Artificial Intelligence and Machine Learning Courses

AI+ Nurse - Self-paced

  • Length 365 days access
  • Price  NZD 500 exc GST
  • Inclusions Online exam
Course overview
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Why study this course

The AI + Nurse course equips healthcare professionals with the essential skills to integrate artificial intelligence into nursing practice. By focusing on AI technologies and their application in clinical settings, the certification prepares nurses to enhance patient care, optimise workflows, and improve decision-making. The program covers AI fundamentals, data analytics, machine learning, and ethical considerations, enabling nurses to confidently leverage AI tools to advance patient outcomes. With the growing role of technology in healthcare, the AI + Nurse certification provides a critical edge for nurses seeking to stay at the forefront of the evolving healthcare landscape.

Exam and certification

This course prepares students for the corresponding certification. The exam/assessment is completed online and provided as part of the course content.

The exam is:

  • 90 minutes

  • 50 multiple choice / multiple response questions

  • Pass mark is 35 out of 50 (i.e. 70%)

  • Online via AI Proctoring platform

Course availability update

Lumify Work is actively monitoring demand for this course. It is currently offered as a self-paced eLearning course and includes the certification exam. If you're interested in joining a waitlist for future instructor-led training — or exploring options for a tailored delivery for your organisation — please contact us. Your feedback helps shape our activation roadmap.

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What you’ll learn

This course is designed to teach participants how to:

  • Leverage AI for enhanced patient outcomes

  • Make informed clinical and operational choices

  • Integrate AI into daily healthcare practice


AI CERTs Authorized Training Partner Platinum logo Oct 2025

AI CERTs at Lumify Work

AI CERTs® stands at the forefront of AI and blockchain certification, offering world-class programs that prepare individuals to lead in these rapidly growing fields. AI CERTs courses and certifications are vendor agnostic and designed to bridge the gap between theoretical knowledge and practical application, ensuring learners are equipped to make an immediate impact in their careers.
Lumify Work is a Platinum Authorized Training Partner for AI CERTs in Australia, New Zealand, and the Philippines.


Who is the course for?

  • Registered Nurses

  • Nurse Practitioners

  • Healthcare Administrators

  • Nursing Educators

  • Nursing Students


Course subjects

Module 1: What is AI for Nurses?

  • What is AI for Nurses?

  • Where AI Shows Up in Nursing

  • Case Study: Improving Patient Safety and Nursing Efficiency with AI at Riverside Medical Center

  • Hands-on: Using Nurse AI for Clinical Data Visualisation in Postoperative Nursing Care

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

  • Introduction to Natural Language Processing

  • Workflow Automation: Transforming Nursing Practice

  • Beginner’s Guide to Data Literacy in Nursing

  • Legal & Compliance Basics in Nursing AI Documentation

  • Case Study: Integrating AI and Workflow Automation at Massachusetts General Hospital (MGH)

  • Hands-on Exercise: Using the ChatGPT Registered Nurse Tool in Clinical Documentation and Patient Education

Module 3: Predictive AI and Patient Safety

  • Understanding Predictive Models

  • Alert Fatigue and Trust

  • Simulation Activity: Responding to Real-Time Deterioration Alerts

  • Collaborating Across Teams

  • Bias in Predictions

  • Case Study

  • Hands-on Activity: Interpreting Predictive Alerts with ChatGPT

Module 4: Generative AI in Nursing

  • Introduction to Generative AI in Nursing

  • Large Language Models (LLMs) for Nurses

  • Creating Patient Education Materials with AI

  • Ensuring Safe and Ethical Use of AI

  • Case Study

  • Hands-on Activity: Exploring AI-Powered Differential Diagnosis with Symptoma

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

  • Bias, Fairness, and Inclusion

  • Informed Consent and Transparency

  • Nurse Advocacy and Professional Responsibilities

  • Creating an Ethics Checklist

  • Stakeholder Feedback Techniques

  • Legal and Regulatory Considerations

  • Psychological and Social Implications

  • Case Study: Addressing Racial Bias in Healthcare Algorithms (Optum Algorithm Case)

  • Hands-on: Uncovering Bias in Diabetes Risk Prediction — A Fairness Audit Using Aequitas

Module 6: Evaluating and Selecting AI Tools

  • Understanding Performance Metrics

  • Vendor Red Flags

  • Nurse Role in Selection

  • Evaluation Templates and Checklists

  • Use Cases: AI in Clinical Decision-Making

  • Case Study: Using AI to Enhance Real-Time Clinical Decision-Making at UAB Medicine with MIC Sickbay

  • Hands-on: Evaluating AI Diagnostic Model Performance Using Confusion Matrix Metrics

Module 7: Implementing AI and Leading Change on the Unit

  • Building Buy-In: Promoting AI as an Ally, Not a Competitor

  • Change Management Essentials

  • Creating an AI Playbook: A Comprehensive Roadmap for Sustainable Success

  • Monitoring Quality Improvement: Leveraging AI Metrics for Continuous Enhancement

  • Error Reporting and Safety Protocols: Ensuring Safe and Reliable AI Integration

  • Hands-on Activity: Calculating Clinical Risk Scores and Visualisation with ChatGPT


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


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.


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