The explosion of generative AI has created unprecedented data governance challenges that traditional approaches can't handle. This course equips you with the specialized skills to govern GenAI data safely while maintaining operational agility. This Short Course was created to help machine learning and AI professionals accomplish secure, compliant GenAI data governance at enterprise scale. By completing this course, you'll be able to design sophisticated role-based access control systems, assess your organization's governance maturity using industry frameworks like DAMA-DMBOK, and create comprehensive stewardship programs that balance innovation with security. These are the foundational skills that separate GenAI operations that scale safely from those that create compliance nightmares. By the end of this course, you will be able to: - Analyze data access patterns across user cohorts to recommend precise role-based controls - Evaluate governance maturity using established frameworks to identify strategic improvement opportunities - Create data stewardship programs with clear ownership, quality standards, and governance procedures This course is unique because it bridges the gap between cutting-edge GenAI capabilities and enterprise-grade governance, focusing specifically on the intersection of AI operations and data security. To be successful in this project, you should have experience with data analytics, understanding of enterprise risk concepts, and familiarity with AI/ML environments.
CERTIFICATEKatılım Sertifikası
FORMAT100% Online
DURATIONSelf-paced
What you'll learn
Data Governance
Role-Based Access Control (RBAC)
Risking
Responsible AI
Governance
Data Management
Generative AI
Security Controls
AI Security
Data Quality
Data Access
Identity and Access Management
Details
ProviderCoursera
TypeCourse
CategoryData Science & AI
LanguageEnglish
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