You’ll see what’s included, what you’ll be able to do by the end, and exactly how to earn completion credit.

Introduction

You’ll get plain-language definitions of AI, generative AI, and LLMs so you can explain them confidently to colleagues and students.

Foundations

Foundations (Definitions & Context)

You’ll understand where AI is today, why it matters to nursing, what Nurses (No CE) are saying about it, and what common model names actually mean.

AI Landscape

Landscape & Rationale

You’ll grasp the basics—tokens, temperature, training, and deep learning—so you know what these tools can (and can’t) do.

How LLMs Work

How it Works

You’ll learn how to spot hallucinations quickly and apply simple checks to keep outputs accurate and safe.

Hallucinations

Risks & Limitations

You’ll practice practical prompting techniques you can reuse at work to get clearer, more reliable results.

Prompt Engineering Overview

Prompt Engineering

You’ll know what typical institutional policies require, HIPAA implications, and where to find privacy controls in popular tools.

Policies

Policy & Privacy

You’ll see how AI can enhance teaching and simulation—virtual patients, VR, and real-time feedback—to boost engagement and learning.

AI in Education

AI in Nursing Education

You’ll explore bedside and clinic use cases—CDS, RPM, workflow automation, and virtual scribes—with examples and clear guardrails for when not to use AI.

Clinical Practice

AI in Clinical Practice

You’ll discover how LLMs fit into research workflows and where you can start contributing.

AI in Research

You’ll apply ANA-aligned ethical principles, stay the human-in-the-loop, navigate the evolving policy landscape, and keep equity front and center.

Safety, Policy & Ethics

Safety, Ethics, and Policy

You’ll lock in key takeaways, grab curated resources to keep learning, and know exactly what’s coming in the next module.

Wrap Up & Reflection

Quick Reference Guide

Wrap-Up & Reflection

Post-test is required with a passing grade of 80% or better.

Post Test

Evaluation

Post Test & Evaluation

Title: Introduction to AI &amp; Large Language Models (LLMs) for Nurses (No CE).Course overview: A concise, practice-focused introduction to artificial intelligence for Nurses (No CE). Learn what AI and large language models are, how they work, where they help (and where they don’t), and how to use them responsibly across education, research, and clinical practice. Real examples and plain-language demos show how AI can support—but not replace—human judgment and evidence-based care.Learning outcomes (you will be able to): • Explain how AI and large language models function. • Apply ethical and HIPAA-aware best practices for responsible use. • Analyze examples of AI integration in nursing education, research, and clinical workflows.Who should take this: RNs, APRNs, and interprofessional colleagues seeking foundational AI literacy with nursing-specific examples.Format &amp; assessment: Self-paced internet enduring activity delivered via EzyCourse with narrated slides and short demonstrations. Successful completion requires finishing the full module, passing the post-test (≥80%), and submitting the evaluation.Course details: • Completion of this course is not an accredited continuing education activity and the certificate is for participation records only. • Contact hours: 1.0 unit hour. • Criteria for successful completion: Complete the module, score ≥80%

Introductory course for nurses & other clinicians on AI and large language models. Learn what AI is, how LLMs work, safe/ethical use, & real clinical/education examples. Leave with practical prompts, policy awareness, and confidence to use AI responsibly.

Introduction to AI & Large Language Models (LLMs) for Nurses (No CE)

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Introduction to AI & Large Language Models (LLMs) for Nurses (No CE)

Stephen Ferrara

Course content

Course Description

This Course Includes