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

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Eligibility and requirements

Prerequisites

One of the following:

Code Name Teaching period Credit Points
COMP20003 Algorithms and Data Structures
Semester 2 (Dual-Delivery - Parkville)
 12.5
 
Code Name Teaching period Credit Points
COMP90038 Algorithms and Complexity
Semester 2 (Dual-Delivery - Parkville)
Semester 1 (Online)
 12.5
 
Code Name Teaching period Credit Points
COMP20007 Design of Algorithms
Semester 1 (Dual-Delivery - Parkville)
 12.5
 
Code Name Teaching period Credit Points
ENGR30003 Numerical Programming for Engineers No longer available

OR

Admission into one of the following courses:

MC-ENG Master of Engineering (200 program only)
MC-IT Master of Information Technology, 100 or 150 pt program in Distributed Computing, Computing, Cyber Security or Artificial Intelligence
MC-IT Master of Information Technology, 100 pt program in Human-Centre Interaction
MC-SCICMP Master of Science (Computer Science)

MC-CS Master of Computer Science


 

Corequisites

None

Non-allowed subjects

Code Name Teaching period Credit Points
COMP30018 Knowledge Technologies No longer available
 OR 433-352 Data on the Web

 AND

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

 

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: 3 November 2022