Computational Statistics & Data Science (MAST90083) // Eligibility and requirements
Eligibility and requirements
Prerequisites
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST30025 | Linear Statistical Models | Semester 1 (On Campus - Parkville) |
12.5 |
OR
Note: the following subject/s can also be taken concurrently (at the same time):
One of
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MAST30027 | Modern Applied Statistics | Semester 2 (On Campus - Parkville) |
12.5 |
| MAST90104 | A First Course In Statistical Learning | Semester 2 (On Campus - Parkville) |
25 |
OR
Admission into the Statistical Data Science specialisation (formal) in the MC-DATASC Master of Data Science
OR
Admission into the Computational and Statistical Data Science specialisation (formal) in the MC-DATASC Master of Data Science
OR
Admission into one of:
• Master of Data Science (MC-DATASC)- Statistics Background Stream (pre-2025)
• Master of Data Science (MC-DATASC) - Data Science Background Stream (pre-2025)
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: 4 March 2025