AI+ Nurse Practitioner™

Formerly known as AI+ Nurse™<br> <br>Blending Human Touch with AI Intelligence

Certificate Code: AP 1102

About This Course

  • 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

Certificate Overview

Included

Instructor-led OR Self-paced course + Official exam + Digital badge

Duration

  • Instructor-Led: 1 day (live or virtual)
  • Self-Paced: 8 hours of content

Prerequisites

Basic nursing knowledge, Familiarity with healthcare technology, Critical thinking, Foundational AI and ML concepts, Problem solving skills

Exam Format

50 questions, 70% passing, 90 minutes, online proctored exam

Course Modules

1

Module 1: AI for Nurses

  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
2

Module 2: AI for Documentation, Workflow, and Data Literacy

  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
3

Module 3: Predictive AI and Patient Safety

  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
4

Module 4: Generative AI and Nursing Education

  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
5

Module 5: Ethics, Safety, and Advocacy in AI Integration

  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
6

Module 6: Evaluating and Selecting AI Tools

  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
7

Module 7: Implementing AI and Leading Change on the Unit

  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
8

Module 8: Capstone Project: Designing a Personal AI in Nursing Impact Plan

  1. 8.1 Capstone Project – Designing a Personal AI-in-Nursing Impact Plan
9

Optional Module: AI Agents for AI+ Nurses

  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. 7. Applications and Trends in Nursing
  8. 8. Case Study – AI Agents for Nursing Workflow & Sepsis
  9. 9. Hands-On Lab

AI Tools You'll Learn

Python

Python

Scikit-learn

Scikit-learn

Keras

Keras

Jupyter Notebooks

Jupyter Notebooks

Matplotlib

Matplotlib

Power BI

Power BI