Master of Data Science (MC-DATASC)

Overview

Entry requirements

In order to be considered for entry, applicants must have completed:

• Any undergraduate degree with a major in Computer Science, Data Science or Statistics with a weighted average mark of at least H3 (65%), or equivalent
• A 12.5 point subject from computer science or related disciplines whose content is focused on computer programming (taken at any tertiary year level)
• 25 points of first-year tertiary Mathematics and Statistics subjects including MAST10006 Calculus 2 or equivalent

Meeting these requirements does not guarantee selection.

In ranking applications, the Selection Committee will consider prior academic performance.

The Selection Committee may seek further information to clarify any aspect of an application in accordance with the Academic Board rules on the use of selection instruments.

Applicants are required to satisfy the university’s English language requirements for postgraduate courses. For those applicants seeking to meet these requirements by one of the standard tests approved by the Academic Board, performance band 6.5 is required.

Inherent requirements (core participation requirements)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.The University is dedicated to providingsupport to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website. http://www.services.unimelb.edu.au/disability/

Course structure

This 200 point Master is based around

• 125 points of compulsory subjects: four core subjects in statistics (50 points) , four core subjects in computer science (50 points) and a 25 point capstone project;
• and 25 points of electives*.

Subject options

*‘Prerequisite’ Subjects (up to 50 points depending on educational background)

It is expected that students admitted into the course will have either computer science or statistics background, though some students may have a mix of both.

• If a student has a computer science background, they will be required to complete statistics subjects in their first year as part of their elective component to satisfy the prerequsites for the Statistics core subjects
• If the student has Statistics background, they will need to complete computer science subjects in their first year as part of their elective component to satisfy the prerequsites for the Computer Science core subjects
• If a student already meets the prerequisites for the core subejcts, they can choose their elective subjects freely.

Dependant upon educational background students may need to take up to 50 points of the following:

-

Student entering with a Computer Science background may need to take

Student entering with a Statistics background may need to take:

Core (125 points):

Students must take:

Statistics core subjects

Computer Science core subjects

Capstone Project

Students are expected to have completed at least two semesters of their course before beginning the Data Science Project

Electives (50-75 points):

The remainder of the 200 points are made up subjects that may include Prerequisite Subjects (maximum 50 points, listed above), Discipline Elective Subjects, Professional Skills Subjects (maximum 25 pts) and an optional Data Science Research Project.

Discipline Elective Subjects

Professional Skills Subjects

Students may take no more than 25 points of the following:

Data Science Research Project

Students who maintain a sufficiently high weighted average mark will be eligible to undertake a 25 point individual research project in Data Science:

Students must first have agreement from a supervisor before enrolling in the research project.

Last updated: 18 December 2020