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).

• DATA401 Introduction to Data Science
• COSC480 Computer Programming
• MBIS623 Data Management

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

• DIGI405 Texts, Discourses and Data: the Humanities and Data Science
• STAT462 Data Mining
• DATA420 Scalable Data Science
• STAT448 Big Data

You should complete the foundation course DATA401, or have a background in statistics, before enrolling in STAT462 and STAT448.

You should also complete the foundation course COSC480, or have a background in Python computer programming, before enrolling in DATA420.

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:

• COSC421 Advanced Topics in Security
• COSC424 Secure Software
• COSC428 Computer Vision
• DATA415 Computational Social Choice
• DATA416 Contemporary Issues in Data Science
• DATA417 The Trustworthy Data Scientist
• DATA419 Online Communities and Social Networks
• DATA422 Data Wrangling
• DATA423 Data Science in Industry
• DATA424 Information is Beautiful
• DATA425 Foundations of Deep Learning
• DATA430 Medical Data Informatics
• DATA474 Special Topic - Legal, Regulatory, and Policy Considerations Around AI Technologies
• BIOL459 Genomics
• GISC404 Spatial Analysis
• GISC412 Spatial Data Science
• GISC422 Foundations of Geographic Information Systems
• HLTH462 Quantitative Health Methods
• INFO620 Information Systems Management
• INFO634 Data Analytics and Business Intelligence
• POLS443 Science, Technology and Environmental Policy
• STAT446 Advanced Generalised Linear and Multivariate Models
• STAT447 Official Statistics
• STAT450 Advanced Statistical Modelling
• STAT455 Data Collection and Sampling Methods
• STAT456 Time Series and Stochastic Processes
• STAT463 Advanced Multivariable Statistical Methods and Applications

• DATA601 Applied Data Science Project (45 points)

This compulsory project for the Master's programme 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.

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 Applied Data Science 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
• an understanding of what programming can offer.