坎特伯雷大學(xué)

Data is used by organisations of all sizes to make better decisions. In this degree, you will learn how to analyse and interpret data to inform decision-making and forecast trends.

With big data comes big responsibility, and you will learn the importance of data security, ethics, and strategy. You will learn skills in programming, mathematics, and statistics from experts in biology, computing, geography, linguistics, and many other fields. As a result, you will be able to contribute your diverse skillset across many cross-disciplinary fields.

A number of our research centres utilise data science.

The Bachelor of Data Science requires a minimum total of 360 points:

• 195 points of compulsory Data Science core courses
• 165 points of courses towards your major.

At least 225 points must be from courses above 100-level, with at least 105 points at 300-level.

Each major has specific course requirements, but all consist of a minimum 165 points, with at least 45 points at 200-level or above and at least 60 points at 300-level.

The Bachelor of Data Science includes core introductory courses in programming, mathematics, statistics, and computer sciences, as well as hands-on lab work and group projects.

You will also complete courses towards a major subject, completing with a final capstone project in the third year with supervision from industry.

Major subjects

• Bioinformatics
• Computational Linguistics
• Data Science
• Population Health Data Science
• Spatial Data Science

Further study

UC offers postgraduate studies in Data Science:

• Bachelor of Science with Honours
• Postgraduate Certificate in Science
• Postgraduate Diploma in Science
• Master of Science

There are also specialist applied studies available:

• Postgraduate Diploma in Applied Data Science
• Master of Applied Data Science
• Master of Spatial Analysis for Public Health
• Professional Master of Geospatial Science and Technology

Career Opportunities

As data increases exponentially, there is a high demand for people who can store, organise, and analyse big data for many different uses.

Roles include data scientist, data analyst, data architect, solutions architect, business analyst, information technology consultant, statistician, marketing analyst, and other IT or software engineering related positions.