Program Overview

Master of Applied Data Science

The Master of Applied Data Science is a conversion Master's degree that accommodates students from a range of backgrounds who want to enhance or build their data science and analytics capabilities.

Introduction

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. This degree is designed for students who want to work in a range of industries, including government, corporates, the IT sector, market research, and finance.

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.

Entry Requirements

Potential students can come from a variety of undergraduate backgrounds. You will need a B Grade Point Average in 300-level bachelor's degree courses, or have evidence of achievement at postgraduate level.

• If you are an international student and need help meeting these requirements, study one of UC's International Pre-Master's pathways to gain entry into this degree.
• If you are a domestic student and need help meeting these requirements, study UC's Diploma in Advancing University Studies to gain entry into this degree.
• If English is not your first language, you are also required to meet UC's Postgraduate language requirements.

Degree Structure

The Master of Applied Data Science degree will comprise a minimum of 180 points as follows:

• Three Foundation Courses
• Four courses from advanced data science competencies
• At least 30 points from relevant elective options
• A Data Science project. You can study this qualification full-time within 1 to 1.5 years, or part-time in a maximum of 5 years.

Foundation Courses

You will be required to enrol in all these foundational courses unless there is evidence of your 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

Advanced Data Science Competencies

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

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

Data Science Project

Complete one of the following:

• DATA601 Applied Data Science Project
• DATA603 Applied Data Science Industry Project
• DATA605 Applied Data Science Industry Research Project

Elective Courses

The remaining 30 points will be any relevant 400 or 600-level courses in the following subjects:

• 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 Some examples of popular elective courses students have enrolled in recently include:
• 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

Fees

Domestic Students

• 2025 tuition fee estimate: $14,115 (180 points)
• 2026 tuition fee estimate: $14,963 (180 points)

International Students

• 2025 Special Programme Fee: $62,100 (180 points)
• 2026 Special Programme Fee: $56,850 (180 points)
• 2027 Special Programme Fee: $59,400 (180 points)

Student Services Levy (SSL)

• 2025 SSL: $9.72 per point ($1,166.40 per 120 points)
• 2026 SSL: $10.30 per point ($1,236.00 per 120 points)

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
• Finance
• Agriculture
• Transport A Master of Applied Data Science graduate's skills will include:
• Advanced knowledge in data science and business analytics
• The ability to use data to inform workplace solutions
• Planning and implementing data-informed projects
• Working in multidisciplinary teams
• Understanding of what programming can offer.