Master of Applied Data Science

Summary

Data science is a new profession, emerging along with the exponential growth in size and availability of 'big data'. A data scientist provides business analytics and insight into future trends from looking at existing data. Data science is an essential skillset in a world where almost every industry involves large-scale data collection and digitalisation.

This conversion Master’s degree accommodates 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 and analytics capabilities.

What will my study involve?

• One of the few such programmes in Australasia that supports your development from a wider undergraduate study background.
• Potential for work-integrated learning — you may be able to work on an industry data science project during your studies.
• Option to study via distance learning off campus from any location.
• 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, Toi Hangarau | Geospatial Research Institute, Tangata Hangarau, Hangarau Tangata | HIT Lab NZ, Wireless Research Centre, Digital Humanities).

Subjects and Courses

• all foundation courses
• all advanced data science competencies
• one Data Science Project course
• an additional 30 points from either the listed elective courses (for the unendorsed degree) or from the endorsement options (for the endorsed degree).
• DATA401 Introduction to Data Science
• COSC480 Computer Programming
• MBIS623 Data Management
• DATA420 Scalable Data Science
• DIGI405 Texts, Discourses and Data: the Humanities and Data Science
• STAT448 Big Data
• STAT462 Data Mining
• DATA601 Applied Data Science Project
• DATA603 Applied Data Science Industry Project
• DATA605 Applied Data Science Industry Research Project
• Applied AI
• Biological Sciences
• Chemistry
• Computer Science
• Data Science
• Digital Humanities
• Economics
• Environmental Science
• Finance
• Geography
• Geology
• Geospatial Data Science
• Health
• Information Systems
• Mathematics
• Philosophy
• Physics
• Project Management
• Psychology
• Statistics
• COSC428 Computer Vision
• COSC401 Machine Learning
• COSC440 Deep Learning
• DATA415 Computational Social Choice
• DATA416 Contemporary Issues in Data Science
• DATA422 Data Wrangling
• DATA423 Data Science in Industry
• DATA424 Information is Beautiful
• DATA425 Foundations of Deep Learning
• GISC401 Foundations of Geospatial Data Science
• GISC404 Spatial Analysis
• GISC412 advanced Methods in Geospatial Data Science
• GISC422 Foundations of Geographic Information Systems
• INFO621 AI in Business
• INFO634 Data Analytics and Business Intelligence
• STAT447 Official Statistics
• STAT455 Data Collection and Sampling Methods
• STAT456 Time Series and Stochastic Processes
• STAT463 Advanced Multivariable Statistical Methods and Applications
• PSYC486 Computational Methods in Psychological Science
• HLTH402 Health Information Management
• Geographic Information Systems (GIS)
• Digital Humanities and Computational Social Science