Bachelor of Data Science
Blended learning – on-campus and digital learning
With a Bachelor of Data Science learn how to interpret and harness the power of data for a career at the forefront of data-driven decision making and forecasting.
Unlock the statistical methods and tools you need to manage big data sets, as well as the most up-to-date visualisation techniques needed to represent and understand that data. Gain meaningful insights into how data is used, not only to solve problems across a range of industries, but also how to spot problems before they arise.
With hands-on learning and using contemporary tools, you’ll build in-demand skills for a rewarding career in our data-driven world.
Our Work Integrated Learning program bolsters your CV with real industry experience such as placements, internships and industry-linked projects. In this course, you’ll undertake six projects – one per semester – and each will build on the last.
Upon graduation, you’ll be ready to apply for data science roles, such as data scientist, data analyst, business intelligence developer or data infrastructure architect.
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VTAC codes
- 3400212641 (CSP)
- 3400212643 (IFP)
Course details
- Course structure and career opportunities.
Course structure
Successful completion of the Bachelor of Data Science requires students to complete units of study to the value of 300 credit points. All units of study are valued at 12.5 credit points unless otherwise stated.
View course rules and special requirements
| Units | Unit codes | Credit points |
|---|---|---|
| Computer Systems | COS10004 | |
| Introduction to Programming | COS10009 | |
| Technology in an Indigenous Context Project | COS10025 | |
| Computing Technology Inquiry Project | COS10026 | |
| Networks and Switching | TNE10006 | |
| Object Oriented Programming | COS20007 | |
| Computing Technology Project A * | COS40005 | |
| Computing Technology Project B * | COS40006 |
*Outcome unit – completion demonstrates the attainment of course learning outcomes
+
Learn the statistical methods and tools needed to manage big data sets and the visualisation techniques needed to represent and understand that data.
| Units | Unit codes | Credit points |
|---|---|---|
| Introduction to Data Science | COS10022 | 12.5 |
| Cloud Computing Architecture | COS20019 | 12.5 |
| Big Data Architecture and Application * | COS20028 | 12.5 |
| Computing Technology Design Project | COS20031 | 12.5 |
| Data Visualisation * | COS30045 | 12.5 |
| Computing Technology Innovation Project * | COS30049 | 12.5 |
| Software Architectures and Design * | SWE30003 | 12.5 |
| Software Deployment and Evolution | SWE40006 | 12.5 |
*Outcome unit – completion demonstrates the attainment of course learning outcomes
+
Other studies
8 units (100 credit points)
Choose from a combination of the following course components to complete 100 credit points of other study. Students may also select elective units (12.5 credit points each).
Work Integrated Learning
Swinburne's Work Integrated Learning program provides additional opportunities for you to gain valuable skills and real industry experience in the form of placements, internships or study tours - all while earning credit towards your degree.
Choose a Work Integrated Learning option:
You'll get paid to work in an area related to your field of study for 12 months, where you'll combine hands-on learning with academic submissions, workplace reflection and feedback from your host organisation. Most students undertake their placements in the third year of their degree, so you’ll want to map out your electives as soon as you can and register for a placement at least 6 months before your preferred start date.
The Professional Placement co-major has four 25 credit point units.
Professional Placement in Information and Communication Technology
| Units | Unit codes | Credit points |
|---|---|---|
| Work Experience in Industry A | WEI20001 | 25 |
| Integrated Professional Placement A - Information and Communication Technology | ICT20013 | 25 |
| Work Experience in Industry B | WEI20002 | 25 |
| Integrated Professional Placement B - Information and Communication Technology | ICT20014 | 25 |
You'll get paid to work in an area related to your field of study for 6 months, where you'll combine hands-on learning with academic submissions, workplace reflection and feedback from your host organisation. Most students undertake their placements in the third year of their degree, so you’ll want to map out your electives as soon as you can and register for a placement at least 6 months before your preferred start date.
The Professional Placement minor has two 25 credit point units.
Professional Placement in Information and Communication Technology
| Units | Unit codes | Credit points |
|---|---|---|
| Work Experience in Industry A | WEI20001 | 25 |
| Integrated Professional Placement A - Information and Communication Technology | ICT20013 | 25 |
A Professional Internship is all about gaining valuable real-world skills in your area of study all while earning credit points towards your degree. Plus, it looks great on your CV as it shows you’ve had real industry experience before you’ve even graduated!
You might choose to complete your internship part-time over a semester or in a more intensive block during Summer or Winter terms.
Travel overseas, discover other cultures, enrich your professional experience and enhance your CV all while gaining credit towards your course.
- Full-time study: 100 credit points/eight standard units of study per year
- Part-time study: 50 credit points/four standard units of study per year
- One credit point is equivalent to one hour of study per week per semester (including contact hours and private study)
- See the course planner for an example degree structure
Course learning outcomes
On successful completion of this Course students will be able to :
1. Apply a broad and coherent knowledge of data science in diverse contexts and domains using critical thinking and judgment
2. Employ appropriate methods and contemporary tools used in different domains of data science
3. Communicate proficiently to a variety of audiences, function as an effective member or leader of a team, and use the contemporary tools and practices of project management within project work
4. Demonstrate professionalism, integrity, ethical conduct, professional accountability and an awareness of professional practice in a global context
5. Utilise data analysis and decision-making methodologies to glean insights into industry relevant problems for the benefit of organisations
6. Reflect on personal performance, learning, and self-management processes as a means of continued professional development and lifelong learning
Career opportunities
Graduates of this course will have extensive skills in data science, particularly relating to medium- and large-scale projects. They will have developed experience in working on team projects and will have well-developed oral and written communication skills. Potential career options for the graduates of this course include data scientist, data engineer, machine learning engineer, data warehouse architect, and data analyst.
Fees
- Fees for 2022.
Students who participate in a six- or 12-month professional placement will be subject to an increase in total course fees.
| 2022 rate* | Estimated total cost of the course | Estimated cost of the course per year if studying full-time* | Amenities fee per year if studying full-time* |
|---|---|---|---|
| Commonwealth Supported Place (CSP) |
$24,063 | $8,021 | See how your SSAF is calculated |
How do I pay my fees?
HECS-HELP is a loan and discount scheme available to eligible students enrolled in a Commonwealth supported place. A HECS-HELP loan can cover all or part of the student contribution amount.
Find out more about fees.
Scholarships
At Swinburne scholarships are about providing opportunity, promoting equity and recognising excellence and achievement. Scholarships are available for both commencing and current students.
How to enter this course
- Entry requirements, pathways, credit transfer and recognition of prior learning.
How to apply
Find out more about how to apply.