Master of Data Science (MDataSc)
Information valid for students commencing 2020
Duration
1.5 Years full-time (or part-time equivalent)
Commencing 2020
Semester 1 (24 Feb, 2020)
Semester 2 (03 Aug, 2020)
Program level
Postgraduate Coursework
Units
24
Program code
5659
Faculty
Engineering, Architecture & Information Technology
Teaching Location
St Lucia
Delivery mode
Flexible Delivery, Internal
Entry requirements
AQF level
AQF level 9
Fees for Australian students
When you enrol each semester, mySI-net will calculate your fees. An invoice with the fees for the current semester will generally be available for viewing on mySI-net overnight.
If the invoice for a given semester or teaching period is not yet available, you can use the Fees Schedules to estimate your fees. Please see the course list if you are unsure which courses you can do in your program.
Fees for all students are reviewed annually in accordance with the University's Student Fees Policy, and may increase from 1 January each year.
If you are a prospective student, or if you haven't yet commenced your program, please see the Study at UQ website for fee information.
How to Apply
Applications must be lodged via the Online Application Form.
Closing Date
To commence study in Semester 2 - June 30 of the year of commencement.
To commence study in semester 1 - November 30 of the previous year.
Enquiries for Australian students
Faculty of Engineering, Architecture and Information Technology
Email: enquiries@eait.uq.edu.au
Phone: 07 3365 4777
Why study the Master of Data Science?
There is a significant and ongoing growth in the demand for Data Scientists globally. Data Science is an exciting new area of study that is applicable in a large number of industry sectors such as health, energy, finance, manufacturing, as well as in government. The Data Science program at The University of Queensland will be the first in Australia to offer an advanced level of computing, statistics, mathematics and business knowledge applied in industry, government, social and scientific contexts and balanced with essential attributes relevant to data science including the ethical use of data, legal considerations for data science, business communication, hands-on experience with relevant big data tools and technologies, and creative and disruptive thinking applied to complex problems. Graduates from this program will be well-equipped to tackle complex data science challenges and play a leading role in the future development of data science solutions globally.
