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.
Applied Learning Project
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.
