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Data Science Double Degree Major (BSc/BA) / Data Science Double Degree Major (BSc/BCom)

Non-Award

Data scientists work at the interface of computing, statistics, visualisation and media to collate and analyse large volumes of data and communicate findings to various audiences. This course is part of a double degree combination, offering flexibility in study options.

Key details

Degree Type

Non-Award

Course Code

MDDU-DATSC

About this course

Overview

Data scientists work at the interface of computing, statistics, visualisation and media to collate and analyse large volumes of data and then communicate findings to a range of audiences. Their ability to leverage big data to predict future trends is becoming an essential part of decision-making in business and government.

This course sits within the double degree combination of Bachelor of Science/Bachelor of Arts, and also the Bachelor of Science/Bachelor of Commerce. Applicants have the choice of which double degree combination they would like to study.

What jobs can the Data Science course lead to?

Marketing and advertising data analyst
Pricing or financial analyst
Game designer
Health and allied health data analyst
Business intelligence analyst
Machine learning specialist
Information security technologist
Growth analyst
IT statistician

What you'll learn

Understand the theoretical background to processes for efficient collection, management, secure storage and analysis of large data sets
Formulate hypotheses about data and develop innovative strategies for testing them by implement appropriate algorithms to analyse both large and small datasets
Extract valid and meaningful conclusions from various types of large data sets that can support evidence based decision making
Communicate approaches and solutions to data science problems to a range of audiences in a variety of modes
Identify, select and use appropriate open source and proprietary data management and analysis tools to identify patterns or relationships in large volumes of data
Recognise the importance of continuous learning opportunities in a rapidly developing field and engage in self-driven development as a data scientist
Understand the global nature of data science and apply appropriate international standards in data science and data analytics
Work collaboratively and respectfully with data scientists from a range of cultural backgrounds
Work professionally and ethically on independent data science projects and as a team member working collaboratively to innovative data science solutions

Entry requirements

Admission criteria

What you need in order to get into this course. There are different pathway options depending on your level of work and education experience.

Select an option that best suits you:

You're considered someone with work and life experience if:

You have left secondary education more than two years ago (i.e. who are not classified as recent secondary education applicants) and have not undertaken vocational education training (VET) or higher education study since then.

How we define 'experience'

'Experience' includes a combination of factors sufficient to demonstrate readiness for higher education such as mature-age entry, professional experience whether completion of the Skills for Tertiary Admissions Test (STAT) is required or not, community involvement or work experience. Applicants may have undertaken non-formal programs that have helped prepare them for tertiary education or are relevant to the proposed higher education field of study.

Pathways

STAT entry

Special Tertiary Admissions Test (STAT)

The Skills for Tertiary Admissions Test (STAT) is a national test for those who don't meet university admission criteria. STAT can be used to meet entry criteria for some courses, or as a way to satisfy Curtin's English proficiency requirements.

STAT is not accepted as an entry pathway, but may be used to demonstrate English language proficiency.

English requirements

Curtin requires all applicants to demonstrate proficiency in English. Specific English requirements for this course are outlined in the IELTS table below.

You may demonstrate English proficiency using the following tests and qualifications.

IELTS Academic (International English Language Testing System)

Writing: 6
Speaking: 6
Reading: 6
Listening: 6
Overall band score: 6

What you will learn

What you'll learn

understand the theoretical background to processes for efficient collection, management, secure storage and analysis of large data sets
formulate hypotheses about data and develop innovative strategies for testing them by implement appropriate algorithms to analyse both large and small datasets
extract valid and meaningful conclusions from various types of large data sets that can support evidence based decision making
communicate approaches and solutions to data science problems to a range of audiences in a variety of modes
identify, select and use appropriate open source and proprietary data management and analysis tools to identify patterns or relationships in large volumes of data
recognise the importance of continuous learning opportunities in a rapidly developing field and engage in self-driven development as a data scientist
understand the global nature of data science and apply appropriate international standards in data science and data analytics
work collaboratively and respectfully with data scientists from a range of cultural backgrounds
work professionally and ethically on independent data science projects and as a team member working collaboratively to innovative data science solutions

Career pathways

### What jobs can the Data Science course lead to? * Marketing and advertising data analyst * Pricing or financial analyst * Game designer * Health and allied health data analyst * Business intelligence analyst * Machine learning specialist * Information security technologist * Growth analyst * IT statistician

Credit for prior study or work

Credit for recognised learning (CRL) ### Use your experience to get credit towards your degree Finish your course sooner with credit for your previous study or work experience. Submit an enquiryCRL search

How to apply

## How to applyPlease review information on how to apply for the campus of your choiceApply now * The offering information on this website applies only to future students. Current students should refer to faculty handbooks for current or past course information.The information on this page may be subject to change. In particular, Curtin University may change the content, method or location of delivery or tuition fees of courses.While Curtin uses reasonable efforts to ensure that the information provided on this page is accurate and up to date, errors and omissions sometimes occur. Curtin makes no warranty, representation or undertaking (expressed or implied) nor does it assume any legal liability (direct or indirect) for the accuracy, completeness or usefulness of any information.View courses information disclaimer. * Curtin course code: MDDU-DATSC * Last updated on: 13 October 2025