Master of Data Science specialisation in Data Science - Taught 240

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The last decade has seen an explosion in the amount of data available. It has evolved into the most important asset for many companies and people. Big data is ubiquitous, but to extract information, individuals require the ability to both manage and analyse the data. This ability to turn data into information, knowledge and innovative products often separates success from failure.

Data scientists have the skill set to drive innovation and affect the success of start-ups, established businesses and organisations, governments and science projects, as well as media, broadcasting and cultural events.

The Data Science major will provide initial preparation for students wishing to pursue a career in this area. It ties together courses from Computer Science, Statistics and Mathematics to provide the necessary background and training.

The Department of Statistics is the birthplace of the R Project. Founded in 1996 by Associate Professors Robert Gentleman and Ross Ihaka. R is a programming language and environment for statistical computing and graphics. It is taught around the world and is used by Ivy League universities, Google, Uber, and many more organisations.

The Master of Data Science is an advanced programme and takes the skills learned from your undergraduate degree in Data Science to the next level. You will be taught how to apply state-of-the-art techniques to real-world problems, drawing from computer science and statistics.

On the world stage, Data Science is a rapidly growing field with an unmet demand for suitably qualified graduates.
- Data analyst
- Data scientist
- Database administrator
- Developer
- Information officer
- Insight manager
- Statistician

Complete 240 points comprising:

45 points for all Compulsory Courses, and
At least 15 points from Statistics Courses, and
60 points from Group 1 Elective Courses, and
At least 15 points from Group 2 Elective Courses, and
At least 15 points from Group 3 Elective Courses, and
0 to 45 points from Group 4 Elective Courses, and
15 points for all Statistical Computing Skills for Professional Data Scientists Course, and
Either:
30 points for all Research Project - 1 Semester, or
30 points for all Research Project - 2 Semesters

Compulsory Courses

Complete 45 points for ALL of the following:

COMPSCI 752 - Big Data Management (15 points)

COMPSCI 760 - Advanced Topics in Machine Learning (15 points)

STATS 769 - Advanced Data Science Practice (15 points)

Statistics Courses

Complete at least 15 points from the following:

STATS 762 - Regression for Data Science (15 points)

STATS 763 - Advanced Regression Methodology (15 points)

Group 1 Elective Courses

Complete exactly 60 points from the following:

COMPSCI 717 - Fundamentals of Algorithmics (30 points)

COMPSCI 751 - Advanced Topics in Database Systems (15 points)

COMPSCI 762 - Foundations of Machine Learning (15 points)

DATASCI 709 - Data Management (30 points)

STATS 707 - Computational Introduction to Statistics (15 points)

STATS 709 - Predictive Modelling (30 points)

STATS 765 - Statistical Learning for Data Science (15 points)

STATS 782 - Statistical Computing (15 points)

Up to 60 points may be substituted from other 700 level courses offered at this University approved by the Programme Director.

Group 2 Elective Courses

Complete at least 15 points from the following:

STATS 705 - Topics in Official Statistics (15 points)

STATS 730 - Statistical Inference - Level 9 (15 points)

STATS 731 - Bayesian Inference (15 points)

STATS 763 - Advanced Regression Methodology (15 points)

STATS 767 - Foundations of Applied Multivariate Analysis (15 points)

STATS 784 - Statistical Data Mining (15 points)

STATS 786 - Time Series Forecasting for Data Science (15 points)

STATS 787 - Data Visualisation (15 points)

Group 3 Elective Courses

Complete at least 15 points from the following:

COMPSCI 711 - Parallel and Distributed Computing (15 points)

COMPSCI 720 - Advanced Design and Analysis of Algorithms (15 points)

COMPSCI 734 - Web, Mobile and Enterprise Computing (15 points)

COMPSCI 750 - Computational Complexity (15 points)

COMPSCI 753 - Algorithms for Massive Data (15 points)

Group 4 Elective Courses

Complete 0 to 45 points from the following:

COMPSCI 705 - Advanced Topics in Human Computer Interaction (15 points)

COMPSCI 715 - Advanced Computer Graphics (15 points)

COMPSCI 732 - Software Tools and Techniques (15 points)

COMPSCI 761 - Advanced Topics in Artificial Intelligence (15 points)

COMPSCI 765 - Modelling Minds (15 points)

COMPSCI 767 - Intelligent Software Agents (15 points)

DIGIHLTH 701 - Principles of Digital Health (15 points)

DIGIHLTH 702 - Health Knowledge Management (15 points)

DIGIHLTH 703 - New Zealand Health Data Landscape (15 points)

DIGIHLTH 704 - Artificial Intelligence in Healthcare (15 points)

DIGIHLTH 705 - Digital Health Design and Evaluation (15 points)

DIGIHLTH 706 - Health Data Analytics (15 points)

ENGSCI 711 - Advanced Mathematical Modelling (15 points)

ENGSCI 755 - Decision Making in Engineering (15 points)

ENGSCI 760 - Algorithms for Optimisation (15 points)

ENGSCI 761 - Integer and Multi-objective Optimisation (15 points)

ENGSCI 763 - Advanced Simulation and Stochastic Optimisation (15 points)

ENGSCI 765 - Advanced Optimisation in Operations Research (15 points)

INFOSYS 700 - Digital Innovation (15 points)

INFOSYS 720 - Information Systems Research - Level 9 (15 points)

INFOSYS 722 - Data Mining and Big Data (15 points)

INFOSYS 757 - Project Management and Outsourcing (15 points)

MATHS 715 - Graph Theory and Combinatorics (15 points)

MATHS 761 - Dynamical Systems (15 points)

MATHS 765 - Mathematical Modelling (15 points)

MATHS 766 - Inverse Problems (15 points)

MATHS 767 - Inverse Problems and Stochastic Differential Equations (15 points)

MATHS 769 - Stochastic Differential and Difference Equations (15 points)

OPSMGT 741 - System Dynamics and Complex Modelling (15 points)

OPSMGT 752 - Modelling Methods in Operations Management (15 points)

OPSMGT 766 - Fundamentals of Supply Chain Coordination (15 points)

SCIENT 701 - Accounting and Finance for Scientists (15 points)

STATS 710 - Probability Theory - Level 9 (15 points)

STATS 726 - Time Series (15 points)

STATS 732 - Foundations of Statistical Inference (15 points)

STATS 770 - Introduction to Medical Statistics (15 points)

STATS 780 - Statistical Consulting (15 points)

COMPSCI 717 - Fundamentals of Algorithmics (30 points)

COMPSCI 751 - Advanced Topics in Database Systems (15 points)

COMPSCI 762 - Foundations of Machine Learning (15 points)

DATASCI 709 - Data Management (30 points)

STATS 707 - Computational Introduction to Statistics (15 points)

STATS 709 - Predictive Modelling (30 points)

STATS 765 - Statistical Learning for Data Science (15 points)

STATS 782 - Statistical Computing (15 points)

STATS 705 - Topics in Official Statistics (15 points)

STATS 730 - Statistical Inference - Level 9 (15 points)

STATS 731 - Bayesian Inference (15 points)

STATS 763 - Advanced Regression Methodology (15 points)

STATS 767 - Foundations of Applied Multivariate Analysis (15 points)

STATS 784 - Statistical Data Mining (15 points)

STATS 786 - Time Series Forecasting for Data Science (15 points)

STATS 787 - Data Visualisation (15 points)

COMPSCI 711 - Parallel and Distributed Computing (15 points)

COMPSCI 720 - Advanced Design and Analysis of Algorithms (15 points)

COMPSCI 734 - Web, Mobile and Enterprise Computing (15 points)

COMPSCI 750 - Computational Complexity (15 points)

COMPSCI 753 - Algorithms for Massive Data (15 points)

Up to 45 points may be substituted from other 700 level courses offered at this University approved by the Programme Director.

Statistical Computing Skills for Professional Data Scientists Course

Complete 15 points for ALL of the following:

DATASCI 779 - Statistical Computing Skills for Professional Data Scientists - Level 9 (15 points)

Research Project - 1 Semester

Complete 30 points for ALL of the following:

DATASCI 791 - Research Project - Level 9 (30 points)

Research Project - 2 Semesters

Complete 30 points for ALL of the following:

DATASCI 791A - Research Project - Level 9 (15 points)

DATASCI 791B - Research Project - Level 9 (15 points)