AI in Patient Care:
Learn how AI enhances patient monitoring, early warning systems, and proactive care delivery.
← Back to catalogue
AI CERTS® certification
AI+ Nurse Practitioner™
Formerly known as AI+ Nurse™ Blending Human Touch with AI Intelligence
Enquire about this certificationCourse code: AP 1102
Course overview
Review the course before deciding whether it is suitable.
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
- 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
- Exam format
- 50 questions, 70% passing, 90 minutes, online proctored exam
- Prerequisites
- Basic nursing knowledge, Familiarity with healthcare technology, Critical thinking, Foundational AI and ML concepts, Problem solving skills
Course focus
Why this certification may be relevant.
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.
Who it may suit
Check the intended audience against your experience and goals.
- Registered Nurses (RNs): Professionals seeking to integrate AI into daily patient care and clinical decision-making.
- Nursing Students: Learners aiming to build future-ready skills in AI-driven healthcare practices.
- Healthcare Administrators: Individuals looking to optimize nursing workflows and enhance patient care outcomes.
- Clinical Informatics Specialists: Experts interested in applying AI to electronic health records and patient data analysis.
- Nurse Educators & Trainers: Professionals preparing the next generation of nurses with AI-powered healthcare knowledge.
Course content
Modules supplied by AI CERTs.
Open each module to review the stated topics.
01Module 1: AI for Nurses
- 1.1 Understanding AI Basics in a Nursing Context
- 1.2 Where AI Shows Up in Nursing
- 1.3 AI Risks Nurses Must Recognize
- 1.4 AI as a Nursing Support Tool
02Module 2: AI for Documentation, Workflow, and Data Literacy
- 2.1 AI in Nursing Documentation
- 2.2 Workflow Automation in Nursing Practice
- 2.3 Beginner’s Guide to Data Literacy in Nursing
- 2.4 Data Integrity and Documentation Safety
- 2.5 Communication and Translation Support
- 2.6 Real-World Case Studies: Documentation AI in Practice
03Module 3: Predictive AI and Patient Safety
- 3.1 Understanding Predictive AI in Healthcare
- 3.2 Evaluating Alerts and Model Performance
- 3.3 Human-in-the-Loop Clinical Decision-Making
- 3.4 Interdisciplinary Response and Handoff Support
- 3.5 Bias and Equity in Predictive Models
- 3.6 Real-World Case Studies: Predictive AI in Practice
04Module 4: Generative AI and Nursing Education
- 4.1 Introduction to Generative AI in Nursing
- 4.2 Safe Use of Generative AI
- 4.3 Patient Education and Communication Materials
- 4.4 Multilingual and Accessible Communication
- 4.5 Clinical Use Boundaries for Generative AI
- 4.6 Real-World Case Studies: Generative AI in Practice
05Module 5: Ethics, Safety, and Advocacy in AI Integration
- 5.1 Bias, Fairness, and Inclusion
- 5.2 Informed Consent and Transparency
- 5.3 Privacy, Security, and Confidentiality
- 5.4 Regulatory Literacy for Nurses
- 5.5 Professional Responsibility and Accountability
06Module 6: Evaluating and Selecting AI Tools
- 6.1 Understanding Performance Metrics
- 6.2 Predictive Tools vs. Generative Tools
- 6.3 Vendor Red Flags
- 6.4 The Nurse Practitioner’s Role in Tool Selection
07Module 7: Implementing AI and Leading Change on the Unit
- 7.1 Building Buy-In
- 7.2 Change Management Essentials
- 7.3 Creating an AI Playbook: A Comprehensive Roadmap for Sustainable Success
- 7.4 Monitoring Quality Improvement
- 7.5 Error Reporting and Safety Protocols
- 7.6 Real-World Case Studies in AI Implementation and Change Leadership
08Module 8: Capstone Project: Designing a Personal AI in Nursing Impact Plan
- 8.1 Capstone Project – Designing a Personal AI-in-Nursing Impact Plan
09Optional Module: AI Agents for AI+ Nurses
- 1. What Are AI Agents?
- 2. How Does an AI Agent Work in Healthcare?
- 3. Core Characteristics of AI Agents
- 4. Importance of AI Agents (General + Nursing)
- 5. Significance of AI Agents in Nursing
- 6. Types of AI Agents?
- 7. Applications and Trends in Nursing
- 8. Case Study – AI Agents for Nursing Workflow & Sepsis
Tools referenced by AI CERTs
Platforms and tools included in the course information.
Python
Scikit-learn
Keras
Jupyter Notebooks
Matplotlib
Power BIThis course information is supplied through the AI CERTs catalogue. Kiwi Fern Education will confirm current availability, delivery arrangements, inclusions and fees before enrolment. The programme is not presented as a New Zealand Qualifications Authority qualification.
Speak with our team
Would you like to discuss this certification?
Tell us whether you are enquiring for yourself or a team and what capability you want to build. We will confirm the next steps before you commit.