Qualification

Master of Applied Data Science

Overview

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.

Features of the Master of Applied Data Science (MADS)

  • 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.
  • UC has strengths in the area of data science, including a number of relevant research centres (eg, Geospatial Research Institute, HIT Lab NZ, High Performance Computing, Wireless Research Centre, Digital Arts, Social Sciences and Humanities).

Entry requirements

Potential students can come from a variety of undergraduate backgrounds. Candidates would require a B average in relevant 300-level Bachelor's courses or show evidence of achievement at postgraduate level.

See the university regulations for this award for more information on what candidates should have before applying to enrol. 

Qualification structure and duration

The degree will comprise a minimum of 180 points as follows:

You can study this qualification full-time (in a minimum of 12 months) and part-time (in a maximum of five years). It can be started in February or July.

Subjects and courses

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:

Group A: Advanced Data Science Competencies

You will be required to take the following courses (unless the Programme Director approves a substitution):

* In 2017 DIGI401 is not offered; students are recommended to take DIGI405 Digital Humanities Research Methods 2 instead.

Group B: Domain Specific Competencies

The remaining courses will be any relevant 400 or 600-level courses in: Biological SciencesComputer ScienceDigital HumanitiesEconomicsEnvironmental ScienceFinanceGeographyGeologyMathematicsPhysicsPsychologyStatistics. Or in any other relevant subject as approved by the Programme Director and the relevant Head of Department.

Some examples of group B courses students have enrolled in recently include BIOL459 Genomics; HLTH 462 Quantitative Health Methods; INFO620 Information Systems Management; MBIS601 Management of Information Systems; MBIS622 IS Security and Risk Management; POLS443 Science, Technology and Environmental Policy; STAT446 Generalised Linear Models; STAT450 Advanced Statistical Modelling; STAT455 Data Collection and Sampling Methods; STAT456 Time Series and Stochastic Processes; STAT462 Data Mining; and STAT463 Multivariate Statistical Methods.

DATA601 Applied Data Science Project (45 points)

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

Career opportunities

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.

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.

More information

For full requirements see the Regulations for the Master of Applied Data Science.

For study planning help contact:

School of Mathematics and Statistics

Location
Corner of Science and Engineering Roads – see the School website for up-to-date location details

Postal address
University of Canterbury
Te Whare Wānanga o Waitaha
Private Bag 4800
Christchurch 8140
New Zealand

Phone +64 3 364 2600 
Email enquiries@math.canterbury.ac.nz