Statistical Machine Learning (COMP90051) // Further information

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Further information

  • Texts

    Prescribed texts

    None

  • Subject notes

    LEARNING AND TEACHING METHODS

    The subject is delivered through a combination of lectures and tutorials. One feature of the subject is that the projects are designed to be relatively open-ended and broad enough that students have scope to get hands-on experience implementing the breadth of material covered in the subject, as well as building off the subject content in innovating their own methods/researching related methods from the research literature and implementing them themselves.

     

    INDICATIVE KEY LEARNING RESOURCES

    Students will have access to lecture slides, readings relating to the lecture materials (both from a textbook and conference/journal papers), tutorial worksheets with worked solutions for all numeric problems, and sample reports to use in writing the project reports. Students are permitted to do their programming in Python and any programming environment/OS.

     

    CAREERS / INDUSTRY LINKS

    Machine learning has been growing rapidly in industry over the past two decades, with key industry players including Google, Microsoft, Amazon and Meta. There have been guest lecturers in the subject from organisations such as NICTA, which has a strong interest in machine learning (indeed one of the primary research groupings within NICTA is based on Machine Learning).

     

  • Related Handbook entries

    This subject contributes to the following:

    TypeName
    CourseMaster of Data Science
    CourseMaster of Science (Computer Science)
    CoursePh.D.- Engineering
    CourseMaster of Commerce (Decision, Risk and Financial Sciences)
    CourseDoctor of Philosophy - Engineering
    CourseMaster of Philosophy - Engineering
  • Available through the Community Access Program

    About the Community Access Program (CAP)

    This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.

    Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants

    Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.

    Additional information for this subject

    Subject coordinator approval required.

  • Available to Study Abroad and/or Study Exchange Students

    This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.

Last updated: 4 March 2025