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Engineering and technology
Master of Applied Data Science
Master of Applied Data Science

Master of Applied Data Science

  • ID:UC640082
  • Level:Master's Degree
  • Duration:
  • Intake:

Fees (NZD)

Estimated Total/program:
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60
Accept letter
100
Visa
20
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1

Admission Requirements

Entry requirements

  • Potential students can come from a variety of undergraduate backgrounds. Students require a B Grade Point Average in 300-level bachelor's degree courses, or have evidence of achievement at postgraduate level.

English requirements

  • IELTS: Academic with an average score of 6.5, with a minimum of 6.0 in reading, writing, listening and speaking
  • TOEFL iBT: Total minimum score of 90, with at least 19 in reading, writing and listening. Please note UC only accepts TOEFL iBT scores from a single test date, not MyBest scores.
  • TOEFL PBT: With a minimum score of 575 and TWE with a minimum score of 4.5
  • CCEL EAP: Level 2 with a minimum C+ grade
  • CAE or CPE: minimum score of 176 with at least 169 in reading, writing, listening and speaking
  • Pearson Test of English (Academic): PTE with an overall score of 58 and no PTE communicative skills score below 50
  • NZCEL:  Level 5

Course Information

Data science is a new profession emerging along with the exponential growth in size and availability of 'big data'. A data scientist provides insight into future trends from looking at past and current data. Data science is an essential skillset in a world where everything from education to commerce, communication to transport, involves large-scale data collection and digitalisation.

This conversion Master's is designed to accommodate students from a range of backgrounds (not just those with Mathematics, Statistics, and Computer Science majors), who want to enhance or build their data science capabilities and combine these with the skills and knowledge they bring from their previous studies. So long as you are data-hungry and industry-aware; this degree can add to your employability and career prospects.

  • One of the few such programmes in Australasia that supports the development of students from a wider undergraduate background.
  • Work-integrated learning is a big component of the degree – you will work on an industry data science project.
  • There is also a focus on broader skills required of data scientists such as advanced analytical capability, problem solving, critical thinking, teamwork, and communication skills.

More info: Click here

Foundation courses

You will be required to enrol in all these foundational courses unless there is evidence of prior learning in the fundamentals of data science (exemptions must be approved by the Programme Director).

The courses are:

  • DATA 401 Statistics

  • COSC 480 Computer Programming

  • MBIS 623 Data Management

Advanced Data Science Competencies

All students take the following courses (unless the Programme Director approves a substitution).

Students are required to enrol in DIGI 405 and STAT 462 before enrolling in DATA 420 and STAT 448:

  • DIGI 405 Texts, Discourses and Data: the Humanities and Data Science

  • STAT 462 Data Mining

  • DATA 420 Scalable Data Science

  • STAT 448 Big Data

Compulsory course

DATA 601 Applied Data Science Project (45 points)

This compulsory project involves working in a team to solve real-world data science problems.

Elective courses

The remaining courses will be any relevant 400 or 600-level courses in: Biological Sciences, Computer Science, Data Science, Digital Humanities, Economics, Environmental Science, Finance, Geography, Geology, Mathematics, Physics, Psychology, Statistics. Or in any other relevant subject as approved by the Programme Director and the relevant Head of Department.

Some examples of elective courses students have enrolled in recently include:

  • COSC 421 Advanced Topics in Security

  • COSC 424 Secure Software

  • COSC 428 Computer Vision

  • DATA 415 Computational Social Choice

  • DATA 416 Contemporary Issues in Data Science

  • DATA 417 The Trustworthy Data Scientist

  • DATA 419 Online Communities and Social Networks

  • DATA 422 Data Wrangling

  • DATA 423 Data Science in Industry

  • DATA 424 Information is Beautiful

  • DATA 430 Medical Data Informatics

  • DATA 473 Special Topic: Foundations of Deep Learning

  • BIOL 459 Genomics

  • GISC 404 Spatial Analysis

  • GISC 412 Spatial Data Science

  • GISC 422 Foundations of Geographic Information Systems

  • HLTH 462 Quantitative Health Methods

  • INFO 620 Information Systems Management

  • INFO 634 Data Analytics and Business Intelligence

  • POLS 443 Science, Technology and Environmental Policy

  • STAT 446 Generalised Linear Models

  • STAT 447 Official Statistics

  • STAT 450 Advanced Statistical Modelling

  • STAT 455 Data Collection and Sampling Methods

  • STAT 456 Time Series and Stochastic Processes

  • STAT 463 Multivariate Statistical Methods

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Pre Courses

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Pathway Courses

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Career Opportunity

Career Opportunity

According to industry experts, data scientists know what the technology can offer, what analytics are possible, and can communicate on all those aspects to the wider business. This applies no matter the field or sector, as data and analytics have become so important and integral to organisational decision making. Graduates will be ready to work in a range of industries including: government, corporates, the IT sector, market research and finance, agriculture, and transport.

Aotearoa New Zealand and other countries are currently experiencing a skills shortage in this area, and the need for data-savvy professionals with applied experience is growing.

An MADS graduate's skills will include:

  • advanced knowledge in data science
  • the ability to use data to inform workplace solutions
  • planning and implementing data-informed projects
  • working in multidisciplinary teams
  • have an understanding of what programming can offer.

Ability to settle

Overseas Student Health Cover

Insurance/year: 700 NZD/per year

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