Course overview
This course covers modern machine learning methods particularly useful for large and complex health data Content includes: Linear Regression and K -Nearest Neighbours; Classification (logistic regression, linear discriminant analysis); Resampling Methods (Cross-Validation, Bootstrap); Model Selection and Regularization (subset selection, shrinkage methods, dimension reduction methods); Beyond Linearity (fractional polynomials, basis functions, splines, generalized additive models); Tree-Based Methods (decision trees, bagging, random forests, boosting).
Course learning outcomes
- Recognise situations where machine learning methods can offer advantages over traditional statistical modelling approaches to data analyses in health applications
- Recognise and explain the differences between the goals of description and prediction
- Determine and implement appropriate machine learning approaches for description and prediction in real-world health applications
- Measure and explain the uncertainty of the results of analyses using machine learning approaches
- Interpret the results of analyses using machine learning in light of the assumptions required, the quality of input data, and the sensitivity to the specific technique implemented
- Critically appraise published papers concerning machine learning applications for classification or prediction in health
- Effectively communicate results of analyses in language suitable for a clinical or epidemiological journal
Availability
Class details
Online
Group 1
Class number 60444
Section 01OL
Size 30
Available 30
Fee calculator
To display course fees for 2027, select your status and program below:
Study Abroad student tuition fees are available here.
Only some Postgraduate Coursework programs are available as Commonwealth Supported. Please check your program for specific fee information.
If you are studying in a Professional Pathway Psychology, Clinical Psychology or Social Work program, please refer to the Student Contributions amounts published here.
The Student Contribution amount displayed below is for students commencing a new program from 2021 onwards. If you are continuing in a program you commenced prior to 1 January 2021, or are commencing an Honours degree relating to an undergraduate degree you commenced prior to 1 January 2021, you may be charged a different Student Contribution amount from the amount displayed below. Please check the Student Contribution bands for continuing students here. If you are an international student, or a domestic student studying in a full fee paying place, and are continuing study that you commenced in 2025 or earlier, your fees will be available here before enrolments open for 2026.