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AI CERTS® certification

AI+ Healthcare Fundamentals™

Formerly known as AI+ Healthcare™ Revolutionize Patient Care with Advanced AI

AI+ Healthcare Fundamentals™ certification badge

Course overview

Review the course before deciding whether it is suitable.

Healthcare Transformation: Learn how AI reshapes predictive analytics, diagnostics, and patient-centric solutions Comprehensive Modules: Covers ML, NLP, and ethical healthcare applications Practical Impact: Address real challenges like personalised medicine and operational efficiency Regulatory Navigation: Understand compliance and legal standards for AI in healthcare

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 networking knowledge, Python familiarity, fundamental AI/ML concepts

Course focus

Why this certification may be relevant.

01

Demand for AI-Certified Healthcare Professionals:

Healthcare organizations seek certified professionals who can balance innovation with patient safety and data privacy.

02

Mitigating AI Risks in Healthcare:

Misuse of AI in healthcare can compromise patient care and trust. This certification helps professionals avoid such risks.

03

Designing AI Strategies for Quality Healthcare:

Certified professionals contribute to designing healthcare AI strategies that enhance care quality while ensuring compliance and safety.

04

Gaining Career Advantage:

As AI adoption in healthcare accelerates, this certification gives professionals a distinct advantage in advancing their careers.

Who it may suit

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Course content

Modules supplied by AI CERTs.

Open each module to review the stated topics.

01Course Overview
  • Course Introduction Preview
02Module 1: Introduction to AI in Healthcare
  • 1.1 Fundamentals of Artificial Intelligence
  • 1.2 AI in the Healthcare Ecosystem
  • 1.3 Ethical and Regulatory Framework
03Module 2: Data Handling and AI Modelling
  • 2.1 Data Acquisition and Management
  • 2.2 Preprocessing Techniques for Medical Data
  • 2.3 Model Development and Validation
04Module 3: AI in Medical Imaging
  • 3.1 Introduction to Medical Imaging
  • 3.2 AI Techniques in Imaging
  • 3.3 Implementation and Future Trends
05Module 4: AI in Diagnostics and Predictive Analytics
  • 4.1 AI-powered Diagnostic Systems
  • 4.2 Predictive Analytics in Healthcare
  • 4.3 Challenges and Solutions
06Module 5: AI in Treatment Planning and Personalized Medicine
  • 5.1 Customized Treatment Solutions
  • 5.2 Machine Learning Models in Treatment
  • 5.3 Case Studies and Ethics
07Module 6: AI in Patient Monitoring & Care Management
  • 6.1 Wearable Technologies and IoT in Healthcare
  • 6.2 Remote Patient Monitoring Systems
  • 6.3 Impact on Healthcare Delivery
08Module 7: AI in Health Insurance and Healthcare Management
  • 7.1 AI in Health Insurance
  • 7.2 Operational Efficiency in Healthcare
  • 7.3 Future of AI in Health Systems
09Module 8: Advanced Topics and Future Directions in AI+ Healthcare
  • 8.1 Innovations in AI and Their Impact on Healthcare
  • 8.2 Interdisciplinary Approaches
  • 8.3 Preparing for the Future
10Optional Module: AI Agents for Healthcare
  • 1. What Are AI Agents for Healthcare?
  • 2. Applications of AI Agents in Healthcare
  • 3. Aligned Examples

Tools referenced by AI CERTs

Platforms and tools included in the course information.

PathAIViz.aiTempusVirtuSense
Before you enrol

This 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.

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