Master of Data Science
Develop your skills to succeed in a data-driven world. Our Master of Data Science equips you with a foundation of practical analytics and machine learning skills, whatever your background. Learn to turn data into insight across a wide variety of fields.
180 points, 1 - 1.5 years
Hamilton
Trimester A (March) and Trimester B (July) - to be confirmed
Why study the Master of Data Science?
In today’s world of data-driven decision making, the ability to analyse and interpret data is essential across almost every industry.
Competence in data analytics, computing and machine learning enables professionals to uncover insights, make informed decisions, and drive innovation. As organisations increasingly rely on data to guide strategy, these skills are in high demand—not just in tech, but also in business, health, education, science, and more.
This programme is designed both for students who may not have an undergraduate background in data analytics, computing and artificial intelligence but are wanting to upskill in these areas to complement their existing knowledge, and for students who have the undergraduate background and want to develop their knowledge further.
The Master of Data Science can be completed without endorsement, or with one of the following:
- Artificial intelligence
- Business analytics
- Geographic information systems
- Health analytics
- Mathematics
- Statistics modelling
Career Opportunities
- Big data engineer
- Business analyst
- Data analyst
- Data Scientist
- GIS Analyst
180 points, 1 - 1.5 years
Hamilton
Trimester A (March) and Trimester B (July) - to be confirmed
Degree information
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Plan your study -
Subjects Choose an endorsement
Browse available subjects and choose one for more information.
Browse MDSc subjects Browse available subjects and choose one for more information
An endorsement requires passing 75 points from the prescribed papers.
The degree may be completed without an endorsement.
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Entry Requirements Entry to B trimester requires students to have a background in coding and statistics and is at the University's discretion. Students entering in B trimester will still be required to complete the full 180 point programme, and need to select any two additional papers from any papers listed for Data Science (see list under the degree planner for the MDSc without endorsement) to replace DATAX500 and DATAX503.
Endorsements in AI and Mathematics will require prior tertiary study in numeracy and/or programming. These will be assessed on a case-by-case basis.
Students selecting no endorsement, Business Analytics, GIS or Health Analytics will be accepted with the equivalent of a B grade in the final year from any bachelor's degree.
An endorsement in Business Analytics is only available for students entering in A trimester.
Entry to B trimester requires students to have a background in coding and statistics and is at the University's discretion. Students entering in B trimester will still be required to complete the full 180 point programme, and need to select any two additional papers from any papers listed for Data Science (see list under the degree planner for the MDSc without endorsement) to replace DATAX500 and DATAX503.
Endorsements in AI and Mathematics will require prior tertiary study in numeracy and/or programming. These will be assessed on a case-by-case basis.
Students selecting no endorsement, Business Analytics, GIS or Health Analytics will be accepted with the equivalent of a B grade in the final year from any bachelor's degree.
An endorsement in Business Analytics is only available for students entering in A trimester.
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Fees and scholarships Estimated fees
$15,400 per year
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Domestic tuition fees
Approximate annual tuition fees and costs for domestic students enrolled in one year of full-time study.
Domestic tuition costs -
Scholarships
Visit our Scholarship finder for more information about possible scholarships.
Scholarships Finder
Relevant as of 18 November 2025.
All amounts are in New Zealand Dollars (NZD). Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment. Please see the Table of Fees and Charges for more information. You will be sent an enrolment agreement which will confirm your fees. View information about fees free study.
Estimated fees
$68,370 (180 points)
-
International tuition fees
Approximate annual tuition fees and costs for international students enrolled in one year of full-time study.
International tuition costs -
Scholarships
Visit our Scholarship finder for more information about possible scholarships.
Scholarships Finder
Relevant as of 18 November 2025.
All amounts are in New Zealand Dollars (NZD). Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment. Please see the Table of Fees and Charges for more information. You will be sent an enrolment agreement which will confirm your fees.
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Graduate outcomes Graduates of the Master of Data Science will be able to:
- Write computer code in a variety of environments for use in data science.
- Apply advanced statistical modelling and inference to data.
- Use artificial intelligence and machine learning models to gain insights from data.
- Use data science in a variety of disciplines.
- Manager and use large databases and data warehouses.
- Create dashboards for the reporting of data.
- Communicate data to non-technical people.
- Have knowledge of indigenous data sovereignty.
- Apply appropriate processes for handling and storage of indigenous data.
- Undertake independent research in data science.
In addition to achieving the broader outcomes and attributes of the Master of Data Science, a graduate of the following endorsements will be able to:
Artificial intelligence
- Demonstrate knowledge and understanding of advance machine learning and artificial intelligence tools.
- Use advanced machine learning and artificial intelligence models to analyse complex data.
Business analytics
- Apply data science knowledge and tools in a business context.
Geographic information systems
- Demonstrate knowledge of Geographic information systems software.
- Use Geographic information systems to analyse spatial data.
Health analytics
- Apply data science knowledge and tools in a health analytics context.
Mathematics
- Use advanced computational methods in data science.
- Apply mathematical constructs to analyse certain types of structured data.
Statistical modelling
- Demonstrate understanding of advanced statistical modelling methods and the supporting mathematical theory.
- Use advance statistical methods to analyse complex data.
Browse available subjects and choose one for more information
An endorsement requires passing 75 points from the prescribed papers.
The degree may be completed without an endorsement.
Entry to B trimester requires students to have a background in coding and statistics and is at the University's discretion. Students entering in B trimester will still be required to complete the full 180 point programme, and need to select any two additional papers from any papers listed for Data Science (see list under the degree planner for the MDSc without endorsement) to replace DATAX500 and DATAX503.
Endorsements in AI and Mathematics will require prior tertiary study in numeracy and/or programming. These will be assessed on a case-by-case basis.
Students selecting no endorsement, Business Analytics, GIS or Health Analytics will be accepted with the equivalent of a B grade in the final year from any bachelor's degree.
An endorsement in Business Analytics is only available for students entering in A trimester.
Entry to B trimester requires students to have a background in coding and statistics and is at the University's discretion. Students entering in B trimester will still be required to complete the full 180 point programme, and need to select any two additional papers from any papers listed for Data Science (see list under the degree planner for the MDSc without endorsement) to replace DATAX500 and DATAX503.
Endorsements in AI and Mathematics will require prior tertiary study in numeracy and/or programming. These will be assessed on a case-by-case basis.
Students selecting no endorsement, Business Analytics, GIS or Health Analytics will be accepted with the equivalent of a B grade in the final year from any bachelor's degree.
An endorsement in Business Analytics is only available for students entering in A trimester.
Estimated fees
$15,400 per year
-
Domestic tuition fees
Approximate annual tuition fees and costs for domestic students enrolled in one year of full-time study.
Domestic tuition costs -
Scholarships
Visit our Scholarship finder for more information about possible scholarships.
Scholarships Finder
Relevant as of 18 November 2025.
All amounts are in New Zealand Dollars (NZD). Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment. Please see the Table of Fees and Charges for more information. You will be sent an enrolment agreement which will confirm your fees. View information about fees free study.
Estimated fees
$68,370 (180 points)
-
International tuition fees
Approximate annual tuition fees and costs for international students enrolled in one year of full-time study.
International tuition costs -
Scholarships
Visit our Scholarship finder for more information about possible scholarships.
Scholarships Finder
Relevant as of 18 November 2025.
All amounts are in New Zealand Dollars (NZD). Tuition fees shown are indicative only and may change. There are additional fees and charges related to enrolment. Please see the Table of Fees and Charges for more information. You will be sent an enrolment agreement which will confirm your fees.
Graduates of the Master of Data Science will be able to:
- Write computer code in a variety of environments for use in data science.
- Apply advanced statistical modelling and inference to data.
- Use artificial intelligence and machine learning models to gain insights from data.
- Use data science in a variety of disciplines.
- Manager and use large databases and data warehouses.
- Create dashboards for the reporting of data.
- Communicate data to non-technical people.
- Have knowledge of indigenous data sovereignty.
- Apply appropriate processes for handling and storage of indigenous data.
- Undertake independent research in data science.
In addition to achieving the broader outcomes and attributes of the Master of Data Science, a graduate of the following endorsements will be able to:
Artificial intelligence
- Demonstrate knowledge and understanding of advance machine learning and artificial intelligence tools.
- Use advanced machine learning and artificial intelligence models to analyse complex data.
Business analytics
- Apply data science knowledge and tools in a business context.
Geographic information systems
- Demonstrate knowledge of Geographic information systems software.
- Use Geographic information systems to analyse spatial data.
Health analytics
- Apply data science knowledge and tools in a health analytics context.
Mathematics
- Use advanced computational methods in data science.
- Apply mathematical constructs to analyse certain types of structured data.
Statistical modelling
- Demonstrate understanding of advanced statistical modelling methods and the supporting mathematical theory.
- Use advance statistical methods to analyse complex data.