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University of Waikato

Hamilton , North Island, New Zealand, New Zealand

Master of Data Science

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

Campus Information

Hamilton campus

Our main campus is located in the vibrant, multicultural city of Hamilton, with outdoor activities, shopping malls and eateries only a short drive away. On campus, you鈥檒l find a new state-of-the-art Student Centre, sporting facilities, cafes and eateries, car parking, subsidised bus services and more.

Intakes

  • March
  • July

Application Processing Time in Days: 30

Application Process

More Information Required
30 Days
GTE/Possible Interview call from Institution
30 Days
Visa Process
10 Days

Minimum English Language Requirements

English Level Description IELTS (1.0 -9.0) TOEFL IBT (0-120) TOEFL CBT (0-300) PTE (10-90)
Expert 9 120 297-300 86-90
Very Good 8.5 115-119 280-293 83-86
Very Good 8 110-114 270-280 79-83
Good 7.5 102-109 253-267 73-79
Good 7 94-101 240-253 65-73
Competent 6.5 79-93 213-233 58-65
Competent 6 60-78 170-210 50-58
Modest 5.5 46-59 133-210 43-50
Modest 5 35-45 107-133 36-43
Limited 4 32-34 97-103 30-36
Extremely Limited < 4 < 31 < 93 < 30

Job Opportunity Potential

  • Big data engineer
  • Business analyst
  • Data analyst
  • Data Scientist
  • GIS Analyst

PSW Opportunity

Level 7 (Bachelor’s degree)

  • Duration: Equal to length of study (typically up to 3 years)
  • Requirement: minimum 30 weeks full time study in NZ

Level 7 (Graduate Diploma)
Eligible for PSWV
Conditions:

  • Must also hold a Bachelor’s degree (NZ or overseas)
  • Duration: Up to length of study (typically 1 year)

Level 8 (Postgraduate Diploma)

  • Duration: Equal to length of study, OR
  • Up to 3 years in some cases (if part of higher qualification pathway)

Level 9 and 10 (Master’s degree and Doctoral degree)

  • Duration: 3 years
  • Condition: Must study at least 30 weeks in New Zealand

- Most eligible international students can work up to 25 hours per week during study and full-time during scheduled breaks, only if their student visa includes work rights.

- Foundation, pathway and short courses have different rules.

- Not allowed for part time students.

Admission Requirement / Eligibility Criteria

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.

 

For More Information Please Contact To Our PSA Counselor.

Disclaimer: GR updates the information on this page from time to time; however, there may have been more recent updates. Please refer to the university website for the latest information.