Postgraduate Diploma in Applied Data Science
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. This is an essential skillset in a world where everything from education to commerce, communication to transport, involves large-scale data collection and digitalisation.
This Postgraduate Diploma 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.
- 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 | Toi Hangarau, HIT Lab NZ | Tangata Hangarau, Hangarau Tangata, High Performance Computing, Wireless Research Centre, Digital Humanities).
Potential students can come from a variety of undergraduate backgrounds. Students require a B Grade Point Average in their 300-level bachelor's degree courses, or have evidence of achievement at postgraduate level.
Students with English as their additional language are also required to meet UC's English language requirements.
For the full entry requirements see the Regulations for the Postgraduate Diploma in Applied Data Science or use the admission requirements checker.
How to apply
You can apply online at myUC. Find out more about how to apply for graduate and postgraduate qualifications.
The Diploma will comprise a minimum of 120 points as follows:
- up to 45 points from the Foundation Courses
- all courses from Group A: Advanced Data Science Competencies
- at least 15 points from Group B: Domain Specific Competencies.
You can study this qualification full-time in a minimum of 1 year (2 semesters) or part-time in a maximum of 4 years.
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):
Group B: Domain specific competencies
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 Group B courses students have enrolled in recently include:
- DATA 422 Data Wrangling
- DATA 423 Data Science in Industry
- DATA 430 Medical Data Informatics
- DATA 471 Special Topic: The Trustworthy Data Scientist
- DATA 473 Special Topic: Societal Impacts of A.I.
- DATA 474 Special Topic: Computational Social Choice
- DATA 475 Special Topic: Mixed Reality
- DATA 476 Special Topic: Information is Beautiful
- BIOL 459 Genomics
- HLTH 462 Quantitative Health Methods
- INFO 620 Information Systems Management
- INFO 634 Data Analytics and Business Intelligence
- MBIS 601 Management of Information Systems
- MBIS 622 IS Security and Risk Management
- 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
Provided you have not graduated with the Diploma and you fulfil the entry requirements, you can transfer to the Master of Applied Data Science.
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.
A PGDipADS 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.
- Read what other UC postgraduate students have gone on to achieve in their studies and careers in our student and graduate profiles.
- Te Rōpū Rapuara | UC Careers can help you to achieve the career you want, connect with employers, or find a job.
- For research into career destinations by qualification, visit Te Pōkai Tara | Universities New Zealand website.
- Find out more about what you can do with a degree from UC.
- Come along to an upcoming information event for prospective postgraduate students.
See Tuition Fee Structure for more information
|2019||120||Banded Fee - total tuition fee dependent on course selection||$8,014|
|2020||120||Banded Fee - total tuition fee dependent on course selection||$8,174|
|2019||120||Special (Set) Programme Fee||$25,000|
|2020||120||Special (Set) Programme Fee||$27,500|
For full requirements see the Regulations for the Postgraduate Diploma in Applied Data Science.
For study planning help contact the School of Mathematics and Statistics or the College of Engineering:
College of Engineering | Te Rāngai Pūkaha
University of Canterbury | Te Whare Wānanga o Waitaha
Private Bag 4800