Top 200 worldwide for computer science and information systems
Globally recognised Australian degree in Singapore
Accredited by Australian Computer Society (ACS)
Why choose data science at Deakin
With every click, swipe, search, share, and stream data is generated at a phenomenal rate. Its volume and complexity create considerable opportunities as businesses seek to harness the power of big data to remain competitive. In the Bachelor of Data Science, you will explore the full lifecycle of data.
Build expertise in a growing field through innovative course content that reflects current trends in data science. Explore analytical methods, tools and techniques while building knowledge in areas including machine learning, artificial intelligence (AI), and predictive analytics. Graduate with specialised technical skills that are highly valued across industries.
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World-class Australian degree
Experience the best of Australian education and earn a globally recognised IT degree while studying in Singapore.
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Industry-informed curriculum
This course is designed in consultation with leading global technology companies and governments, ensuring you graduate ready to work in the rapidly growing IT industry.
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Practical experience with new technology
Benefit from Deakin's leading research in IT and AI and develop practical experience with advanced technologies throughout your degree.
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Graduate work-ready with ERCI
ERCI connects students with leading global industry partners through guest speakers, industry visits and projects. Build the networks and practical knowledge you need to graduate work-ready.
Connected to industry
Deakin’s strong industry connections help shape your learning. Build practical experience in real workplace contexts through work-integrated learning, mentoring and networking opportunities. Industry advisory boards also help shape our degrees, which means what you study is current, relevant and aligned to what your future employers need.
Deakin puts employability first
Career outcomes
Turn complex data into meaningful insights that shape business decisions. This degree prepares you for careers helping organisations solve problems, uncover opportunities and drive innovation across a wide range of industries.
Data scientist
Transform complex data into meaningful insights using statistical analysis, machine learning and predictive modelling. Help organisations solve problems, identify opportunities and support evidence-based decision-making.
- #11
Fastest-growing job globally
- 41%
Global job growth by 2030
Big data specialist
Design and manage the systems that capture, organise and process large volumes of complex data. Build scalable data solutions that enable organisations to analyse information and uncover valuable insights.
- #1
Fastest-growing job globally
- #1
Fastest-growing skills globally
Other jobs
- Data analyst
- Business strategist
- Data engineer
- Data architect
- Data visualisation specialist
- Information analyst
*Deakin references data from a range of government, higher education and reputable media sources. Learn more about our achievements on our University rankings page, or explore our sources page for supporting references.
What will I study in the Bachelor of Data Science?
The Bachelor of Data Science is a three-year degree. You will develop strong foundations in computing, statistics and data analysis before progressing to advanced techniques that turn complex data into meaningful insights.
Build the foundations of data science
Develop programming and data skills
Learn how to write code, manage datasets and build simple data-driven applications to analyse information.
Strengthen mathematical foundations
Apply statistics and quantitative reasoning to understand patterns and relationships within data.
Build analytical problem-solving
Learn how to frame questions, interpret results and communicate insights from data clearly.
Develop your data science expertise
Advance data analysis capability
Explore techniques used to organise, analyse and visualise complex data sets.
Work with modern data systems
Use data platforms, databases and computational tools for large-scale analytics.
Apply learning in practical contexts
Complete projects that simulate data science challenges faced by organisations.
Advanced data science in practice
Develop advanced data science techniques
Engage with machine learning and predictive analytics used to uncover patterns and inform decisions.
Apply data skills in authentic settings
Participate in capstone or professional practice experiences based on real analytical problems.
Strengthen career-ready capabilities
Refine communication, teamwork and ethical awareness required for responsible data practice.
Course structure
To complete the Bachelor of Data Science, you must pass 24 credit points. This includes:
- DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in your first study period
- STP010 Career Tools for Employability (0-credit-point compulsory unit)
- 17 credit points of core units
- 3 credit points of capstone units
- 1 minor (4 credit points)
- a maximum of 10 credit points at level 1
- a minimum of 14 credit points over levels 2 and 3
- a minimum of 6 credit points at level 3.
Most units are equal to one credit point.
As a full-time student you will study four credit points per trimester and usually undertake two trimesters per year.
All students are required to meet the University's academic progress and conduct requirements.
Are you a current student? For course information that applies to the year you started your degree, visit the handbook.
All students are required to meet the University's academic progress and conduct requirements
Units
You are required to complete 17 core units plus three credit points of capstone units (these are essential units for this degree).
In your first trimester you must also complete two 0-credit point units which are compulsory for this degree.
Year 1 - Trimester 1
Year 1 - Trimester 2
Year 1 Trimester 3
Year 2 - Trimester 1
Plus 1 of:
1 minor unit (1 credit point) OR 2 minor units (2 credit points)
Year 2 - Trimester 2
Plus one of
Year 2 - Trimester 3
One (1) capstone unit (one (1) credit point):
Year 3 - Trimester 1
Plus one (1) minor unit (1credit point)
Plus one (1) capstone unit (1credit point):
Year 3 - Trimester 2
Plus one (1) minor unit (1credit point)
Plus one (1) capstone unit (1 credit point):
^ Offered in Trimester 1, Trimester 2 and Trimester 3.
# Corequisite of STP010 Career Tools for Employability (0-credit point compulsory unit).
+ Students must have completed STP010 Career Tools for Employability (0-credit point compulsory unit) and SIT223 Professional Practice in IT.
You must complete one of these minor sequences:
Refer to the details of each minor sequence for availability.
What to expect while studying
This program, delivered by Deakin University and ERC Institute is an exciting partnership between two quality institutions. It provides an opportunity for international students to experience the best of Australian teaching and learning practices while based in Singapore. This course is not available to international students studying online or onshore at campuses in Australia.
The learning experiences and assessment activities within this course require that students have access to a range of technologies beyond a desktop computer or laptop. Students will be required to purchase minor equipment, such as small single board computers, microcontrollers and sensors, which will be used within a range of units in this course. This equipment is also usable by the student beyond their studies. Equipment requirements and details of suppliers will be provided on a per-unit basis. The indicative cost of this equipment for this course is AUD$500.
For information regarding hardware and software requirements, please refer to the Bring your own device (BYOD) guidelines via the School of Information Technology website in addition to the individual unit outlines in the Handbook.
You can expect to participate in a range of teaching activities each week. This could include lectures, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.
When can I start?
When you study depends on your course, location and available intakes. Check the table to see when you can start and how study is offered throughout the year.
This course is intended for students studying onshore in Singapore, with located learning support provided by ERC Institute.
This course is not available to domestic and international students studying online or onshore at campuses in Australia.
Your course learning outcomes describe the knowledge, skills and capabilities you’ll develop and be able to demonstrate by the time you graduate. Built into your course through your units and assessments, they provide a clear picture of what you’ll be equipped to know, understand and do – preparing you to apply your learning with confidence beyond university.
| Course Learning Outcomes |
|---|
| Develop a broad and coherent knowledge of data science, with detailed knowledge of the data analytics principles and approaches and knowledge, skills, tools, and methodologies for professional practice. |
| Communicate in a professional context to inform, motivate, and effect change, and to drive sustainable innovation, utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences. |
| Utilise a range of digital technologies and information sources to discover, analyse, evaluate, select, process, and disseminate both technical and non-technical information in data science projects. |
| Evaluate information and evidence, applying critical and analytical thinking and reasoning, technical skills, personal judgement, and values, in decision making processes. |
| Apply theoretical constructs and skills and critical analysis to real-world and ill-defined problems and develop innovative data analytics solutions. |
| Work independently to apply knowledge and skills to new situations in professional practice and/or further learning in the field of data science with adaptability, autonomy, responsibility, and personal accountability for actions as a practitioner and a learner. |
| Contribute effectively as a skilled and knowledgeable individual to the processes and output of a work unit or team, applying specific knowledge and skills and using professional practices associated with the information technology industry. |
| Apply professional and ethical standards and accountability in the preparation, handling, and analysis of data. |
- Award granted
- Bachelor of Data Science
- Year
2027 course information
- Deakin code
- S379E
- Level
- Undergraduate
- Australian Qualifications Framework (AQF) recognition
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 7
Fees
Please contact the ERC Institute for Bachelor of Data Science fee information.
Scholarships
We want to help you excel at Deakin. Our scholarships recognise your dedication and achievements, providing financial support that can ease the cost of living and studying. With less pressure, you'll have more freedom to focus on what matters most – your education and future success.
Apply now
Apply through ERC Institute
Applications can be made directly to ERC Institute. For more information on the application process and closing dates, please contact ERC Institute directly by emailing enquiry@erci.edu.sg or call +65 6349 2727.
Recognition of prior learning
We value your previous study and experience. Recognition of prior learning enables you to get credit for what you've already achieved. When you apply, we'll consider your previous study and experience for recognition of prior learning.