Last Updated on July 31, 2023 by Oluwajuwon Alvina
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Interpret the rapidly changing world
Fifteen years ago, the role of data scientist was unheard of. Today, it’s an established role in business and government departments around the world. The nature of the role is constantly shifting as data sources, software tools, and techniques change. Equip yourself with the skills and knowledge to move and adapt to these changes.
Our graduates leave with an advanced understanding of techniques in data science, including machine learning and statistical methods and their uses in the world of big data. You will be able to critically analyse data requirements and sources in a variety of areas of application from the sciences, humanities, and social sciences to business and government.
Study Data Science
Master of Data Science
Kelburn campus, Wellington
Coursework, practicum, and research project
- 2022, Trimester 1: Apply by 20 Jan 2022 to start studying 28 Feb 2022
Estimated domestic fees for 2021
NZ$9,996 per year
A Bachelor’s degree with a major in Data Science, Computer Science, or Statistics, with an average grade of B+ or better in courses in those subjects. Candidates with a major in Data Science or a double major in Computer Science and Statistics may be exempted Part 1 (60 points) and can complete the degree in 3 trimesters (12 months).
Contribute to society
Data Science can assist equitable social and economic outcomes through the interpretation and dissemination of information, enabling communities to learn about themselves and others.
You’ll learn about the unique characteristics of working with data collected by, for, and about Māori, and how the principles of the Treaty of Waitangi apply: in particular, the considerations of Māori sovereignty in data collection, transfer, storage, and publication.
You have to remember the people behind it and what you’re doing it for. There’s always a story behind the data—it’s not just numbers.
Data Scientist at Dragonfly Data Science
Gain practical experience
Demand for data scientists in the commercial and state sectors is rapidly growing, and the role of data scientist has been consistently ranked among the top jobs of recent years.
The MDataSc has a professional focus and involves you completing a five-week work placement with one of our industry partners. These partners include a range of data science consultancies, government departments and agencies, and private companies. Here, you will have the opportunity to apply what you have learned to a professional environment, developing your practical competence and honing your professional skills.
The practicum placement allowed me to gain real-world experience and apply my studies to a project that was relevant at the time.
Junior Data Scientist at Spotlight Reporting
The Master’s programme is grounded in academic staff research expertise in the areas of statistics, data analysis, and machine learning. During your studies you’ll undertake a research project in a real-world setting and gain valuable experience working alongside experts in the Wellington Faculties of Science and Engineering.
The 240-point MDataSc comprises two parts.
In Part 1 (60 points), you will take courses that address fundamental techniques of data science, statistical methods, and machine learning.
Part 2 (180 points) includes a compulsory core of statistical methods and computational techniques; a research component made up of a research preparation course and an individual research project; and a five-week workplace practicum.
Course assessments include a combination of assignments, group work projects, oral presentations, a written research project report, term tests, written examinations, workplace reports, and self-reflections.
Find out more about the full range of postgraduate qualifications in the area of Data Science.
Find out more about the full range of postgraduate qualifications in the area of Data Science.Postgraduate Data Science
You can look for other scholarships based on your level of study, subject area, and background.
Requirements for domestic students who studied in ‐ Choose the country of last study ‐AfghanistanAlbaniaAlgeriaAmerican SamoaAndorraAngolaAnguillaAntarcticaAntigua and BarbudaArgentinaArmeniaArubaAustraliaAustriaAzerbaijanBahamasBahrainBangladeshBarbadosBelarusBelgiumBelizeBeninBermudaBhutanBolivia (Plurinational State of)Bonaire, Sint Eustatius and SabaBosnia and HerzegovinaBotswanaBouvet IslandBrazilBritish Indian Ocean TerritoryBrunei DarussalamBulgariaBurkina FasoBurundiCabo VerdeCambodiaCameroonCanadaCayman IslandsCentral African RepublicChadChileChinaChristmas IslandCocos (Keeling) IslandsColombiaComorosCongoCongo (Democratic Republic of the)Cook IslandsCosta RicaCroatiaCubaCuraçaoCyprusCzech RepublicCôte d’IvoireDenmarkDjiboutiDominicaDominican RepublicEcuadorEgyptEl SalvadorEquatorial GuineaEritreaEstoniaEthiopiaFalkland Islands (Malvinas)Faroe IslandsFijiFinlandFranceFrench GuianaFrench PolynesiaFrench Southern TerritoriesGabonGambiaGeorgiaGermanyGhanaGibraltarGreeceGreenlandGrenadaGuadeloupeGuamGuatemalaGuernseyGuineaGuinea-BissauGuyanaHaitiHeard Island and McDonald IslandsHoly SeeHondurasHong KongHungaryIcelandIndiaIndonesiaIran (Islamic Republic of)IraqIrelandIsle of ManIsraelItalyJamaicaJapanJerseyJordanKazakhstanKenyaKiribatiKorea (Democratic People’s Republic of)Korea (Republic of)Kosovo, Republic ofKuwaitKyrgyzstanLao People’s Democratic RepublicLatviaLebanonLesothoLiberiaLibyaLiechtensteinLithuaniaLuxembourgMacaoMacedonia (the former Yugoslav Republic of)MadagascarMalawiMalaysiaMaldivesMaliMaltaMarshall IslandsMartiniqueMauritaniaMauritiusMayotteMexicoMicronesia (Federated States of)Moldova (Republic of)MonacoMongoliaMontenegroMontserratMoroccoMozambiqueMyanmarNamibiaNauruNepalNetherlandsNew CaledoniaNew ZealandNicaraguaNigerNigeriaNiueNorfolk IslandNorthern Mariana IslandsNorwayOmanPakistanPalauPalestine, State ofPanamaPapua New GuineaParaguayPeruPhilippinesPitcairnPolandPortugalPuerto RicoQatarRomaniaRussian FederationRwandaRéunionSaint BarthélemySaint Helena, Ascension and Tristan da CunhaSaint Kitts and NevisSaint LuciaSaint Martin (French part)Saint Pierre and MiquelonSaint Vincent and the GrenadinesSamoaSan MarinoSao Tome and PrincipeSaudi ArabiaSenegalSerbiaSeychellesSierra LeoneSingaporeSint Maarten (Dutch part)SlovakiaSloveniaSolomon IslandsSomaliaSouth AfricaSouth Georgia and the South Sandwich IslandsSouth SudanSpainSri LankaSudanSurinameSvalbard and Jan MayenSwazilandSwedenSwitzerlandSyrian Arab RepublicTaiwan, Province of ChinaTajikistanTanzania, United Republic ofThailandTimor-LesteTogoTokelauTongaTrinidad and TobagoTunisiaTurkeyTurkmenistanTurks and Caicos IslandsTuvaluUgandaUkraineUnited Arab EmiratesUnited Kingdom of Great Britain and Northern IrelandUnited States Minor Outlying IslandsUnited States of AmericaUruguayUzbekistanVanuatuVenezuela (Bolivarian Republic of)VietNamVirgin Islands (British)Virgin Islands (U.S.)Wallis and FutunaWestern SaharaYemenZambiaZimbabweÅland IslandsNew Zealand
To be accepted into this programme you will need:
- A Bachelor’s degree with a major in Data Science, Computer Science, or Statistics with an average grade of B+ or better in the courses for those subjects.
- To be accepted by the head of school or nominee as capable of proceeding with the proposed course of study.
- With the approval of the Associate Dean, candidates with extensive practical, professional, or scholarly experience may gain entry to the programme without a Bachelor’s degree with the required major and grade average.
- If you want to enrol in this programme but don’t meet some of the entry requirements, you should contact the programme director or administrator to discuss your options.
- For more programme details and requirements, see the University Calendar. It’s an annual publication and an authoritative source for planning your degree.
For this programme you’ll need to:
- Complete 240 points:
- Part 1—Complete 60 points in:
- Machine Learning Tools and Techniques (AIML 421)
- Practical Data Science (Practical Data Science (DATA 471))
- Programming and Data Management (Data Management and Programming (DATA 472))
- Statistical Modelling for Data Science (Statistical Modelling for Data Science (DATA 473))
- Simulation and Stochastic Models (Simulation & Stochastic Models (DATA 474))
- Part 2—Complete 180 points in:
- Big Data (AIML 427)
- One course from:
- Research Preparation for Data Science (Research Preparation for Data Science (DATA 480))
- Either Research Project (15 points) (Research Project (DATA 487)) or Research Project (30 points) (Research Project (DATA 489))
- Advanced Techniques for Data Science (Advanced Techniques in Data Science (DATA 501))
- Data Science Practicum (Data Science Practicum (DATA 581))
- Computational Statistics (STAT 432)
- Generalised Linear Models (STAT 438)
- 30 or 45 further points from:
- Students will have an individual course of study approved, appropriate to their level of preparation.
- A candidate who has completed a Bachelor’s degree in Data Science or a double major in Computer Science and Statistics shall be exempted from Part 1 and admitted directly to Part 2.
- The Head of School of the School of Mathematics and Statistics may exempt a student from any 400-level DATA course in Part 1 for which the student has mastered the material through prior study.
- The Head of School of the School of Mathematics and Statistics may approve the substitution of DATA 588 for DATA 487 or DATA 581.
- The MDataSc may be awarded with Distinction or Merit as described in sections 20 and 22 of the Personal Courses of Study Regulations.