Data Science - C6004

Data Science

Expert master degree

Data Scientists are in demand in the information age, where big data is ever changing and ever challenging. Data Science extracts value from data assets, helping us understand the past, better manage the present, and effectively plan for the future. It plays a critical role in advancing industry, commerce, governance and research so graduates skilled in this area are highly sought after.

The Master of Data Science (MDS) teaches you how to explore data and discover its potential – how to find innovative solutions to real problems in science, business and government, from technology start-ups to global organisations. With a degree in science, engineering, arts or computing, you can pursue a Master of Data Science, gaining skills in data management, data analytics and data processing – skills needed in this fast-growing field.

The MDS expands your knowledge of the analytical, organisational and computational aspects of data. You learn to manage data and gain an understanding of its impact on society.

The MDS caters to students from a variety of backgrounds by including foundation units in programming, databases and maths or statistics. However, if you have this background from previous studies or work experience, you may accelerate your study with an exemption from these units, or choose to take more data science electives.

The core coursework covers data science objectives, data analysis, data pre-processing and visualisation. You then select data science electives such as machine learning, learning from semi-structured data like text, and big data handling. Your course electives allow you to build deeper skills in data analytics and machine learning.

Our highly regarded faculty takes great pride in developing the most up-to-date material while maintaining a solid core of established theory and platforms, including Python and R (two of the most popular open-source programming languages for data analysis), Hadoop and Spark (for distributed processing). You also gain hands-on experience with state-of-the-art tools and get exposure to key industry players.

In your final semester, you will take part in an Industry Experience team project, working with industry mentors to develop data-driven IT solutions. Or you will undertake a minor-thesis research project, investigating cutting-edge problems under the supervision of internationally recognised researchers.

Students wishing to exit early can complete with a Graduate Certificate or Graduate Diploma of Data Science.

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At a glance

Course Details

Location
  • On-campus at Clayton: Full time & part time
Duration 1, 1.5 or 2 years full-time depending on prior qualifications. See entry requirements.
Start date Semester one (February), Semester two (July)
Qualification Master of Data Science
Course Handbook

Data Science

Entry Requirements

You need to satisfy the following entrance requirements to be considered for entry to this course.

Equivalent Australian Year 12

Minimum Entry Requirements (Domestic students)

Qualifications

Entry requirements for 2019

Entry level 1:

Duration: 2 years full-time, 4 years part-time (96 points to complete)

An Australian undergraduate degree, not necessarily in IT, with at least a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent.

Entry level 2:

Duration: 1.5 years full-time, 3 years part-time (72 points to complete)

An Australian undergraduate degree in a cognate discipline relating to IT, or a business, engineering or science degree with an IT major including programming, databases and mathematics, with at least a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent.

or

A four-year Australian honours degree with a research thesis consisting of at least 37.5% of a one year full time load and with at least a pass a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent.

Entry level 3:

Duration: 1 years full-time, 2 years part-time (48 points to complete)

A four-year Australian honours degree in a cognate discipline relating to IT, or a business, science or engineering degree with an IT major including programming, databases and mathematics, with a research thesis consisting of at least 37.5% of a one year full time load and with at least a 60% average, or qualification deemed by the faculty to be a satisfactory equivalent.

English requirements

Applicants must also meet the English language requirements.

University entrance requirements

Minimum entrance requirements for admission to Monash University Australia.

Making the application

Future students

Semester one (February)

Apply directly to Monash using course code C6004

Semester two (July)

Apply directly to Monash using course code C6004

Current Monash students

Current Monash students should apply for an internal transfer.

Self assess for credit eligibility

Check for study credit using the "Credit search" link on the Credit for prior study page

Fees

Fees are subject to change annually.

Full fee

Fees are per 48 credit points which represents a standard full-time course load for a year.

A$33,600

Fee assistance

As a full fee-paying student, you may be eligible to apply for the optional FEE-HELP to assist you to pay all or part of your tuition fees.

Scholarships

We offer over 360 types of scholarships, valued at up to $280,000. Some scholarships offer one-off payments while others continue for the length of your course. Learn more about Monash Scholarships.

Other fees

The Student Services and Amenities Fee applies to some students each calendar year.

The course is structured in three parts, A, B and C. All students complete Part B (core studies). Depending upon prior qualifications, you may receive credit for Part A (foundation studies) or Part C (advanced studies) or a combination of the two.

Note that if you are eligible for credit for prior studies you may elect not to receive the credit.