Course overview
An introduction to the use and application of key machine learning tools. Students will learn to build software that uses pre-existing toolkits as appropriate to solve a variety of machine learning problems. The course will have a practical focus using case studies and worked examples, with an emphasis on ensuring that solutions are valid and verifiable.
Course learning outcomes
- Apply industry standard software tools to model and solve machine learning tasks on real data sets
- Select an appropriate method and tool for a given problem and data set
- Distinguish problems and data sets that are amenable to machine learning methods from those that are not
- Analyse results and solutions to verify their correctness, and identify sources of error
- Compare the significance and validity of solutions obtained by multiple methods
- Design data management procedures to enable accurate application of machine learning
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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.