The Master of Science (Applied) is the new name for the former Master of Applied Science degree.
Students intending to begin study in 2027 should apply for the Master of Science (Applied).
Programme requirements may have changed for some subjects.
Study the Master of Science (Applied) (MSc(Applied)) in Data Science
Build technical expertise across computing and statistics
At Otago, you will study Data Science across the School of Computing and the Department of Mathematics and Statistics, combining expertise from multiple disciplines. The programme blends advanced technical learning with applied study, including machine learning, large scale data management, and high-performance computing. You will also explore ethical and social questions connected to artificial intelligence, data use, and Māori and Indigenous data sovereignty in Aotearoa New Zealand.
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If this is the qualification for you, get started with your application today.
Programme details
Regulations for the Degree of Master of Science (Applied) (MSc (Applied))
Admission to the Programme
- Admission to the programme shall be subject to the approval of the Pro-Vice-Chancellor (Sciences).
- Every applicant must have been awarded a bachelor's degree with an average grade of at least B in the relevant 300-level papers or have alternative qualifications or experience acceptable to the Pro-Vice-Chancellor (Sciences).
Subjects of Study
The degree may be awarded in any of the subjects for the degree of Master of Science (Applied) listed in Science Schedule D. With the approval of the Pro-Vice-Chancellor (Sciences), the degree may be awarded in a subject not listed in Science Schedule D.
Structure of the Programme
- The programme of study:
- shall consist of approved papers at 400-level or higher worth at least 180 points, selected from the papers specified in Science Schedule D for the Master of Science (Applied) subject concerned, and must include at least 40 points from SCNC 501, SCNC 503, SCNC 597, SCNC 598, or approved 500 level papers.
- shall normally include papers from more than one subject and at least one of the approved 400-level papers that shall be amongst the first papers taken in the programme of study.
- may, with the approval of the Head of Department or Course Director concerned, include papers substituted worth up to 60 points from 400- and 500-level papers other than those specified in the subject requirements.
- A candidate who has completed the requirements for the Postgraduate Certificate or the Postgraduate Diploma in Applied Science shall be exempted from those papers in the programme for the degree which have previously been passed for the certificate or diploma.
- The programme of study:
Duration of the Programme
The programme shall normally be completed within 18 months and not less than one year (12 months) by full-time candidates, or by part-time candidates over more than 18 months.
Examination
- Every report for SCNC 597 or SCNC 598, shall be assessed by at least two examiners and be subject to the overview of the external assessor for the supervising department.
- The candidate's supervisor for any of SCNC 597 or SCNC 598 shall not be an examiner but may make a report on the work of the candidate to the Course Director concerned
Level of Award of the Degree
The degree may be awarded with distinction or with credit.
Variations
The Pro-Vice-Chancellor (Sciences) may in exceptional circumstances approve a course of study which does not comply with these regulations.
Note: The due date for applications for first enrolment in the programme is 10 December. Late applications will be considered.
Explore more in Data Science
Learn where this subject can take you and discover the full range of study options, from undergraduate programmes to postgraduate pathways.
Career opportunities
A Postgraduate degree in Data Science is valued wherever organisations need to generate insight, build predictive models, or support evidence-informed decision-making. Graduates may contribute to technical, analytical, research, or leadership-focused work across a wide range of sectors:
- Data science and analytics, generating insight from complex data to inform decisions.
- Machine learning and artificial intelligence, developing predictive models and intelligent data applications.
- Data engineering and management.
- Research and innovation, investigating new methods and applications across disciplines.
- Policy and strategic analysis, applying evidence to planning, evaluation, and decision-making
Apply advanced methods to complex data challenges
This qualification encourages you to think critically about how data is collected, analysed, interpreted, and applied. Alongside advanced technical study, you will engage with ethical, social, and interdisciplinary questions connected to artificial intelligence, machine learning, and large-scale data systems.
Through applied projects and independent study, you will learn to approach complex challenges thoughtfully, communicate insights clearly, and work confidently across a range of data rich contexts.
You will also have the choice of advanced papers that enable you to work with masters' students from across the Sciences, tackling real-world issues that don't have simple solutions to build experience in interdisciplinary collaboration.
