1. Handbook
  2. Subjects
  3. Machine Learning Applications for Health
  4. Eligibility and requirements

Machine Learning Applications for Health (COMP90089) // Eligibility and requirements

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Eligibility and requirements

Prerequisites

Admission into or selection of one of the following:

  • MC-SCICMP Master of Science (Computer Science)
  • MC-SOFTENG Master of Software Engineering
  • MC-IT Master of Information Technology
  • MC-DATASC Master of Data Science
  • GD-CS Graduate Diploma in Computer Science
  • MC-ENG Master of Engineering
  • MC-CS Master of Computer Science

OR

Completion of one of the subjects below

Code Name Teaching period Credit Points
COMP90059 Introduction to Programming
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
 12.5
COMP90038 Algorithms and Complexity
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5

Or equivalent

OR

Permission of the coordinator is required prior to enrolling in this subject (some programming experience in Python is required)

Corequisites

None

Non-allowed subjects

None

Inherent requirements (core participation requirements)

The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.

Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home

Last updated: 31 January 2024