AI is already part of nursing practice. Risk scores, deterioration alerts, prioritized patient lists, and AI‑assisted documentation tools shape what information reaches nurses every shift often without clear explanation or preparation. This Specialization helps nurses understand what these tools are, how they work, and how to use them responsibly in patient care.
Across three courses, you'll move from recognition to evaluation to application. You'll learn how AI systems are structured, how AI learns from data, where AI can fall short, and how bias enters tools in predictable ways. You'll practice applying that understanding through guided case studies drawn from realistic clinical scenarios in acute care, outpatient, and telehealth settings, and through AI-enabled discussion activities that ask you to bring a tool from your own workflow into the learning.
In support of improving patient care, Duke University Health System Clinical Education and Professional Development is accredited by the American Nurses Credentialing Center (ANCC), the Accreditation Council for Pharmacy Education (ACPE), and the Accreditation Council for Continuing Medical Education (ACCME), to provide continuing education for the health care team.
Upon completing the entire Specialization and passing the final assessment, Duke University Health System Department of Clinical Education and Professional Development designates this activity for up to 9 credit hours for nurses.
Übungsprojekt
In each course, learners apply concepts through a Dialogue activity—a guided conversation with an AI learning coach that connects course ideas to real clinical workflows. In Course 1, learners identify and describe an AI tool from their practice. In Course 2, they evaluate a tool using the course’s framework for interpreting AI outputs. In Course 3, they reflect on a real clinical moment where an AI output influenced their decision-making. Each Dialogue adapts to the learner’s care setting, helping translate course concepts into practical clinical judgment.
