Practical Use of AI in Healthcare
Develop essential practical skills in working with healthcare data in machine learning environments. Currently only available for organisations. Register individual interest below:
$990.00 (inc GST)
What you will learn
Gain contemporary skills and knowledge for your job now.
As new technologies continue to drive innovation in healthcare, machine learning provides an exciting opportunity to improve the accuracy of diagnoses, personalise medicine, and develop new solutions to current and future challenges in patient care.
Essential for hospital data teams, medtech start-ups, and digital health companies, this online micro-credential introduces the essential practical skills that help you make effective use of healthcare data in your own business.
Throughout this course, you'll learn to analyse, clean, and prepare data for use in a machine learning environment, while gaining familiarity with industry-standard tools used to build AI healthcare solutions that improve automated decision-making and enhance patient care.
Delivered by leading medical technology experts, Practical Use of AI in Healthcare is endorsed by the Victorian Medtech Skills and Devices Hub, a respected provider of industry-aligned and future-ready medtech education courses.
An accessible introduction to building AI healthcare solutions with AI
Develop your skills with industry standard tools used to build machine solutions for healthcare environments. Suitable for newcomers to programming, you'll learn to apply a basic but complete processing pipeline from data cleansing to preprocessing and manipulation, through to machine learning and evaluation.
Work with your own healthcare data
Gain experience building a machine learning solution using your own healthcare data, with support from leading medical experts in medical AI. A key focus is on processing and interpreting data from medical images, clinical text, and sensor outputs, ensuring strong alignment with real-world applications.
Apply machine learning and evaluate outcomes
A highly practical course, students will be introduced to the fundamental elements of working with healthcare data in a machine learning environment, including essential steps such as data cleaning and manipulation, and preprocessing.
More from this series
This series of micro-credentials has been designed to address a key skills gap in the medical technology sector, providing essential instruction on technologies of growing importance to the industry.
The AI for Health Professionals series
AI for Health Professionals provides a complete learner’s journey across four micro-credentials, providing essential instruction on technologies of growing importance to the industry. You'll gain an overview of the fundamentals of AI in healthcare, be introduced to the industry-standard tools used to build AI solutions and develop your ability to interpret your own data with existing tools, before finally designing and building a custom solution.
Explore more from the AI for Health Professionals series:
- Foundations of AI in Healthcare (Micro-credential)
- Create Healthcare Solutions from Existing AI Tools (Micro-credential)
- Build Custom AI Tools for Healthcare (Micro-credential)
Fees
For individuals
To take Practical Use of AI in Healthcare as a stand-alone micro-credential, you'll pay the normal course price.
Please contact Student Support to discuss discounts and payment options for University of Melbourne staff or alumni, or to pay by invoice.
$990.00 (inc GST)
For teams
If you have three or more team members who are keen to upskill with Practical Use of AI in Healthcare, get in touch to discuss pricing. For large groups, we can also deliver and contextualise this course exclusively for your organisation.
Pricing on request
Dates
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Course details
This innovative online course is ideal for data scientists, medical technologists and healthcare professionals interested in seeking to understand how to implement machine learning systems.
Healthcare data analysts, medical AI researchers, clinical informatics specialists, and bioinformatics scientists – as well as professionals involved in seeking a career in product development and quality management will all find this course particularly useful.
Learners are expected to have:
- completed a bachelor’s degree or have equivalent levels of professional experience in a healthcare related area, and
- demonstrable understanding of programming concepts, or
- completed MMC1 Foundations of AI in Healthcare or have attained the equivalent knowledge and skills through other channels.
Recommended prior knowledge:
Proficiency with a variety of programming concepts such as functional, object-oriented, and modular programming. Proficiency with the use of command line interfaces.
This micro-credential will advance your knowledge of Medtech, with a specific focus on machine learning. You'll gain the essential tools and strategies to start building machine learning solutions for clinical research, patient care, and report analysis.
Endorsed by the Victorian Medtech Skills and Devices Hub, a leading provider of specialised medtech education, the Victorian MedTech Skills and Device Hub has been established to accelerate Victoria’s medical technology development ecosystem and help create skilled jobs for specialised Medtech professionals.
By the end of this course, you'll have the skills to apply machine learning and basic programming concepts to healthcare data.
You'll be able to:
- Programmatically load, manipulate and save healthcare data using industry-standard tools
- Apply preprocessing methods to healthcare data to enable machine learning
- Develop and evaluate basic machine learning pipelines for solving healthcare problems
This course runs over six weeks:
Your total time commitment will be approximately 42 hours, which includes:
- 4 hours guided learning
- 19 hours self study and peer learning
- 19 hours for assessment tasks
Assessment:
- Preprocessing and evaluating healthcare data using: Learn to develop code to pre-process raw data (45%)
- Application and evaluation of machine learning techniques: Create code that applies machine learning to a given healthcare problem (55%).
Practical Use of AI in Healthcare is part of the AI for Health Professionals series, which provides a pathway (known as advanced standing ) into the following graduate courses:
Eligible for advanced standing (core)
Master of Biomedical Engineering
Eligible for advanced standing (elective)
Master of Information Technology
Graduate Diploma in Computer Science
To use Practical use of AI in Healthcare in this way, you'll need to complete all four micro-credentials from the AI for Health Professionals series then apply for credit towards one of the above courses.
The AI for Health Professionals series includes:
- Foundations of AI in Healthcare
- Practical Use of AI in Healthcare
- Create Healthcare Solutions from Existing AI Tools (Expected 2025 delivery)
- Build Custom AI Tools for Healthcare (Expected 2025 delivery)
Delivered fully online, this course provides a convenient way to develop your skill set from a location that suits you. Within our digital learning environment, you'll engage with other professionals and leaders and take part in synchronous and asynchronous learning activities.
You'll have access to videos of industry leaders discussing real-world case studies. You'll also take part in live online workshops, contribute to discussion boards with your peers, and complete independent study to deepen your understanding of machine learning in a healthcare context.