advanced
Two deals to help you save
Save money when you learn. Here are two deals and offers that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until July 14
Coursera Plus Annual
Work toward what's next for your career with access to 10,000+ programs. Discover emerging skills and save.
Up to
40%
off
Get offer
Valid until August 30
Google AI App Builder
Learn how to use Gemini API and API Studio with a three-course series from Google DeepMind
Take
100%
off
Get offer
What's inside
Syllabus
Foundation and Strategy with Security
Understand the pillars of modern data strategy—management, frameworks, and governance. Learn how to secure data using encryption, access control, and ISO standards.
Read more
Syllabus
Foundation and Strategy with Security
Understand the pillars of modern data strategy—management, frameworks, and governance. Learn how to secure data using encryption, access control, and ISO standards.
Read more
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
Save
Save
Activities
Coming soon
We're preparing activities for
Advanced Data Techniques for Enterprise AI Systems.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Advanced Data Techniques for Enterprise AI Systems will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/c9xjgv/advanced
Reading list
We haven't picked any books for this reading list yet.
Explores the fundamental trade-offs and concepts behind designing modern data systems, covering various technologies and distributed systems principles. It is highly relevant for understanding contemporary data management challenges and must-read for engineers and architects.
Save
Provides a detailed look inside the implementation of database systems, covering topics like storage engines, indexing, and concurrency control. It is excellent for deepening understanding of how databases function at a low level and is valuable for database professionals.
This practical guide focuses on writing effective SQL queries for data retrieval and manipulation. It is ideal for anyone needing to work directly with data in relational databases and provides hands-on examples to solidify understanding of this fundamental data management skill.
Considered a classic in data warehousing, this book provides a comprehensive guide to dimensional modeling techniques. It is essential for those working with data warehouses and business intelligence systems, offering practical methods for designing understandable and performant databases.
Save
Provides a practical guide to establishing and implementing data governance programs. It is crucial for understanding the organizational and process aspects of managing data effectively and valuable resource for data leaders and practitioners.
Save
This concise guide introduces the concepts and types of NoSQL databases. It is valuable for understanding alternatives to traditional relational databases and is relevant for contemporary data management architectures.
Save
This guide provides a comprehensive framework for data management functions, principles, and best practices. It is essential for professionals seeking to understand the full scope of data management and valuable reference for establishing and improving data management programs within organizations.
Offers a detailed coverage of database fundamentals, including data models, database design, and database technologies. It is well-suited for students and professionals looking to gain a solid understanding of the core concepts in data management and is often used as a primary textbook.
Delves into the essential principles and techniques of data modeling, a critical aspect of data management. It is valuable for understanding how to design effective database structures and useful reference for data professionals.
Serves as a gentle introduction to data management, covering the fundamentals of data collection, storage, organization, and analysis. It is appropriate for beginners and those seeking a broad understanding of data management.
This practical guide focuses on data management in the cloud, covering topics such as cloud data storage, data migration, and data security. It is recommended for IT professionals and architects responsible for designing and implementing cloud data solutions.
This expert-level book provides insights into data governance, metadata management, and data integration, covering topics such as data quality, data security, and data sharing. It is recommended for data management professionals and leaders seeking to enhance their skills and understanding.
Focuses on data management for analytics, covering topics such as data engineering with Hadoop and Spark, and NoSQL database management. It is suitable for data engineers and analysts seeking to leverage big data technologies for data-driven decision-making.
Provides a business-oriented introduction to data science, covering topics such as data mining, data visualization, and predictive analytics. It is recommended for business professionals and managers seeking to understand and leverage data for decision-making.
Provides a framework for assessing and improving data management maturity, covering topics such as data governance, data quality, and data architecture. It is suitable for data management professionals and leaders seeking to enhance their organization's data management capabilities.
This seminal book by renowned data warehousing expert W.H. Inmon provides a comprehensive guide to data integration and data warehouse design. It is recommended for data architects and data engineers involved in the design and implementation of data warehouses.
This acclaimed book provides a deep dive into the design and architecture of data-intensive applications, covering topics such as data modeling, data storage, and data processing. It is recommended for software architects, data engineers, and anyone seeking to build scalable and efficient data-driven applications.
A widely-used textbook in database courses, this book offers a thorough introduction to database systems, including relational models, SQL, and transaction management. It's valuable for both broad understanding and deepening knowledge, providing a solid theoretical and practical basis for data management.
Save
Introduces the concept of Data Mesh as a decentralized approach to data management in complex environments. It is highly relevant for understanding contemporary data architecture patterns and is valuable for professionals dealing with distributed data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/c9xjgv/advanced
Share
Similar courses
Similar courses are unavailable at this time. Please try again later.
Effort
3 weeks of study
Level
Intermediate
Via
Coursera
Institution
Fractal Analytics
Instructors
David Drummond
Fractal Analytics Academy
Session
November 3, 2025
- December 22, 2025
Language
English
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2025 OpenCourser