Transforming Healthcare with Data Analytics and AI
Leverage data-driven insights and AI to transform healthcare
Harness the power of data analytics and artificial intelligence (AI) to revolutionise healthcare. This course equips you with the tools to navigate the complexities of healthcare data, leverage AI technologies, and translate healthcare data into solutions that improve clinical practice and operational efficiency.
This is a 12-week, 100% online short course consisting of weekly self-paced online learning modules (3 hours) and engaging live Zoom workshops (2.5 hours), facilitated by interprofessional specialists, data/AI experts and health tech industry leaders. Each week, you will engage in interactive workshop sessions, designed to enhance your understanding of healthcare data analytics and AI concepts. Workshop sessions will run from 6:30-8:30 PM on a weeknight. Full schedule available below. Places are limited. Sign up now to secure your spot.
If you are interested in earning University credit points for this course, enrol in it as a single subject, as an elective in your Masters degree. CHIA CPD points awarded.
What you will learn
By the end of this course, you will:
- Appraise the benefits and limitations of implementing emerging healthcare solutions in data analytics and AI.
- Translate data project ideas into clinically relevant questions that empower data and EMR teams to generate actionable datasets.
- Demonstrate foundational data concepts, including healthcare data sources, collection, standards, preparation, and analysis.
- Illustrate how to derive insights from data to improve clinical practice through computable and shareable knowledge.
Hospitals and healthcare settings generate vast amounts of data, but how can we make the most of it? This course helps you unlock the potential of healthcare data and AI, empowering you to turn information into actionable insights that can improve patient care and operational efficiency
Explore before you enrol
Begin exploring the course at your own pace. Engage with a short 8-minute microlearning module or sample one of our on-demand modules drawn from the full program.
Our on-demand modules include 3 hours of self-paced material and a 2-hour pre-recorded workshop. These workshops let you explore key concepts and apply practical skills — without committing to a full course.
From the course, into the clinic
Dr Belinda Hibble, ED physician and Director of Emergency Services at Barwon Health, could see the potential of data to improve clinical decisions and wanted a structured, evidence-based way to use data-driven insights with her leadership team.
Course outline
This course offers a structured series of interconnected modules, blending 3 hours of self-paced online learning with 2 hours of live sessions, to guide you through the process of transforming healthcare using data analytics and AI.
Week 1: Why Data?
- Explore how data analytics and AI can save time and improve patient care.
Weeks 2–4: Healthcare Data and Processes
- Learn about available data sources and the data journey within healthcare organisations.
- Understand data ethics, governance, and storage.
Weeks 5–7: Data Selection and Preparation
- Craft clinically-relevant data questions and develop digital phenotypes.
- Create and communicate data queries and perform data preparation and quality checks.
Weeks 8–11: Data Analysis
- Dive into descriptive analysis, hypothesis testing, regression analysis, machine learning, and AI techniques.
Week 12: Communication
- Master the art of storytelling to present clear and persuasive findings.
Key features
- Expert insights: Learn from leaders in healthcare, AI, and data science.
- Hands-on learning: Work with real healthcare data to solve practical challenges.
- Ethical focus: Address equity and ethics in designing AI solutions.
- Collaborative projects: Engage with interdisciplinary peers and stakeholders.
- Real-world impact: Develop solutions with practical applications in healthcare.
FAQs
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Fees apply:
- $2590 for senior hospital medical staff with CME budget
- $1770 for others
- $1330 Unimelb Staff/Students
- International - submit an inquiry
Group discounts are available. For more information, click here.
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Group discounts are available. For more information, click here.
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There are no formal prerequisites, but participants should be ready to engage with online material and participate in Zoom workshops.
- Strong interest in the topic and commitment to complete the course and engage in real-time sessions
- No healthcare expertise required.
- No data analytics required.
A few clarifications:
- You do not need prior analytics or coding experience
- The course starts with foundations and builds step by step
- You will work with real-world data, not abstract toy examples
- You will be learning alongside clinicians, managers, data and IT staff – not in a room full of data scientists
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This course is built for people who:
- Work with data‑rich services, but have never had a structured way to use that data
- Need to lead or evaluate digital initiatives, but do not have a technical background
- Want to understand AI well enough to ask the right questions and make good decisions
This includes:
- Hospital and Primary Care Professionals: With a focus on hospital-based participants.
- Clinicians: Interested in specialising or acquiring essential skills for future projects.
- Novice Data Analysts: Those at the beginning of their analytics journey.
- Emerging Researchers: Including Master's and PhD students, as well as clinical researchers.
- Non-Clinicians: Such as EMR team members, managers, and quality and safety staff.
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Contact the CDTH Education Team, Cdth-education@unimelb.edu.au, if you have any questions about the course or any payment queries.
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Topics Dates
(Tuesdays 6:30-8:30 PM)0. Orientation 1. How can data analytics and AI save time and improve patient care? 28/07/2026 2. What data sources are available? 4/08/2026
(no workshop)3. What is the data journey and architecture at a health organisation? 11/08/2026 4. How do I navigate ethics, governance and storage? 18/08/2026
(no workshop)5. How do I craft data questions and digitally phenotype? 25/08/2026 6. How do I create and communicate data queries? How can I prepare and quality check the data? 1/09/2026 7. Descriptive analysis 8/09/2026 8. Regression 15/09/2026 9. Machine Learning 22/09/2026 Mid-unit break (1 Week) 10. AI in Healthcare (CDS) 6/10/2026 11. AI in Healthcare (Gen AI/LLMs/NLP) 13/10/2026 12. How can I tell a clear, persuasive story with my findings? 20/10/2026