Statistical Machine Learning (COMP90051) // Eligibility and requirements
About this subject
Contact information
Semester 2
Dr Benjamin Rubinstein
Eligibility and requirements
Prerequisites
One of the following:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP30018 | Knowledge Technologies | Not available in 2017 |
12.5 |
COMP90049 | Knowledge Technologies |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP30027 | Machine Learning | Semester 1 (On Campus - Parkville) |
12.5 |
OR admission into MCIT-150 or MCIT-100
Corequisites
None
Non-allowed subjects
433-484 Machine Learning
433-679 Evolutionary and Neural Computation
433-680 Machine Learning
433-684 Machine Learning
Recommended background knowledge
Basic probability
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