Why Study / Key Benefits

• Develops practical analytics and machine-learning skills for a data-driven economy.
• Suitable for students from relevant and some non-traditional backgrounds who want to build or extend their data-science capability.
• Combines data analysis, programming, statistical modelling, machine learning and data-management skills.
• Allows students to specialise through six optional endorsements.
• Skills can be applied across business, health, education, science, government and other sectors.
• Students develop the ability to communicate data and analytical findings to non-technical audiences.
• The programme includes learning about indigenous data sovereignty and appropriate handling and storage of indigenous data.
• Students develop the ability to undertake independent research in data science.
• Waikato's School of Computing & Mathematical Sciences provides postgraduate research opportunities in areas including artificial intelligence, machine learning, data security and related computing fields.

Programme Structure and Subjects / Topics

The 2027 Data Science Subject Regulations require students completing the MDSc without an endorsement to complete 180 points of Data Science papers at 500 level, including:

• COMPX570 – Data Management
• DATAX500 – Data Analysis for Researchers
• DATAX501 – Modelling for Data Science
• DATAX503 – Programming for Data Science
• DATAX504 – Practical Machine Learning for Data Analysis
• A further 45 points selected from specified Data Science-related papers.

Examples of the core subjects include:

• Data Analysis for Researchers: quantitative research data-analysis skills and tools, particularly for postgraduate students with limited previous data-analysis experience.
• Modelling for Data Science: general and generalised linear models, statistical learning, classification methods and models.
• Programming for Data Science: programming using languages such as MATLAB and Python, providing the programming foundation needed for data science.
• Data Management: management of data within large data ecosystems and associated ethical considerations.
• Practical Machine Learning for Data Analysis: application of machine-learning methods to real-world data-analysis problems.

Other 500-level options available within the Data Science subject regulations include:

• Agri-Food Analytics
• Technology in Biomedicine
• Managing Big Data
• Decision Making with Data Analytics
• Dissertation
• Advanced Statistical Modelling
• Mathematical Statistics
• Economics for Business
• Time Series Econometrics for Macroeconomics and Finance
• Programming Tools and Techniques
• Preparation for Research in Computer Science. 

Disciplines / Specialisations

The MDSc can be completed without an endorsement or with one of six endorsements:

1. Artificial Intelligence
2. Business Analytics
3. Geographic Information Systems
4. Health Analytics
5. Mathematics
6. Statistical Modelling.

The 2027 endorsement requirements are:

• Artificial Intelligence: 75 points including COMPX520 and 30 points from COMPX521, COMPX523 or COMPX525.
• Business Analytics: 75 points including MNGMT562 and MNGMT563, plus 30 points from specified business/economics analytics papers.
• Geographic Information Systems: 75 points including GEOGY523 plus 30 points from specified environmental/geography papers.
• Health Analytics: 75 points including HELTH597 plus 30 points from specified biomedical/health/computing papers.
• Mathematics: 75 points including MATHS520 plus 30 points from specified mathematics/computing papers.
• Statistical Modelling: 75 points including DATAX520 plus 30 points from specified advanced statistics papers.

Programme Highlights

• 180-point Level 9 master's qualification.
• 1–1.5-year completion period.
• Hamilton campus.
• March and July intakes.
• Strong focus on practical data analytics and machine learning.
• Covers programming, statistical modelling, data management and artificial intelligence.
• Six optional specialist endorsements.
• Suitable for students wanting either broad data-science training or a defined specialisation.
• Includes indigenous data sovereignty and responsible data handling.
• Develops independent research capability.
• Can lead to careers across technology, business, health, science, education and other data-intensive sectors.

Career Outcomes

The University specifically lists the following career opportunities:

• Big data engineer
• Business analyst
• Data analyst
• Data scientist
• GIS analyst.

Depending on the chosen endorsement, graduates can also develop capabilities relevant to:

• Artificial intelligence and machine learning
• Business intelligence and analytics
• Spatial/GIS analysis
• Health data analysis
• Statistical modelling
• Mathematical and computational data analysis.

Latest Updates / Special Requirements

• The current programme is listed as 180 points with a 1–1.5-year duration and March/July intakes.
• The 2027 Data Science Subject Regulations are now available and should be used when planning a 2027 study programme.
• The degree can be completed without an endorsement or with one of six endorsements.
• An endorsement requires 75 points from the relevant prescribed papers.
• Some endorsement combinations have specific paper prerequisites.
• The University may vary or waive programme regulations in individual cases through the appropriate authority.
• Students progressing from the Waikato College Pre-Masters pathway into some MDSc endorsements may require Division approval. The College specifically notes that progression into an MDSc endorsement in Trimester B, and into Mathematics or Artificial Intelligence in A or B, may require approval that can take up to three weeks.
• The programme is taught in Hamilton, and current core 2027 papers are listed as in-person.
• Students completing a dissertation must satisfy the applicable research/dissertation requirements. For example, DATAX520 is a 45-point Level 500 dissertation running from 1 March 2027 to 27 February 2028.

International Student Visa Requirements

For a standard offshore international student coming to New Zealand to study the MDSc, the relevant visa will generally be the Fee Paying Student Visa.

Immigration New Zealand requires applicants to:

• Have an offer of place from an approved education provider.
• Have sufficient funds to pay tuition fees or an acceptable scholarship/funding arrangement.
• Have sufficient funds for living expenses or an acceptable sponsor.
• Be in good health.
• Be of good character.
• Have a genuine reason for studying in New Zealand.
• Demonstrate that they can leave New Zealand at the end of their stay.
• Hold appropriate medical and travel insurance.