Master of Data Science Mid-Year Entry
A competitive edge in data science
Big data and data science is an emerging area of necessity for many fields—from science and engineering to economics and digital humanities.
Our Master of Data Science explores how data is changing our world. We give you the knowledge and skills to contribute in the areas you care about.
What will you do?
- Undertake a specialised introductory IT program in your first semester.
- Build core skills in programming, mathematics and data science.
- Learn how data science techniques can drive changes in organisations, industries and communities.
- Advance your abilities in chosen areas of interest.
- Combine and apply your learning in a significant project.
Where could it take you?
You might help big businesses use data to make more informed decisions in the face of uncertainty. You could analyse data from apps to drive UX updates. Perhaps you’ll come up with innovative management systems as a data architect.
This program is accredited by the Australian Computer Society (ACS) – please see the Careers section below for more accreditation and careers information.
For those who are based in Adelaide, we will be offering a blended delivery mode that combines face-to-face with remote learning in as many courses as possible, taking into consideration social distancing and hygiene. All lectures will continue to be delivered online for the remainder of the year, with some exceptions.
For our students who are studying offshore for the remainder of the 2021 Academic Year, the University will continue to offer high-quality access to the learning resources remotely for most programs. This includes all lectures, tutorials and other support material. Students will be advised in advance if there are course components that cannot be provided in remote mode and, wherever possible, offered alternative courses. Please refer to the COVID-19 FAQ page for a list of programs where in-person attendance is required.
Choose your applicant type to view the relevant admissions information for this program.
I am a:
SATAC Code 3CM203 Deferment Yes - 2 year Intake February and July Enquiries Future Students teamGraduate entry
Prerequisites SACE Stage 2 Mathematical Methods (or equivalent). MathTrackX is an online bridging program available as a recognised alternative to Mathematical Methods. Higher Education Study Advanced standing of 12 units may be granted to eligible applicants who have successfully completed the Big Data MicroMasters program and received a verified certificate for each course with a minimum overall score of 65 percent.SATAC Code: 3CM203
CRICOS 094326M Intake February and July
English Language Requirements
Australian Year 12 Successful completion of an Australian year 12 qualification with a minimum pass in an accepted English language subject English Tests accepted by the University of Adelaide IELTS Overall 6.5 Reading 6 Listening 6 Speaking 6 Writing 6 TOEFL Overall 79 Reading 13 Listening 13 Speaking 18 Writing 21 Pearson Overall 58 Reading 50 Listening 50 Speaking 50 Writing 50 C1 Advanced Overall 176 Reading 169 Listening 169 Speaking 169 Writing 169 Qualifications that meet minimum English requirements A range of alternative qualifications may meet the University’s minimum English requirements
Academic Entry RequirementsMore Information
Tertiary Qualifications Advanced standing of 12 units may be granted to eligible applicants who have successfully completed the Big Data MicroMasters program and received a verified certificate for each course with a minimum overall score of 65 percent.
Australian Year 12 SACE Stage 2 Mathematical Methods (or equivalent). MathTrackX is an online bridging program available as a recognised alternative to Mathematical Methods. International Qualifications SACE Stage 2 Mathematical Methods (or equivalent)
Fees and Scholarships
Choose your applicant type to view the relevant fees and scholarships information for this program.
I am a:
Indicative annual tuition feesAustralian Full-fee place: $37,000
Indicative annual tuition fees (24 units) International student place: $45,000
These scholarships, as well as many others funded by industry and non-profit organisations, are available to potential and currently enrolled students.
Professional AccreditationThe Master of Data Science is accredited by the Australian Computer Society.
Business Consultant, Database Coordinator, Engineer, Financial Systems / Computer Analyst, Scientific Data Analyst, Systems Analyst, Information Analyst, Information Technologist, Information and Communications Technologist, Business Analyst, Business Data Analyst, Computer Scientist, Data Analyst, Data scientist
Degree StructureThe 48-unit master's program normally takes four semesters of full-time study. However, credit in core courses to the value of 12 units on account of successful completion of the MicroMasters in Big Data with a minimum overall score of 65 per cent, is possible. As part of the 48 units, students are required to undertake a research project, deliver a public presentation and write a report on their research. The project is normally completed over two consecutive semesters.
The Masters program includes:
- eight (27 units) core foundation courses
- two (6 units) electives
- three (15 units) research courses
Academic Program Rules
The Calendar is a comprehensive handbook of the University's academic program rules.
Example Study Plan
- COMP SCI 7094 Distributed Databases & Data Mining
- COMP SCI 7201 Algorithm & Data Structure Analysis
- COMP SCI 7208 Programming and Computational Thinking for Data Science
- COMP SCI 7209 Big Data Analysis and Project
- COMP SCI 7306 Mining Big Data
- COMP SCI 7314 Introduction to Statistical Machine Learning
- MATHS 7027 Mathematical Foundations of Data Science
- MATHS 7103 Probability & Statistics
Electives, choose two of:
- COMP SCI 7007 Specialised Programming
- COMP SCI 7059 Artificial Intelligence
- COMP SCI 7076 Distributed Systems
- COMP SCI 7088 Systems Programming
- COMP SCI 7305 Parallel and Distributed Computing
- COMP SCI 7407 Advanced Algorithms
- STATS 7004 Statistics Topic A
- STATS 7014 Statistics Topic B
- STATS 7016 Statistics Topic C
- STATS 7008 Statistics Topic D
- STATS 7023 Computational Bayesian Statistics III
- STATS 7054 Statistical Modelling
- STATS 7056 Biostatistics
- STATS 7058 Time Series
- STATS 7059 Mathematical Statistics
- STATS 7069 Statistics Topic E
- STATS 7070 Statistics Topic F
- STATS 7107 Statistical Modelling and Inference
Study plans are available on the Faculty of Engineering, Computer and Mathematical Sciences website.
AssessmentResearch project, written assignments, practical work and/or examinations.
Further InformationPlease direct enquiries to Ask Adelaide
/>Phone: +61 8 8303 7335 (toll free 1800 061 459)
For more opportunities to see our campus, meet with academics, and discuss your study options, please visit our Open Day on Sunday 20 August 2017 or our Information Nights in December and January: www.adelaide.edu.au/infonight
The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.
Last updated: Friday, 5 Mar 2021