Master of Data Science

This course provides students with the opportunity to engage in a semester-long work-orientated project or a work-integrated experience. This provides an excellent springboard for employment following this degree. Career pathways available to data science graduates include data scientist, data analyst, machine learning scientist, statistician, informatician, computational scientist. Graduates of this course will also have the option to pursue further study at the PhD level.

Possible future job titles

Data Scientist, Data Analyst, Informatician, Computational Scientist

Higher education

Academic admission requirements (Band 6) may be satisfied through completion of one of the following:

• Bachelor degree; or
• Equivalent prior learning including at least five years relevant professional experience.

English Proficiency Requirements

English competency requirements may be satisfied through completion of one of the following:

• IELTS Academic Overall band minimum score of 6.5 (no individual band less than 6.0);
• Bachelor degree from a country specified on the English Proficiency Bands page;
• Successfully completed 0.375 EFTSL of study at postgraduate level or higher at an Australian higher education provider (or equivalent);
• Where accepted, equivalent prior learning, including at least five years relevant professional experience; or
• Other tests, courses or programs defined on the English Proficiency Bands page.

If you're applying for a course and have previous study or professional experience, you may be eligible for what we call 'advanced standing'.

For more information and to apply please go to https://www.ecu.edu.au/future-students/course-entry/advanced-standing

Data Science is an inter-disciplinary field, drawing on mathematics, statistics, and computer science, that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.

This course provides the necessary foundations in the disciplines of mathematics, statistics and computer science, and develops student knowledge and skills in some of the key tools and techniques relevant to data science. It also pays specific attention to ethical issues surrounding the manner in which data is gathered, stored and analysed/utilised.

Data Science is a significant area of growth and potential employment in Australia and the Asia-Pacific region.

Recommended Study Pattern

Year 1 - Semester 1

• CSI6208 Programming Principles 20
• MAT5212 Biostatistics 20
• MAT6105 Mathematical Fundamentals 20

Year 1 - Semester 2

Students who commence the course midyear will complete their second and third semesters in reverse order.

• MAT6104 Applied Multivariate Statistics 20
• SCI6120 Science Communication and Ethics 20
• CSI6209 Artificial Intelligence 20

Year 2 - Semester 1

• MAT6206 Data Analysis and Visualisation 20
• CSI6207 Systems Analysis and Database Design 20
• MAT6100 Time Series Forecasting 20

Year 2 - Semester 2

Research or Industry Focused Capstone Project - Default Option

• CSI6224 ^ Applied Project 60

OR

Work Integrated Learning – For Approved Placements

• CSI6223 ^ Work Experience Project 60

Award Requirements

Students are required to complete 10 units.

• CSI6208 Programming Principles 20
• MAT5212 Biostatistics 20
• MAT6105 Mathematical Fundamentals 20
• MAT6104 Applied Multivariate Statistics 20
• SCI6120 Science Communication and Ethics 20
• CSI6209 Artificial Intelligence 20
• MAT6206 Data Analysis and Visualisation 20
• CSI6207 Systems Analysis and Database Design 20
• MAT6100 Time Series Forecasting 20

Research or Industry Focused Capstone Project - Default Option

• CSI6224 ^ Applied Project 60

OR

Work Integrated Learning – For Approved Placements

• CSI6223 ^ Work Experience Project 60