AI+ NurseTM
This program equips nurses with the skills to leverage AI for enhanced patient monitoring, clinical decision support, and more efficient, data-driven nursing care.
- 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
Prerequisites
Basic Nursing Knowledge: Understanding of clinical practices and patient care.
Familiarity with Healthcare Technology: Experience with electronic health records and medical devices.
Introduction to Data Science: Understanding data analysis and interpretation in healthcare.
Basic AI and Machine Learning Concepts: Knowledge of algorithms and predictive modeling.
Critical Thinking and Problem Solving: Ability to make data-driven healthcare decisions.
Course Delivery Options
The AI+ Nurse™ self-paced course includes:
1. 8 hours of on-demand videos, an e-book, and podcasts.
2. Modular quizzes to help learners monitor their progress.
The course allows learners to study at their own pace. After completing the course, learners can take the certification exam online through a secure remote-proctored system.
Why This Certification Matters?
- AI in Patient Care: Learn how AI enhances patient monitoring, early warning systems, and proactive care delivery.
- Clinical Decision Support: Understand AI tools that assist nurses in medication management, triage, and treatment recommendations.
- Workflow Optimization: Discover how AI reduces administrative burdens and streamlines nursing workflows for efficiency.
- Ethical and Human-Centered Care: Explore responsible AI practices that preserve empathy, trust, and patient-centered values in nursing.
- Practical Simulations: Apply skills in real-world nursing scenarios through interactive, AI-powered case-based learning.
AI+ NurseTM
This program equips nurses with the skills to leverage AI for enhanced patient monitoring, clinical decision support, and more efficient, data-driven nursing care.
- 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
Prerequisites
Basic Nursing Knowledge: Understanding of clinical practices and patient care.
Familiarity with Healthcare Technology: Experience with electronic health records and medical devices.
Introduction to Data Science: Understanding data analysis and interpretation in healthcare.
Basic AI and Machine Learning Concepts: Knowledge of algorithms and predictive modeling.
Critical Thinking and Problem Solving: Ability to make data-driven healthcare decisions.
Course Delivery Options
The AI+ Nurse™ self-paced course includes:
1. 8 hours of on-demand videos, an e-book, and podcasts.
2. Modular quizzes to help learners monitor their progress.
The course allows learners to study at their own pace. After completing the course, learners can take the certification exam online through a secure remote-proctored system.
AI+ NurseTM
This program equips nurses with the skills to leverage AI for enhanced patient monitoring, clinical decision support, and more efficient, data-driven nursing care.
- 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
Prerequisites
Basic Nursing Knowledge: Understanding of clinical practices and patient care.
Familiarity with Healthcare Technology: Experience with electronic health records and medical devices.
Introduction to Data Science: Understanding data analysis and interpretation in healthcare.
Basic AI and Machine Learning Concepts: Knowledge of algorithms and predictive modeling.
Critical Thinking and Problem Solving: Ability to make data-driven healthcare decisions.
The AI+ Nurse™ self-paced course includes:
1. 8 hours of on-demand videos, an e-book, and podcasts.
2. Modular quizzes to help learners monitor their progress.
The course allows learners to study at their own pace. After completing the course, learners can take the certification exam online through a secure remote-proctored system.
Why This Certification Matters?
- AI in Patient Care: Learn how AI enhances patient monitoring, early warning systems, and proactive care delivery.
- Clinical Decision Support: Understand AI tools that assist nurses in medication management, triage, and treatment recommendations.
- Workflow Optimization: Discover how AI reduces administrative burdens and streamlines nursing workflows for efficiency.
- Ethical and Human-Centered Care: Explore responsible AI practices that preserve empathy, trust, and patient-centered values in nursing.
- Practical Simulations: Apply skills in real-world nursing scenarios through interactive, AI-powered case-based learning.
What You'll Learn?
1.1 What is AI for Nurses?
1.2 Where AI Shows Up in Nursing
1.3 Case Study: Improving Patient Safety and Nursing Efficiency with AI at Riverside Medical Center
1.4 Hands-on: Using Nurse AI for Clinical Data Visualization in Postoperative Nursing Care
2.1 Introduction to Natural Language Processing
2.2 Workflow Automation: Transforming Nursing Practice
2.3 Beginner’s Guide to Data Literacy in Nursing
2.4 Legal & Compliance Basics in Nursing AI Documentation
2.5 Case Study: Integrating AI and Workflow Automation at Massachusetts General Hospital (MGH)
2.6 Hands-On Exercise: Using the ChatGPT Registered Nurse Tool in Clinical Documentation and Patient Education
3.1 Understanding Predictive Models
3.2 Alert Fatigue and Trust
3.3 Simulation Activity: Responding to Real-Time Deterioration Alerts
3.4 Collaborating Across Teams
3.5 Bias in Predictions
3.6 Case Study
3.7 Hands-on Activity: Interpreting Predictive Alerts with ChatGPT
4.1 Introduction to Generative AI in Nursing
4.2 Large Language Models (LLMs) for Nurses
4.3 Creating Patient Education Materials with AI
4.4 Ensuring Safe and Ethical Use of AI
4.5 Case Study
4.6 Hands-On Activity: Exploring AI-Powered Differential Diagnosis with Symptoma
5.1 Bias, Fairness, and Inclusion
5.2 Informed Consent and Transparency
5.3 Nurse Advocacy and Professional Responsibilities
5.4 Creating an Ethics Checklist
5.5 Stakeholder Feedback Techniques
5.6 Legal and Regulatory Considerations
5.7 Psychological and Social Implications
5.8 Case Study: Addressing Racial Bias in Healthcare Algorithms (Optum Algorithm Case).
5.9 Hands-on: Uncovering Bias in Diabetes Risk Prediction: A Fairness Audit Using Aequitas
6.1 Understanding Performance Metrics
6.2 Vendor Red Flags
6.3 Nurse Role in Selection
6.4 Evaluation Templates and Checklists
6.5 Use Cases: AI in Clinical Decision-Making
6.6 Case Study: Using AI to Enhance Real-Time Clinical Decision-Making at UAB Medicine with MIC Sickbay
6.7 Hands-on: Evaluating AI Diagnostic Model Performance Using Confusion Matrix Metrics
7.1 Building Buy-In: Promoting AI as an Ally, Not a Competitor
7.2 Change Management Essentials
7.3 Creating an AI Playbook: A Comprehensive Roadmap for Sustainable Success
7.4 Monitoring Quality Improvement: Leveraging AI Metrics for Continuous Enhancement
7.5 Error Reporting and Safety Protocols: Ensuring Safe and Reliable AI Integration
7.6 Hands-On Activity: Calculating Clinical Risk Scores and Visualization with ChatGPT
1. Capstone Project – Designing a Personal AI-in-Nursing Impact Plan
Job Roles & Industry Outlook
What You'll Learn?
1.1 What is AI for Nurses?
1.2 Where AI Shows Up in Nursing
1.3 Case Study: Improving Patient Safety and Nursing Efficiency with AI at Riverside Medical Center
1.4 Hands-on: Using Nurse AI for Clinical Data Visualization in Postoperative Nursing Care
2.1 Introduction to Natural Language Processing
2.2 Workflow Automation: Transforming Nursing Practice
2.3 Beginner’s Guide to Data Literacy in Nursing
2.4 Legal & Compliance Basics in Nursing AI Documentation
2.5 Case Study: Integrating AI and Workflow Automation at Massachusetts General Hospital (MGH)
2.6 Hands-On Exercise: Using the ChatGPT Registered Nurse Tool in Clinical Documentation and Patient Education
3.1 Understanding Predictive Models
3.2 Alert Fatigue and Trust
3.3 Simulation Activity: Responding to Real-Time Deterioration Alerts
3.4 Collaborating Across Teams
3.5 Bias in Predictions
3.6 Case Study
3.7 Hands-on Activity: Interpreting Predictive Alerts with ChatGPT
4.1 Introduction to Generative AI in Nursing
4.2 Large Language Models (LLMs) for Nurses
4.3 Creating Patient Education Materials with AI
4.4 Ensuring Safe and Ethical Use of AI
4.5 Case Study
4.6 Hands-On Activity: Exploring AI-Powered Differential Diagnosis with Symptoma
5.1 Bias, Fairness, and Inclusion
5.2 Informed Consent and Transparency
5.3 Nurse Advocacy and Professional Responsibilities
5.4 Creating an Ethics Checklist
5.5 Stakeholder Feedback Techniques
5.6 Legal and Regulatory Considerations
5.7 Psychological and Social Implications
5.8 Case Study: Addressing Racial Bias in Healthcare Algorithms (Optum Algorithm Case).
5.9 Hands-on: Uncovering Bias in Diabetes Risk Prediction: A Fairness Audit Using Aequitas
6.1 Understanding Performance Metrics
6.2 Vendor Red Flags
6.3 Nurse Role in Selection
6.4 Evaluation Templates and Checklists
6.5 Use Cases: AI in Clinical Decision-Making
6.6 Case Study: Using AI to Enhance Real-Time Clinical Decision-Making at UAB Medicine with MIC Sickbay
6.7 Hands-on: Evaluating AI Diagnostic Model Performance Using Confusion Matrix Metrics
7.1 Building Buy-In: Promoting AI as an Ally, Not a Competitor
7.2 Change Management Essentials
7.3 Creating an AI Playbook: A Comprehensive Roadmap for Sustainable Success
7.4 Monitoring Quality Improvement: Leveraging AI Metrics for Continuous Enhancement
7.5 Error Reporting and Safety Protocols: Ensuring Safe and Reliable AI Integration
7.6 Hands-On Activity: Calculating Clinical Risk Scores and Visualization with ChatGPT
1. Capstone Project – Designing a Personal AI-in-Nursing Impact Plan
Job Roles & Industry Outlook
Chief Nursing AI Officer (CNAIO)
Direct AI adoption in nursing, driving innovation, workforce empowerment, and patient-centered digital transformation.
AI Nursing Practice Consultant
Guide hospitals and care facilities in AI adoption to improve patient monitoring, workflow efficiency, and quality of care.
Clinical AI Nursing Coordinator
Manage AI-powered nursing systems to streamline daily tasks, minimize errors, and improve patient safety.
AI Patient Care Data Specialist
Utilize AI models to interpret nursing and patient care data, predict patient needs, and support evidence-based nursing practices.
Healthcare Operations AI Manager
Lead AI integration in nursing operations, optimizing resource allocation and enhancing patient-care delivery systems.
Chief Nursing AI Officer (CNAIO)
Direct AI adoption in nursing, driving innovation, workforce empowerment, and patient-centered digital transformation.
AI Nursing Practice Consultant
Guide hospitals and care facilities in AI adoption to improve patient monitoring, workflow efficiency, and quality of care.
Clinical AI Nursing Coordinator
Manage AI-powered nursing systems to streamline daily tasks, minimize errors, and improve patient safety.
AI Patient Care Data Specialist
Utilize AI models to interpret nursing and patient care data, predict patient needs, and support evidence-based nursing practices.
Healthcare Operations AI Manager
Lead AI integration in nursing operations, optimizing resource allocation and enhancing patient-care delivery systems.
Skills You’ll Gain
Skills You’ll Gain
Skills You’ll Gain
Tools You’ll Master
Tools You’ll Master
Exam Details
Exam Details
Exam Details
Duration
Passing Score
Format
Delivery Method
(flexible scheduling)
Duration
Passing Score
Format
Delivery Method
(flexible scheduling)
Duration
Passing Score
Format
Delivery Method
Exam Blueprint
What's Included
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
(One-Year Subscription + All Updates)
Exam Blueprint
What’s Included
(One-Year Subscription + All Updates)
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Exam Blueprint
What’s Included
(One-Year Subscription + All Updates)
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone