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.
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
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:
Insurance/year: 700 NZD/per year