Master of Data Science

With their highly specialist knowledge, which is highly valued in this digital age, data scientists use vast amounts of data to spur innovation and change in a variety of sectors. From technology start-ups to multinational corporations, the Master of Data Science program teaches you how to investigate data and uncover its potential in order to come up with creative answers to pressing issues in industry, government, and science. You can pursue a Master of Data Science with a degree in science, engineering, the arts, or computing to acquire the data management, analytics, and processing abilities required in this rapidly expanding sector.

Entry Level 1 (96 points, 2 years full-time, 4 years part-time):

• An Australian bachelor's degree (or equivalent), not necessarily in IT, with a minimum WAM 60.

Entry Level 2 (72 points, 1.5 years full-time, 3 years part-time):

• An Australian bachelor's degree (or equivalent) in a cognate discipline relating to IT, or a business, engineering or science degree with an IT major including Python programming, databases, algorithms, computer architecture, operating systems and networks, and mathematics (including calculus, linear algebra and probability and statistics), with a minimum WAM 60.

Important Note:

• The pathway to Entry Level 1 or Entry Level 2 is subject to an internal assessment of the applicant's qualification to conform to the MQA Program Standards for Computing.

English Language Requirements:

• IELTS (Academic)/IELTS One Skill Retake (Academic)/IELTS Online:
  • Overall score: 6.5
  • Listening score: 6.0
  • Reading score: 6.0
  • Writing score: 6.0
  • Speaking score: 6.0
• TOEFL iBT/TOEFL iBT Paper Edition:
  • Total Score: 79
  • Listening score: 12
  • Reading score: 13
  • Writing score: 21
  • Speaking score: 18
• PTE Academic:
  • Overall score: 58
  • Listening score: 50
  • Reading score: 50
  • Writing score: 50
  • Speaking score: 50
• C1 Advanced or C2 Proficiency:
  • Overall score: 176
  • Listening score: 169
  • Reading score: 169
  • Writing score: 169
  • Speaking score: 169

PART A. FOUNDATIONS FOR ADVANCED DATA SCIENCE STUDIES:

• Introduction to databases
• Algorithms and programming foundations in Python
• Introduction to computer architecture and networks
• Mathematical foundations for data science

PART B. CORE MASTER’S STUDIES:

• Project management
• IT research methods
• Foundations of data science
• Data exploration and visualisation
• Data wrangling
• Statistical data modelling
• Data processing for big data
• Choose one of the following:
  • Machine learning
  • Malicious AI

PART C. ADVANCED PRACTICE:

• Industry experience: A program of coursework involving advanced study and an industry experience studio project.
• Master’s thesis: A research pathway including a thesis. (Recommended for those wishing to pursue a higher degree by research).