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Master of Data Science

Course overview

Qualification Master's Degree
Study mode Full-time, Part-time
Duration 18 months
Intakes July, Mar
Tuition (Local students) $ 9,200
Tuition (International students) $ 43,662


This programme (MDataSci) will equip students with a unique combination of skills in data science, so that they will be able to understand, process and manage data effectively. Students will also learn to be critical, reflective practitioners, giving them an edge in the industry.



For admission requirements and intakes for each individual course/programme please refer to course details.

Tuition and application fees

$ 6,133 per year
Local students
$ 29,108 per year
International students

Estimated cost as reported by the Institution.

Every effort has been made to ensure that information contained in this website is correct. Changes to any aspects of the programmes may be made from time to time due to unforeseeable circumstances beyond our control and the Institution and EasyUni reserve the right to make amendments to any information contained in this website without prior notice. The Institution and EasyUni accept no liability for any loss or damage arising from any use or misuse of or reliance on any information contained in this website.

Entry Requirements

Minimum requirements listed here are the likely grades required and do not guarantee entry. The university assesses each application individually and applicants may require a higher grade to be offered a place.

University of Auckland

Completed one of the following with GPA of 4.5 (Taught 180 points):

  • A Bachelor of Science in Data Science from this University, with a Grade Point Average of 4.5 or higher in 75 points above Stage II
  • A Bachelor of Science with a double major in Computer Science and Statistics from this university, with a Grade Point Average of 4.5 or higher in 75 points above Stage II

Another tertiary institution

  • An undergraduate degree from a recognised university (or similar institution) with GPE of 4.5 in a relevant discipline (Taught 180 points)

English language requirements

  • IELTS Academic Score: 6.5 with no bands less than 6.0


60 points:

  • COMPSCI 752 Web Data Management
  • COMPSCI 760 Datamining and Machine Learning
  • STATS 763 Advanced Regression Methodology
  • STATS 769 Advanced Data Science Practice

At least 15 points from:

  • STATS 705 Topics in Official Statistics
  • STATS 730 Statistical Inference
  • STATS 783 Simulation and Monte Carlo Methods
  • STATS 784 Statistical Data Mining
  • STATS 787 Topics in Statistical Computing

At least 15 points:

  • COMPSCI 711 Parallel and Distributed Computing
  • COMPSCI 720 Advanced Design and Analysis of Algorithms
  • COMPSCI 734 Web, Mobile and Enterprise Computing
  • COMPSCI 750 Computational Complexity
  • COMPSCI 753 Uncertainty in Data

Up to 45 points from:

  • COMPSCI 705 Advanced Topics in Human Computer Interaction
  • COMPSCI 715 Advanced Computer Graphics
  • COMPSCI 732 Software Tools and Techniques
  • COMPSCI 761 Advanced Topics in Artificial Intelligence
  • COMPSCI 765 Interactive Cognitive Systems
  • COMPSCI 767 Intelligent Software Agents
  • ENGSCI 711 Advanced Mathematical Modelling
  • ENGSCI 755 Decision Making in Engineering
  • ENGSCI 760 Algorithms for Optimisation
  • ENGSCI 761 Integer and Multi-objective Optimisation
  • ENGSCI 762 Scheduling and Optimisation in Decision Making
  • ENGSCI 763 Advanced Simulation and Stochastic Optimisation
  • ENGSCI 768 Advanced Operations Research and Analytics
  • HLTHINFO 723 Health Knowledge Management
  • HLTHINFO 728 Principles of Health Informatics
  • HLTHINFO 730 Healthcare Decision Support Systems
  • INFOSYS 700 Digital Innovation
  • INFOSYS 720 Information Systems Research
  • INFOSYS 722 Data Mining and Big Data
  • INFOSYS 737 Adaptive Enterprise Systems
  • INFOSYS 740 System Dynamics and Complex Modelling
  • MATHS 715 Graph Theory and Combinatorics
  • MATHS 761 Dynamical Systems
  • MATHS 765 Mathematical Modelling
  • MATHS 766 Inverse Problems
  • MATHS 769 Stochastic Differential and Difference Equations
  • MATHS 770 Advanced Numerical Analysis
  • OPSMGT 752 Research Methods – Modelling
  • OPSMGT 757 Project Management
  • OPSMGT 760 Advanced Operations Systems
  • OPSMGT 766 Fundamentals of Supply Chain Coordination
  • POPLHLTH 704 Undertaking Qualitative Health Research
  • SCIENT 701 Accounting and Finance for Scientists
  • SCIENT 702 Marketing for Scientific and Technical Personnel
  • SCIENT 705 Research Commercialisation
  • STATS 701 Advanced SAS Programing
  • STATS 710 Probability Theory
  • STATS 726 Time Series
  • STATS 731 Bayesian Inference
  • STATS 770 Introduction to Medical Statistics
  • STATS 779 Professional Skills for Statisticians
  • STATS 780 Statistical Consulting
  • Other 700-level courses approved by the programme director

45 points:

  • DATASCI 792, 792a, 792b Dissertation

Maximum 6 courses for comparison!