AI+ Nurse™ - eLearning (exam included)

AI+ Nurse™ - eLearning (exam included)

AI+ Nurse™ is a role-based certification designed to empower nursing professionals, healthcare educators, and clinical informatics specialists with skills to integrate AI into nursing practice. The course bridges nursing fundamentals with AI capabilities to enhance patient monitoring, decision support, workflow automation, and data-driven nursing care.

Blending Compassion with Intelligent Care

• AI-Enhanced Patient Care: Empower nurses to harness AI tools that improve patient outcomes and safety.
• Informed Decision-Making: Develop the ability to use data-driven insights for smarter clinical and operational choices.
• Holistic AI Knowledge: Gain a full understanding of AI — from core concepts to practical applications in healthcare.
• AI-Driven Clinical Excellence: Equip nursing professionals to confidently apply AI in everyday patient care and clinical workflows.

Why This Course Matters

• Patient-Centric AI Care: Enable nurses to use AI tools to improve patient outcomes, early warning systems, and proactive care.
• Decision Support in Clinical Practice: Learn to leverage AI for medication management, triage, documentation, and care planning.
• Streamlined Workflows: Understand how AI can reduce administrative burdens and streamline daily nursing tasks.
• Ethical & Human-Centered AI: Focus on responsible practices that preserve trust, empathy, and patient values in AI use.
• Hands-On Simulations: Practice in realistic nursing scenarios using AI-powered case studies and simulations.

Key Features

• Course and material in English
• Beginner-Intermediate level (Category: AI+ Professional)
• 1 year access to the platform 24/7

• 6 hours of video lessons & multimedia resources
• 15 hours of study time recommendation
• Quizzes, Assessments, and Course Resources
• Online Proctored Exam with One Free Retake
• Certification of completion included
• Tools You’ll Explore: Python, Scikit-learn, Keras, Jupyter Notebooks, Matplotlib, PowerBI

Learning Outcomes

• Integrate AI tools into nursing workflows to enhance patient monitoring, diagnostics, and care coordination.
• Apply data-driven insights to make informed clinical and operational decisions that improve patient outcomes.
• Understand AI fundamentals including machine learning, predictive analytics, and natural language processing (NLP) in a healthcare context.
• Leverage AI in patient management for tasks such as early risk detection, triage, and personalized care planning.
• Collaborate effectively with AI systems and interdisciplinary teams to optimize care delivery.
• Evaluate and implement AI tools safely within clinical settings, ensuring accuracy, transparency, and reliability.
• Address ethical, legal, and regulatory considerations related to AI in healthcare, including data privacy and bias mitigation.
• Lead innovation initiatives by promoting AI adoption and digital transformation in nursing practice.

Target Audience

• Registered nurses (RNs) wanting to bring AI into patient care
• Nursing students aiming for future-ready skills
• Healthcare administrators seeking to optimize nursing operations
• Clinical informatics specialists working with EHRs & data analytics
• Nurse educators preparing curriculum for AI-informed nursing practice

Prerequisites

• Basic nursing knowledge (clinical practices, patient care)
• Familiarity with healthcare technology (EHRs, medical devices)
• Introduction to data science / analysis in healthcare
• Basic understanding of AI / machine learning concepts
• Critical thinking and problem-solving capacity for data-driven care decisions

Exam Details

• Duration: 90 minutes
• Passing :70% (35/50)
• Format: 50 multiple-choice/multiple-response questions
• Delivery Method: Online via proctored exam platform (flexible scheduling)
• Language: English

Course Content

Module 1: What is AI for Nurses

• Explore how AI is transforming modern nursing practice.
• Discover where and how AI is applied in patient care and hospital operations.
• Analyze a case study on improving patient safety and nursing efficiency at Riverside Medical Center.
• Hands-on activity: Use Nurse AI tools for clinical data visualization in postoperative care.

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

• Learn the basics of Natural Language Processing (NLP) and its use in healthcare documentation.
• Understand workflow automation and how AI enhances nursing efficiency.
• Build data literacy skills to interpret and manage clinical information effectively.
• Explore the legal and compliance aspects of AI documentation in nursing.
• Case study: Integrating AI workflow automation at Massachusetts General Hospital (MGH).
• Hands-on: Use the ChatGPT RN tool for clinical documentation and patient education.

Module 3: Predictive AI and Patient Safety

• Understand how predictive models support early risk detection and patient monitoring.
• Examine the challenges of alert fatigue and establishing trust in AI systems.
• Participate in simulations to respond to real-time deterioration alerts.
• Learn how interdisciplinary teams collaborate around AI insights.
• Discuss bias in predictive algorithms and its impact on patient outcomes.
• Hands-on: Interpret predictive alerts with ChatGPT for clinical decision support.

Module 4: Generative AI and Nursing Education

• Get introduced to Generative AI and its role in modern nursing.
• Understand how large language models (LLMs) support nursing tasks and education.
• Create patient education materials using AI tools.
• Learn safe and ethical practices for AI use in healthcare.
• Case study and hands-on: Use AI-powered tools like Symptoma for differential diagnosis.

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

• Explore fairness, inclusion, and bias mitigation in AI systems.
• Understand transparency, informed consent, and ethical communication with patients.
• Strengthen advocacy skills and uphold professional responsibilities in AI use.
• Develop an ethics checklist for responsible AI adoption.
• Study legal, regulatory, and social implications of AI in healthcare.
• Case study: Addressing racial bias in healthcare algorithms (Optum case).
• Hands-on: Conduct a fairness audit using Aequitas for diabetes risk prediction.

Module 6: Evaluating and Selecting AI Tools

• Learn to interpret AI performance metrics for clinical reliability.
• Identify vendor red flags and questions to ask before adopting AI solutions.
• Understand the nurse’s role in evaluating and selecting AI technologies.
• Use evaluation templates and checklists for decision-making.
• Case study: Enhancing real-time clinical decisions at UAB Medicine with MIC Sickbay.
• Hands-on: Evaluate AI diagnostic performance using confusion matrix metrics.

Module 7: Implementing AI and Leading Change on the Unit

• Build team buy-in and position AI as a supportive tool, not a replacement.
• Master change management strategies for AI adoption.
• Create an AI playbook for sustainable, scalable implementation.
• Monitor quality improvement through AI-driven performance metrics.
• Develop error reporting and safety protocols for AI-integrated workflows.
• Hands-on: Calculate and visualize clinical risk scores with ChatGPT.

Licensing and accreditation

This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements.

Equity Policy

AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.

FAQ

Can I apply what I learn in this course to real-world scenarios right away?

Absolutely. You’ll develop hands-on experience through nursing-specific case studies and projects, enabling you to immediately apply AI tools in patient care settings.

What makes this course unique compared to other Healthcare and AI programs?

This course bridges nursing practice with applied AI training, focusing on enhancing workflow efficiency, patient monitoring, and overall care delivery through intelligent systems.

What kind of projects will I complete?

You’ll engage in projects involving AI-assisted patient monitoring, electronic health record (EHR) documentation, predictive alert systems, and workflow automation tailored for nursing applications.

How is the course designed to ensure effective learning?

The program combines interactive learning modules, and realistic nursing simulations to ensure deep understanding and skill mastery.

How does this course prepare me for career advancement?

You’ll gain in-demand AI and data literacy skills within a clinical context—equipping you for leadership and innovation roles in AI-powered healthcare environments.

How Can AVC Help Foster an AI-Ready Culture?

While AI offers significant advantages, many organizations struggle with challenges like talent gaps, complex data environments, and system integration barriers. At AVC, we understand these obstacles and have tailored our certification programs to help businesses overcome them effectively.

Our strategic approach focuses on building a culture that embraces AI adoption and innovation. Through our industry-recognized certifications and in-depth training, we equip your workforce with the skills and knowledge needed to lead your organization confidently into an AI-powered future.

Customized for Impact: Our programs aren't one-size-fits-all. We offer specialized training designed by industry experts to equip your workforce with the specific skills and knowledge needed for critical AI roles.

Practical, Real-World Learning: We prioritize hands-on experience over theory, using real-world projects and case studies. This approach ensures your team gains the confidence and capability to implement AI solutions effectively, driving innovation and measurable business outcomes.