Master of Data Science
Campus North Terrace Campus
Degree Type Masters by Coursework
Duration 2 years full-time or part-time equiv.
SATAC Code 3CM203
This program provides the necessary skills for entering the world of big data and data science, an emerging area of necessity for many fields, including science, engineering, economics and digital humanities. The program will help students understand how data is changing our world, and how learners can apply data science techniques to drive changes in their organisation or area.
In the Master of Data Science, students undertake a specialised introductory program in their first semester, designed to address fundamental requirements in programming, mathematics and data science. Students then proceed with a program of courses tailored to their particular interest, building skill and knowledge in data science, as well as a significant project designed to combine skills developed across the program.
Choose your applicant type to view the relevant admissions information for this program.
I am a:
SATAC Code 3CM203 Intake February and July Enquiries Ask AdelaideSATAC 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 Pearsons Overall 58 Reading 50 Listening 50 Speaking 50 Writing 50 Cambridge 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 Requirements
Tertiary Qualifications Bachelor degree or equivalent with a minimum GPA of 4.5. Advanced standing of 12 units may be granted to eligible applicants who have successfully completed the MicroMaster in Big Data program with a minimum overall score of 65 percent.
Australian Year 12 University level Maths IB or equivalent. International Qualifications University level Mathematics IB or equivalent
Fees and Scholarships
Choose your applicant type to view the relevant fees and scholarships information for this program.
I am a:
Annual tuition feesAustralian Full-fee place: $34,500
Annual tuition fees International student place: $40,000
These scholarships, as well as many others funded by industry and non-profit organisations, are available to potential and currently enrolled students.
Business Analyst, Business Data Analyst, Computer Scientist, Data Analyst
A Global Learning Experience is an integral component to your academic journey at The University of Adelaide. The university is committed to offering its students the opportunity to study overseas through a range of degrees offered via the Global Learning Office, including student exchange, study tours, short study degrees, internships and placements. There are many exciting opportunities in Europe, Asia, the Americas, Africa, and Oceania ranging from a few weeks to a full academic year.
To find Global Learning opportunities available in your study area click Global Experiences.
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.
Example Study Plan
Please refer to the ECMS website for a study plan to guide your enrolment http://www.ecms.adelaide.edu.au/current-students/enrolment/study-plans/
MASTER OF DATA SCIENCE Year 1 COMP SCI 7208 Programming & Computational Thinking for Data Science (6 units)
MATHS 7103 Probability and Statistics (3 units)
COMP SCI 7201 Algorithm & Data Structure Analysis (3 units)
COMP SCI 7209 Big Data Analysis & Project (3 units)
COMP SCI 7401 Introduction to Statistical Machine Learning (3 units)
Elective (6 units)
Master of Data Science Research Project Part A (6 units)
Master of Data Science Research Project Part B (6 units)
COMP SCI 7405 Research Methods in Software Engineering (3 units)
COMP SCI 7306 Mining Big Data (3 units)
COMP SCI 7094 Distributed Databases and Data (3 units)
Elective (3 uints)
Elective Choices COMP SCI 7059 Artificial Intelligence (3 units)
COMP SCI 7088 Systems Programming (3 units)
COMP SCI 7305 Parallel and Distributed Computing (3 units)
STATS 7004 Statistics Topic A (3 units)
STATS 7014 Statistics Topic B (3 units)
STATS 7016 Statistics Topic C (3 units)^
STATS 7059 Mathematical Statistics (3 units)
STATS 7054 Statistical Modelling (3 units)
COMP SCI 7007 Specialised Programming (3 units)
COMP SCI 7076 Distributed Systems (3 units)
STATS 7008 Statistics Topic D (3 units)
STATS 7069 Statistics Topic E (3 units)^
STATS 7070 Statistics Topic F (3 units)^
SSTATS 7056 Biostatistics (3 units)
STATS 7057 Sampling Theory and Practice (3 units)^
STATS 7058 Time Series (3 units)
STATS 7107 Statistical Modelling and Inference (3 units)
COMP SCI 7407 Advanced Algorithms (3 units)
^Check the course planner for course availability noting the availability of all courses is conditional on the availability of staff and facilities.
AssessmentResearch project, written assignments, practical work and/or examinations.
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Last updated: Monday, 5 Feb 2018