Introduction to Machine Learning (COMP90049) // Eligibility and requirements

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Eligibility and requirements

Prerequisites

Students must meet one of the following prerequisite options:

Option 1

One of

Code Name Teaching period Credit Points
COMP20003 Algorithms and Data Structures
Semester 2 (On Campus - Parkville)
 12.5
COMP20007 Design of Algorithms
Semester 1 (On Campus - Parkville)
 12.5
COMP90038 Algorithms and Complexity
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
 12.5
ENGR30004 Numerical Algorithms in Engineering
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5

ENGR30003 Numerical Programming for Engineers

Option 2

Admission into or selection of one of the following:

  • MC-SCICMP Master of Science (Computer Science)
  • MC-CS Master of Computer Science
  • GC-CS Graduate Certificate in Computer Science

Option 3

Admission into or selection of one of the following:

  • Distributed Computing (100pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Computing (100pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Cyber Security (100pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Artificial Intelligence (100pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Human-Computer Interaction (100pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Digital Innovation (100pt) specialisation (formal) in the MC-IT Master of Information Technology

Option 4

Admission into or selection of one of the following:

  • Distributed Computing (150pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Computing (150pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Cyber Security (150pt) specialisation (formal) in the MC-IT Master of Information Technology
  • Artificial Intelligence (150pt) specialisation (formal) in the MC-IT Master of Information Technology

Corequisites

None

Non-allowed subjects

Code Name Teaching period Credit Points
COMP30027 Machine Learning
Semester 1 (On Campus - Parkville)
 12.5

COMP30018 Knowledge Technologies

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: 4 March 2025