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AI+ Nurse Practitioner™

AI+ Nurse Practitioner™
  • Patient-Centric AI Care: Designed for nurses to leverage AI for enhanced patient outcomes
  • Data-Driven Decisions: Provides practical insights for informed clinical and operational choices
  • Comprehensive AI Understanding: Covers AI fundamentals to real-world healthcare applications
  • Clinical Excellence with AI: Empowers nurses to confidently integrate AI into daily healthcare practice
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Certificate Code

AP 1102

Exam Format

AI-Driven Remote Exam Proctoring

Course Overview

Important details and certification information

Instructor-led OR Self-paced course + Official exam + Digital badge
Instructor-Led: 3 Days (live or virtual)
Basic nursing knowledge, Familiarity with healthcare technology, Critical thinking, Foundational AI and ML concepts, Problem solving skills
50 questions, 70% passing, 90 minutes, online proctored exam

Certification Modules

  1. 1.1 Understanding AI Basics in a Nursing Context
  2. 1.2 Where AI Shows Up in Nursing
  3. 1.3 AI Risks Nurses Must Recognize
  4. 1.4 AI as a Nursing Support Tool

  1. 2.1 AI in Nursing Documentation
  2. 2.2 Workflow Automation in Nursing Practice
  3. 2.3 Beginner’s Guide to Data Literacy in Nursing
  4. 2.4 Data Integrity and Documentation Safety
  5. 2.5 Communication and Translation Support
  6. 2.6 Real-World Case Studies: Documentation AI in Practice

  1. 3.1 Understanding Predictive AI in Healthcare
  2. 3.2 Evaluating Alerts and Model Performance
  3. 3.3 Human-in-the-Loop Clinical Decision-Making
  4. 3.4 Interdisciplinary Response and Handoff Support
  5. 3.5 Bias and Equity in Predictive Models
  6. 3.6 Real-World Case Studies: Predictive AI in Practice
  7. 3.7 Hands-on Activity: Interpreting Predictive Alerts with ChatGPT

  1. 4.1 Introduction to Generative AI in Nursing
  2. 4.2 Safe Use of Generative AI
  3. 4.3 Patient Education and Communication Materials
  4. 4.4 Multilingual and Accessible Communication
  5. 4.5 Clinical Use Boundaries for Generative AI
  6. 4.6 Real-World Case Studies: Generative AI in Practice

  1. 5.1 Bias, Fairness, and Inclusion
  2. 5.2 Informed Consent and Transparency
  3. 5.3 Privacy, Security, and Confidentiality
  4. 5.4 Regulatory Literacy for Nurses
  5. 5.5 Professional Responsibility and Accountability

  1. 6.1 Understanding Performance Metrics
  2. 6.2 Predictive Tools vs. Generative Tools
  3. 6.3 Vendor Red Flags
  4. 6.4 The Nurse Practitioner’s Role in Tool Selection

  1. 7.1 Building Buy-In
  2. 7.2 Change Management Essentials
  3. 7.3 Creating an AI Playbook: A Comprehensive Roadmap for Sustainable Success
  4. 7.4 Monitoring Quality Improvement
  5. 7.5 Error Reporting and Safety Protocols
  6. 7.6 Real-World Case Studies in AI Implementation and Change Leadership

  1. 1. Capstone Project – Designing a Personal AI-in-Nursing Impact Plan

  1. 1. What Are AI Agents?
  2. 2. How Does an AI Agent Work in Healthcare?
  3. 3. Core Characteristics of AI Agents
  4. 4. Importance of AI Agents (General + Nursing)
  5. 5. Significance of AI Agents in Nursing
  6. 6. Types of AI Agents?7. Applications and Trends in Nursing
  7. 8. Case Study – AI Agents for Nursing Workflow & Sepsis
  8. 9. Hands-On Lab

AI Tools Covered

Python
Scikit-learn
Keras
Jupyter Notebooks
Matplotlib
Power BI
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