Artificial Intelligence and Machine Learning Courses

AI+ Medical Assistant - Self-paced

Length 365 days access
Price $495 inc GST
Inclusions Online exam

Course overview

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Why study this course

The AI+ Medical Assistant course is designed for medical assistants, clinical support staff, nursing teams, and healthcare professionals seeking to integrate AI into modern clinical and administrative workflows. The course delivers practical, role-based skills that enable these professionals to leverage AI for patient care, workflow optimisation, and clinical support, enhancing efficiency and decision-making across healthcare environments.

Throughout the course, learners will explore key areas such as patient data analysis, predictive diagnostics, medical documentation automation, and AI-driven workflow management using technologies like machine learning and natural language processing. With a strong emphasis on hands-on, real-world application, the course equips students with the experience to streamline healthcare processes, improve patient outcomes, and support accurate, data-driven clinical decision-making.

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

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What you’ll learn

Through this course, students will be able to:

Learn how AI is changing healthcare delivery, workflows, and patient support practices.
Develop skills to apply AI for analyzing patient data and extracting useful clinical insights.
Grasp how to use AI tools that support diagnostics and improve day-to-day clinical decisions.
Apply AI to streamline documentation, scheduling support, and routine administrative tasks efficiently.
Develop the ability to implement AI driven solutions that optimize workflows and enhance care quality.
Grasp how to apply secure handling practices to protect sensitive patient information in AI-enabled settings.
Equip themselves to contribute using hands-on exercises and case studies in real healthcare environments.

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.

View all AI CERTs at Lumify Work courses

Who is the course for?

This course is intended for:

Medical Assistants in Clinics and Hospitals
Clinical Support Staff and Coordinators
EHR and Documentation-Focused Professionals
Aspiring Medical Assistants and Healthcare Learners
Healthcare Professionals Transitioning to Support Roles

Course subjects

Module 1: Fundamentals of AI for Medical Assistants

Understanding AI and Its Healthcare Applications
The Role of AI in Medical Assistance
Case Studies
Hands-on Session: Functionality Survey and Stepwise Analysis of the Eka.care Patient-Side Application

Module 2: Data Literacy for Medical Assistants

Healthcare Data Types and Management
Using Data Effectively in AI
Case Studies
Hands-On Session: Structured vs. Unstructured Data in Healthcare — A Practical Study Using Eka.care Patient Health Record System

Module 3: AI in Patient Care Optimization

Enhancing Patient Interactions with AI
Predictive Analytics and Workflow Management
Case Studies
Hands-On Session: Eka.care in Action — Appointment Management, Smart Reminders & Tele-Consult Dashboards

Module 4: NLP and Generative AI in Medical Documentation

Foundations of NLP for Medical Assistants
Practical Applications and Risks
Case Studies
Hands-On Simulation Exercise
Hands-On Session: Automating Clinical Documentation Using Eka.care — Notes, Summaries, and Communication Workflows

Module 5: AI in Diagnostics and Screening

Diagnostic Support Tools
Real-World Applications and Simulation
Use Cases
Hands-On: AI-Powered Detection of Common Health Conditions — Review and Analysis of AI-Suggested Diagnostic Insights Using Eka.care

Module 6: Ethics, Bias, and Regulation in AI for Healthcare

Recognizing and Addressing Bias in AI
Legal, Ethical, and Compliance Frameworks
Hands-On Exercise: Analyzing and Visualizing Bias in AI Systems — Exploring Racial, Socioeconomic, and Demographic Disparities Using Google’s What-If Tool

Module 7: Evaluating and Implementing AI Tools

Selecting and Planning for AI Adoption
Best Practices and Stakeholder Engagement
Case Study: Procurement and Early Deployment of AI Tools for Chest Diagnostics in a National Health Service Setting
Hands-On Simulation Exercise: Recognizing Red Flags in Vendor Solutions for AI in Medical Assistance
Hands-On Exercise: Evaluating the Relevance and Effectiveness of AI Models Using Zoho Analytics

Module 8: Cybersecurity and Emerging Trends in AI

Cybersecurity Risks and Protection
Future Trends and Preparing for Innovation
Case Study: EY’s Strategic Transformation — Adapting to Emerging AI Technologies
Hands-On Exercise: Common Cybersecurity Threats in AI-Enabled Healthcare — A Hands-On Exploration Using Google Sheets

Prerequisites

Familiarity with healthcare concepts and terminology.
Understanding of machine learning and algorithms.
Ability to analyze and interpret medical data.
Proficiency in Python or similar languages for AI tools.
Knowledge of clinical workflows and medical practices.

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.